WO2021229477A1 - Recours à des vérifications d'état de santé fondées sur des technologies portées sur soi afin d'enrayer la propagation d'épidémies - Google Patents

Recours à des vérifications d'état de santé fondées sur des technologies portées sur soi afin d'enrayer la propagation d'épidémies Download PDF

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Publication number
WO2021229477A1
WO2021229477A1 PCT/IB2021/054072 IB2021054072W WO2021229477A1 WO 2021229477 A1 WO2021229477 A1 WO 2021229477A1 IB 2021054072 W IB2021054072 W IB 2021054072W WO 2021229477 A1 WO2021229477 A1 WO 2021229477A1
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WIPO (PCT)
Prior art keywords
user
measurements
users
wearable device
computer
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PCT/IB2021/054072
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English (en)
Inventor
Ari M FRANK
Arie Tzvieli
Ori Tzvieli
Gil Thieberger
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Facense Ltd.
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Publication of WO2021229477A1 publication Critical patent/WO2021229477A1/fr

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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02416—Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/117—Identification of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/20—Individual registration on entry or exit involving the use of a pass
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/20—Individual registration on entry or exit involving the use of a pass
    • G07C9/22—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
    • G07C9/25—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition
    • G07C9/26—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition using a biometric sensor integrated in the pass
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
    • G08B21/0438—Sensor means for detecting
    • G08B21/0453—Sensor means for detecting worn on the body to detect health condition by physiological monitoring, e.g. electrocardiogram, temperature, breathing

Definitions

  • This application relates to head-mounted systems, such as smartglasses, configured to detect physiological parameters.
  • Epidemic diseases like the flu and COVID-19 can spread easily through interactions and gatherings of people in enclosed locations such as workplaces, schools, etc. It is very difficult to keep track of the health state of all the people involved in such interactions, in order to limit interactions that may put people at risk of being infected with a contagious disease.
  • Managing physical access to locations can be especially challenging when precautions need to be taken in order to curb the spread of diseases such as the flu or COVID-19.
  • Some aspects of this disclosure use authenticated wearable -based health state verifications in order to authorize access to such locations, which can help curb the spread of these diseases.
  • Some aspects of this disclosure involve privacy -preserving mechanisms in which wearables can be used to grant access to locations without the need to identify users.
  • Other aspects of this disclosure involve utilizing wearable devices that measure physiological signals of users in order to determine whether people who were at a location were healthy, and thus be able to certify the location as contagion-safe.
  • FIG. 1 is a schematic illustration embodiments of a system configured to grant passage through a doorway based on a user’s health state;
  • FIG. 2 illustrates an example of smartglasses that may be considered an embodiment of a wearable device that is utilized in some embodiments described herein;
  • FIG. 3 illustrates examples of automatic doors
  • FIG. 4 illustrates components of an embodiment of a system configured to manage access using reservations and wearable -based health state verifications
  • FIG. 5 illustrates steps that may be part of embodiments of a method for managing reservations with wearable-based health state verifications
  • FIG. 6 is a schematic illustration of a doorway system
  • FIG. 7 is a schematic illustration of components of a system configured to authorize physical access to a location based on an authenticated health score
  • FIG. 8 illustrates a flowchart according to which a computer may operate a barrier disposed in a doorway
  • FIG. 9 illustrates steps that may be part of embodiments of a method for managing authorization of access to a location based on authenticated health scores
  • FIG. 10 is a schematic illustration of an embodiment of a system configured to configured to certify a premises as contagion-safe;
  • FIG. 11 is a schematic illustration of an embodiment of a system for managing access to a contagion-safe premises
  • FIG. 12 illustrates steps that may be part of embodiments of a method for certifying a premises as contagion-safe
  • FIG. 13 illustrates steps that may be part of embodiments of a method for managing access to a contagion-safe premises
  • FIG. 14A and FIG. 14B are schematic illustrations of possible embodiments for computers.
  • photoplethysmogram signal “photoplethysmographic signal”, “photoplethysmography signal”, and other similar variations are interchangeable and refer to the same type of signal.
  • a photoplethysmogram signal may be referred to as a “PPG signal”, or an “iPPG signal” when specifically referring to a PPG signal obtained from a camera.
  • the terms “photoplethysmography device”, “photoplethysmographic device”, “photoplethysmogram device”, and other similar variations are also interchangeable and refer to the same type of device that measures a signal from which it is possible to extract the photoplethysmogram signal.
  • the photoplethysmography device may be referred to as “PPG device”.
  • Sentences in the form of “a sensor configured to measure a signal indicative of a photoplethysmogram signal” refer to at least one of: (i) a contact PPG device, such as a pulse oximeter that illuminates the skin and measures changes in light absorption, where the changes in light absorption are indicative of the PPG signal, and (ii) a non-contact camera that captures images of the skin, where a computer extracts the PPG signal from the images using an imaging photoplethysmography (iPPG) technique.
  • a contact PPG device such as a pulse oximeter that illuminates the skin and measures changes in light absorption, where the changes in light absorption are indicative of the PPG signal
  • a non-contact camera that captures images of the skin
  • iPPG remote photoplethysmography
  • rPPG remote photoplethysmographic imaging
  • MPPG multi-site photoplethysmography
  • camera-based blood perfusion camera-based hemoglobin concentration
  • camera-based hemoglobin concentration camera-based hemoglobin concentration
  • camera-based blood flow camera-based hemoglobin concentration
  • Additional names known in the art for iPPG from facial images include: facial hemoglobin concentration map, facial hemoglobin concentration changes, dynamic hemoglobin concentration/information extraction, facial blood flow map, facial blood flow changes, facial blood pulsation, facial blood perfusion, and transdermal optical imaging.
  • a PPG signal is often obtained by using a pulse oximeter, which illuminates the skin and measures changes in light absorption.
  • a pulse oximeter which illuminates the skin and measures changes in light absorption.
  • Another possibility for obtaining the PPG signal is using an imaging photoplethysmography (iPPG) device.
  • iPPG imaging photoplethysmography
  • iPPG does not require contact with the skin and is obtained by a non-contact sensor, such as a video camera.
  • a time series of values measured by a PPG device which is indicative of blood flow changes due to pulse waves, is typically referred to as a waveform (or PPG waveform to indicate it is obtained with a PPG device).
  • Analysis of PPG signals usually includes the following steps: filtration of a PPG signal (such as applying bandpass filtering and/or heuristic filtering), extraction of feature values from fiducial points in the PPG signal (and in some cases may also include extraction of feature values from non-fiducial points in the PPG signal), and analysis of the feature values.
  • One type of features that is often used when performing calculations involving PPG signals involves fiducial points related to the waveforms of the PPG signal and/or to functions thereof (such as various derivatives of the PPG signal). There are many known techniques to identify the fiducial points in the PPG signal, and to extract the feature values. Examples of features that can be extracted from the PPG signal, together with schematic illustrations of the feature locations on the PPG signal, can be found in the following four publications and their references: (i) Charlton, Peter H., et al. "Assessing mental stress from the photoplethysmogram: a numerical study.” Physiological measurement 39.5 (2016): 054001; (ii) Ahn, Jae Mok.
  • phrases of the form of “based on the PPG signal” refer to the PPG signal and any derivative thereof.
  • Algorithms for filtration of the PPG signal (and/or the images in the case of iPPG), extraction of feature values from fiducial points in the PPG signal, and analysis of the feature values extracted from the PPG signal are well known in the art, and can be found for example in the following references: (i) Allen, John. "Photoplethysmography and its application in clinical physiological measurement.” Physiological measurement 28.3 (2007); (ii) Elgendi, Mohamed.
  • the input comprises images having multiple pixels.
  • the images from which the iPPG signal and/or hemoglobin concentration patterns are extracted may undergo various preprocessing to improve the signal, such as color space transformation, blind source separation using algorithms such as independent component analysis (ICA) or principal component analysis (PC A), and various filtering techniques, such as detrending, bandpass filtering, and/or continuous wavelet transform (CWT).
  • ICA independent component analysis
  • PC A principal component analysis
  • filtering techniques such as detrending, bandpass filtering, and/or continuous wavelet transform (CWT).
  • Various preprocessing techniques known in the art that may assist in extracting iPPG signals from images are discussed in Zaunseder et al. (2016), “Cardiovascular assessment by imaging photoplethysmography - a review”, Biomedical Engineering 63(5), 617-634.
  • machine learning approach and/or “machine learning-based approaches” refer to learning from examples using one or more approaches.
  • machine learning approaches include: decision tree learning, association rule learning, regression models, nearest neighbors classifiers, artificial neural networks, deep learning, inductive logic programming, support vector machines, clustering, Bayesian networks, reinforcement learning, representation learning, similarity and metric learning, sparse dictionary learning, genetic algorithms, rule-based machine learning, and/or learning classifier systems.
  • a “machine learning -based model” is a model trained using one or more machine learning approaches.
  • feature values also known as feature vector, feature data, numerical features, and inputs
  • a computer that utilizes a model to perform the calculation of a value (e.g., an output, “target value”, or label) based on the input.
  • a value e.g., an output, “target value”, or label
  • feature and “feature value” may be used interchangeably when the context of their use is clear.
  • a “feature” typically refers to a certain type of value, and represents a property
  • feature value is the value of the property with a certain instance (i.e., the value of the feature in a certain sample).
  • At least some feature values utilized by a computer of the specific embodiment may be generated based on additional sources of data that were not specifically mentioned in the specific embodiment.
  • additional sources of data include: contextual information, information about the user being, measurements of the environment, and values of physiological signals of the user obtained by other sensors.
  • Sentences in the form of “inward-facing head-mounted camera” refer to a camera configured to be worn on a user’s head and to remain pointed at the region it captures (sometimes referred to as ROI), which is on the user’s face, also when the user’s head makes angular and lateral movements.
  • a head- mounted camera (which may be inward-facing and/or outward-facing) may be physically coupled to a frame worn on the user’s head, may be physically coupled to eyeglasses using a clip-on mechanism (configured to be attached to and detached from the eyeglasses), may be physically coupled to a hat or a helmet, or may be mounted to the user’s head using any other known device that keeps the camera in a fixed position relative to the user’s head.
  • the term “smartglasses” refers to any type of a device that resembles eyeglasses, which includes a frame configured to be worn on a user’s head and electronics to operate one or more sensors.
  • the term “visible-light camera” refers to a non-contact device designed to detect at least some of the visible spectrum, such as a video camera with optical lenses and CMOS or CCD sensor; visible - light camera may be sensitive to near-infrared wavelengths below 1050 nanometer.
  • the term “thermal camera” refers to a non-contact device that measures electromagnetic radiation having wavelengths longer than 2500 nanometer (nm) and does not touch the region it measures.
  • a thermal camera may include one sensing element (pixel), or multiple sensing elements that are also referred to herein as “sensing pixels”, “pixels”, and/or focal-plane array (FPA).
  • a thermal camera may be based on an uncooled thermal sensor, such as a thermopile sensor, a microbolometer sensor (where microbolometer refers to any type of a bolometer sensor and its equivalents), a pyroelectric sensor, or a ferroelectric sensor.
  • a reference to a “camera” herein may relate to various types of devices.
  • a camera may be a visible-light camera.
  • a camera may capture light in the ultra-violet range.
  • a camera may capture near-infrared radiation (e.g., wavelengths between 750 and 2000 nm).
  • a camera may be a thermal camera.
  • the term “temperature sensor” refers to a device that measures temperature and/or temperature change.
  • the temperature sensor may be a contact thermometer (such as a thermistor, a thermocouple), and/or a non-contact thermal cameras (such as a thermopile sensor, a microbolometer sensor, or a cooled infrared sensor).
  • a contact thermometer such as a thermistor, a thermocouple
  • a non-contact thermal cameras such as a thermopile sensor, a microbolometer sensor, or a cooled infrared sensor.
  • Some examples of temperature sensors useful to measure skin temperature include: thermistors, thermocouples, thermoelectic effect, thermopiles, microbolometers, and pyroelectric sensors.
  • Some examples of temperature sensors useful to measure environment temperature include: thermistors, resistance temperature detectors, thermocouples; thermopiles, and semiconductor-based sensors.
  • the term “movement sensor” refers to a sensor comprising one or more of the following components: a 3-axis gyroscope, a 3-axis accelerometer, and a magnetometer.
  • the movement sensor may also include a sensor that measures barometric pressure.
  • the term “acoustic sensor” refers to a device that converts sound waves into an electrical signal.
  • the acoustic sensor may be a microphone, such as a dynamic microphone, a piezoelectric microphone, a fiber-optic microphone, a Micro-Electrical-Mechanical System (MEMS) microphone, and/or other known sensors that measure sound waves.
  • MEMS Micro-Electrical-Mechanical System
  • blood pressure is indicative of one or more of the following: the systolic blood pressure of the user, the diastolic blood pressure of the user, and the mean arterial pressure (MAP) of the user. It is specifically noted that the term “blood pressure” is not limited to the systolic and diastolic blood pressure pair.
  • substance intake or “intake of substances” refer to any type of food, beverage, medications, drugs, smoking/inhaling, and any combination thereof.
  • Some embodiments of systems, methods, and/or computer products for managing access by controlling passage through a doorway are described below.
  • An aspect of these embodiments is utilization of wearable devices, worn by users, in order to determine whether their physiological signals indicates they are healthy, and thus should be allowed through the doorway.
  • Physiological signals may also be used to determine that a person wearing the wearable device, and seeking to pass through the doorway, is the same person determined to be in a healthy state.
  • FIG. 1 is a schematic illustration embodiments of a system configured to grant passage through a doorway based on a user’s health state.
  • the system includes at least a wearable device 840 and a computer 847.
  • the computer 847 utilizes measurements of the user, taken with the wearable device 840, both on that day, and on earlier days, to determine if the user’s health state permits passage through the doorway, and also to determine whether the user wearing the wearable device 840 is the person who wore the wearable device 840 when the earlier measurements were taken.
  • Some embodiments of the system may optionally include additional elements such as a controller 849, which is configured to command an automatic door to open, close, lock and/or unlock, based on signals sent from the computer 847.
  • the wearable device 840 may include various types of sensors that may be used to measure the user wearing the wearable device and/or the environment that is user is in.
  • the wearable device includes a photoplethysmogram (PPG) sensor 841 that measures a signal indicative of a photoplethysmogram (PPG) signal of the user wearing the wearble device 840, and a temperature sensor 842 that measures a temperature of the user.
  • PPG photoplethysmogram
  • the PPG sensor 841 and/or the temperature sensor 842 may be head-mounted sensors, such as sensors coupled to, and/or embedded in, frames of smartglasses, such as the smartglasses illustrated in FIG. 2, which is discussed below.
  • the wearable device 840 may include additional sensors, such as an acoustic sensor 843, a inertial measurement unit (IMU) 844, and/or an environment sensor 845. These sensors may provide signals that can be utilized by the computer 847 to determine the user’s health state, as discussed further below.
  • sensors such as an acoustic sensor 843, a inertial measurement unit (IMU) 844, and/or an environment sensor 845. These sensors may provide signals that can be utilized by the computer 847 to determine the user’s health state, as discussed further below.
  • IMU inertial measurement unit
  • the PPG sensor 841 may be a contact PPG device.
  • Some examples of configurations for the PPG sensor 841 include: a contact PPG device embedded in the nosepiece of smartglasses in order to take measurements indicative of blood flow at and/or near the nose, a contact PPG device embedded inside an earbud in order to take measurements indicative of blood flow in the ear, a contact PPG device embedded in a smart band or smartwatch to take measurements indicative of blood flow in the wrist, or a contact PPG device embedded in a patch that may be attached to a portion of the body in order to take measurements of blood flow at the attached region.
  • the contact PPG device may include one or more light sources configured to illuminate a region on the user’s body with which the contact PPG device comes in contact.
  • the one or more light sources may include light emitting diodes (LEDs) that illuminate the region.
  • the one or more LEDs include at least two LEDs, where each illuminates the region with light at a different wavelength.
  • the at least two LEDs include a first LED that illuminates the region with green light and a second LED that illuminates the region with infrared light.
  • the contact PPG device may also include one or more photodetectors configured to detect extents of reflections from the region.
  • the contact PPG device includes four light sources, which may be monochromatic (such as 625 nm, 740 nm, 850 nm, and 940 nm), and a CMOS or CCD image sensor (without a near-infrared filter, at least until 945 nm).
  • four light sources which may be monochromatic (such as 625 nm, 740 nm, 850 nm, and 940 nm), and a CMOS or CCD image sensor (without a near-infrared filter, at least until 945 nm).
  • the PPG sensor 841 may be a non-contact device.
  • the PPG sensor 841 may be a video camera configured to capture images of a region that includes skin on the user’s head (e.g., images that include a region of the forehead, a cheek, and/or a temple). From these images, PPG signals may be extracted utilizing various techniques known in the art at described herein.
  • the video camera is an inward-facing head-mounted video camera, such as an inward-facing camera coupled to a frame of smartglasses.
  • the temperature sensor 842 may be a contact temperature sensor, such as a sensor embedded in a nose piece of smartglasses, embedded in an earbud, or embedded in a patch attached to a region of the user’s body.
  • the temperature sensor 842 may be a non -contact sensor, such as a thermal camera that takes measurements of a certain region on the user’s face.
  • the thermal camera may be configured to take a measurement of the temperature at a temple of the user.
  • the thermal camera may be configured to take a measurement of the temperature at a periorbital region of the user.
  • the thermal camera may be configured to take a measurement of the temperature at user’s forehead.
  • the temperature of the user measured by the temperature sensor 842 may refer to different types of values.
  • “the temperature of the user” is a temperature of the skin of the user at the area measured by the temperature sensor 842.
  • the temperature of the user refers to a value of the user’s core body temperature, which is estimated based on a measurement of the temperature sensor 842.
  • estimating values based on measurements of the temperature sensor 842 may involve utilization of measurements from additional sensors.
  • core body temperature may be estimated utilizing images of the user’s face captured with a video camera and/or temperatures of the environment (e.g., obtained by the environment sensor 845). Utilizing these multiple sources of data is discussed in more detail in US Patent Application 2020/0397306, “Detecting fever and intoxication from images and temperatures”, which is incorporated herein by reference.
  • the wearable device 840 may include multiple temperature sensors, which may measure temperature at various locations on the user’s face.
  • the multiple temperature sensors may be head-mounted sensors, such as temperature sensors embedded in frames of smartglasses, which take measurements of multiple regions on the user’s head. Calculation of temperature values by aggregating measurements from multiple regions is discussed in more detail in US Patent Application 2021/0007607, “Monitoring blood sugar level with a comfortable head-mounted device”, which is incorporated herein by reference.
  • the wearable device 840 may optionally include one or more acoustic sensors, such as the acoustic sensor 843, which are configured to take audio recordings of the user.
  • the one or more acoustic sensors are mounted to a frame worn on the user’s head, such as a frame of smartglasses, at fixed positions relative to the head of the user.
  • the audio recordings of the user may include recordings of sounds produced by the user, such as sounds of respiration, coughing, speech, and the like. Indications of the user’s respiration and/or extent of coughing may be signals utilized to calculate a health score of a user, as discussed below.
  • the wearable device 840 includes the IMU 844.
  • the IMU 844 may be head-mounted, such as an IMU embedded in frames of smartglasses.
  • the IMU 844 measures a signal indicative of one or more of the following: movements of the user’s body (e.g., due to walking, climbing stairs, etc.), movements of the head of user, an orientation of the head of the user with respect to the earth’s gravity (i.e., an angle between the head’s orientation and the direction in which gravity acts).
  • movements of the user’s body e.g., due to walking, climbing stairs, etc.
  • movements of the head of user e.g., due to walking, climbing stairs, etc.
  • an orientation of the head of the user with respect to the earth’s gravity i.e., an angle between the head’s orientation and the direction in which gravity acts.
  • various patterns of movements of the user’s head may be detected using approaches known in that art to detect activities (e.g., walking or running), as well as whether the
  • the wearable device 840 includes the environment sensor 845.
  • the environment sensor 845 measures the temperature of the environment.
  • a sensor that measures the temperature of the environment include: (i) a non- contact temperature sensor, such as a thermopile or a microbolometer sensor, and (ii) a contact temperature sensor, such as a thermistor or a thermocouple.
  • the environment sensor 845 may be a humidity sensor (hygrometer).
  • references to the wearable device 840 being worn by a user may be interpreted as one or more wearable devices worn by said user.
  • the wearable device 840 refers to more than one wearable device, the aforementioned sensors need not be comprised in a single device.
  • the reference to the wearable device 840 may, in some examples, refer to a first device, e.g., a smartwatch with a contact PPG sensor, and a second device, e.g., a smart shirt with embedded temperature sensors.
  • various sensors are coupled to a single wearable device.
  • FIG. 2 illustrates an example of smartglasses that may be considered an embodiment of the wearable device 840 that is utilized in some embodiments described herein.
  • FIG. 2 illustrates just one possible embodiment of a combination of some of the components described in FIG. 1.
  • the smartglasses include at least a frame 230, which is configured to be worn on a user’s head, and several sensors configured to measure the user and/or the environment.
  • Acoustic sensors 202a and 202b which may be used to take audio recordings of the user, are mounted at fixed positions on the frame 230 (below and above the left lens, respectively).
  • Contact PPG device 212’ is located in the nose piece, and may be utilized to generate a PPG signal of the user, from which the heart rate of the user may be derived, as well as other blood flow -related parameters.
  • Inward-facing cameras 218a and 218b are attached to the frame 230 at locations that are above and below the right lens, respectively.
  • the inward -facing camera 218a is pointed upwards and configured to capture images of a region above the user’s eyes (e.g., a portion of the forehead).
  • the inward-facing camera 218b is pointed downwards and configured to capture images of a region below the user’s eyes (e.g., a portion of a cheek).
  • a non-contact thermal sensor 208’ is coupled to a temple of the smartglasses, which is part of the frame 230, and is configured to measure temperature at a region on the user’s face. Additional thermal sensors may be coupled to the frame 230 and be used to measure temperatures at different regions.
  • Environment temperature sensor 210 which may also be a non-contact thermal sensor, is coupled to the frame 230 such that it is pointed away from the user’s face in order to measure the temperature of the environment.
  • Movement sensor 206 is also coupled to the frame 230 such that it measures the motion of the user’s head.
  • the computer 200’ is coupled to the frame 230 and may perform at least some, and in some embodiments, all, of the operations attributed to some of the computers in this disclosure, such as the computer 847.
  • the computer 847 analyzes measurements taken by the wearable device 840 of the user wearing the wearable device 840, and optionally of the environment the user is in at the time.
  • this analysis may involve calculations with measurements taken at different times: (i) “current measurements”, which are taken with the wearable device 840 during a period that starts a certain time before the analysis is performed (e.g., a few hours before that time) and/or leading up to when the analysis is performed, and (ii) “baseline measurements” taken with the wearable device 840 on one or more earlier days.
  • the current measurements are taken over a duration of at least five minutes.
  • the baseline measurements include more than an hour of measurements, taken over a period of several days.
  • a reference to “the computer 847”, or other computers described in this disclosure, may refer to different components and/or a combination of components.
  • the computer 847 may include a processor located on the wearable device 840.
  • at least some of the calculations attributed to the computer 847, and possibly all of those calculations, may be performed on a remote processor that is not on the wearable device 840, such as a processor on the user’s smartphone and/or a cloud-based server.
  • references to calculations being performed by the “computer 847” can also be interpreted as calculations being performed utilizing one or more computers, with some of these one or more computers being in the wearable device 840. Examples of computers that may be utilized to perform the calculations of one or more computers, which may be collectively referred to as “the computer 847”, are computer 400 or computer 410, illustrated in FIG. 14A and FIG. 14B, respectively.
  • analysis of the current measurements and the baseline measurements, which are taken by the wearable device 840 involves the computer 847 performing the following: calculating a health score based on a difference between the baseline measurements and the current measurements, and calculating an extent of similarity between characteristics of the PPG signal in the current measurements and characteristics of the PPG signal in the baseline measurements. These two values may then be used to determine whether the health of the user of whom the current measurements and baseline measurements were taken, permits passage through the doorway.
  • characteristics of the PPG signal may be any information that is derived from multiple PPG waveforms in the PPG signal of the user (e.g., relationship between fiducial points), a pulse wave template, and/or other forms of templates of PPG signals known in the art.
  • the current measurements of a user are measurements that reflect the present state of the user, such as the state of the user during the hours leading up to an intended time of passage through the doorway and/or at that time.
  • the current measurements include measurements of the user taken with the wearable device 840 on that same day, and possibly up to the intended time of passage through the doorway.
  • the current measurements include measurements taken with the wearable device 840 during a period spanning one hour before the intended time of passage through the doorway and/or the time the health score and the extent of similarity are calculated.
  • the current measurements include measurements taken with the wearable device 840 sometime during a period spanning between 3 hours before the time the health score and the extent of similarity are calculated and the time these values are calculated.
  • the baseline measurements include measurements that reflect a typical state of the user on earlier days (i.e., the user’s baseline state).
  • the baseline measurements include measurements of the user taken with the wearable device 840 on one or more days before the intended time of passage through the doorway.
  • the baseline measurements include measurements taken at least a day before the current measurements were taken.
  • the baseline measurements include measurements that were taken several days, weeks, and even months before the current measurements were taken.
  • comparing the current measurements and the baseline measurements serves two purposes. First, differences between the current measurements and the baseline measurements are used to detect deviation from a baseline state that may be indicative of a change in the health state of the user (this is reflected in the calculated health score). Second, similarities between these sets of measurements, and in particular in characteristics of PPG signals in both sets of measurements, may be used to establish, with a certain degree of certainty, that the baseline measurements and the current measurements are of the same person. This form of biometric identification can help reduce the likelihood of mistakes and/or deceptive behavior that involves measuring a first user and then providing the wearable device 840 to a second user, who poses as the first user, in order to trick the system.
  • the computer 847 transmits an authorization signal 848 that permits the passage of the user through the doorway.
  • the authorization signal 848 indicates that a health state of the user permits passage through the doorway.
  • Health scores of users may have different types of values, in different embodiments. However, generally speaking, a value of a health score of a user is indicative of the extent to which a user is healthy and/or non-contagious. Optionally, a health score may refer to an extent to which a user displays symptoms and/or is considered contagious with respect to a certain disease (e.g., the flu, COVID-19, or some other communicable disease).
  • a certain disease e.g., the flu, COVID-19, or some other communicable disease.
  • a health score may refer to an extent to which a user is considered healthy according to general wellness considerations that involve one or more of the user’s vital signs (e.g., whether the core body temperature is elevated, blood oxygen saturation is in a normal range, etc.)
  • health scores are binary values (e.g., sick/healthy, or contagious/non-contagious).
  • a health score of a user may be a numerical value indicative of an extent to which a user is healthy and/or non-contagious (e.g., values on a scale of 1 to 10, where 1 is very sick and 10 is very healthy).
  • a health score of a user may a value indicative of a probability a user is healthy and/or non-contagious.
  • having a health score that reaches the first threshold may mean that the user is not considered to be in a state that endangers others. For example, if the health score reaches the first threshold, the user may be considered non-contagious. Additionally or alternatively, having a health score that reaches the first threshold may mean that the user is considered healthy. Additional details regarding how the computer 847 may calculate health scores in different embodiments is provided further below.
  • Setting a value of the first threshold may be done in various ways.
  • the threshold is set empirically based on health scores calculated for multiple people. The health status at the time measurements of these people were taken and/or their health status on the following day or two may also be known and monitored.
  • the value of the first threshold is then selected to ensure that health scores of a desired proportion of the people who are known to be healthy and/or non-contagious is above the first threshold. Additionally or alternatively, the value of the first threshold may be selected to ensure that health scores of a desired proportion of the people who are known to be sick and/or contagious is below the first threshold.
  • the extent of similarity between characteristics of the PPG signal in the current measurements and characteristics of the PPG signal in the baseline measurements is indicative, in some embodiments, of a probability that the baseline measurements and the current measurements are measurements of the same person.
  • the extent of similarity is a value that describes a distance of the current measurements from a template derived from the baseline measurements.
  • the extent of similarity is a value calculated utilizing a machine learning-based model provided with feature values generated from the current measurements and the baseline measurements, and is indicative of a probability that the current measurements and the baseline measurements are of the same person. Additional details regarding how the computer 847 may calculate the extent of similarity in different embodiments is provided further below.
  • a probability the current measurements and baseline measurements are of the same person are at least a certain predetermined probability.
  • the predetermined probability may be greater than 50%, greater than 75%, greater than 90%, greater than 95%, or greater than 99%.
  • the second threshold may be arbitrarily set to a predetermined value (e.g., a certain level of similarity).
  • the second threshold may be arbitrarily set according to performance (e.g., values in a confusion matrix). In one example, this may be done by collecting current measurements and baseline measurements of multiple people, and then the extents of similarity are calculated for “matches” (current measurements and baseline measurements of the same person), and “mismatches” (current measurements of one person and baseline measurements of a different person). The value of the second threshold may then selected to ensure that a desired proportion of extents of similarities calculated in cases of matches is above the second threshold. Additionally or alternatively, the value of the second threshold may be selected to ensure that a desired proportion of extents of similarities calculated in cases of mismatches is below the second threshold.
  • the baseline measurements used to calculate the health score of the user may be selected from a larger pool of measurements of the user, in such a way so that user was in a condition (while the selected baseline measurements were taken) that is similar to the condition the user is in when the current measurements are taken. Being in “a similar condition” may mean different things in different embodiments.
  • the computer 847 selects the baseline measurements such that a difference between the temperature in the environment, measured while the baseline measurements were taken with environment sensor 845, and a temperature in the environment, measured while the current measurements were taken, is below a predetermined threshold.
  • the predetermined threshold is below 7°C.
  • the computer 847 calculates, based on measurements of the IMU 844 that are part of the current measurements, a current level of physical activity that belongs to a set comprising: being stationary, and walking. The computer 847 selects the baseline measurements that were taken while the user’s movements were indicative of a similar level of physical activity.
  • Transmitting the authorization signal 848 is intended to enable the user wearing the wearable device 840 to pass through the doorway. This may be done in different ways.
  • transmitting the authorization signal 848 involves sending a message to an access control system that adds an identifier of the user wearing the wearable device 840, and/or an identifier of the wearable device, to a list of users and/or wearable devices that are allowed passage through the doorway.
  • transmitting the authorization signal 848 causes the doorway to change its state in order to enable the user to enter (some examples of such embodiments involve the controller 849, discussed in more detail below).
  • this change in state is temporary and done in response to detecting the presence of the user and/or the wearable device 840 in the vicinity of the doorway.
  • transmission of the authorization signal 848 does not involve providing an indication of the identity of the user and/or does not involve authentication of said identity.
  • transmission of the authorization signal 848 may not involve sending the user’s name, identification number, social security number, credit card number, or any other data that can be used to uniquely identify who the user is.
  • transmission of the authorization signal 848 does not involve providing an indication of the identity of the wearable device 840, such as a MAC address or a SIM card serial number (ICCID).
  • ICCID SIM card serial number
  • transmission of the authorization signal 848 does not have to involve transmitting information that directly contributes to identification of the user and/or of the wearable device 840 (which can be used to identify a user who purchased the device and/or uses it on a regular basis).
  • Transmission of the authorization signal 848 may be done in different ways and/or when different conditions are met, in different embodiments.
  • the authorization signal 848 is transmitted once, which is sufficient to effect changes in the doorway that enable the user wearing the wearable device 840 to pass through the doorway.
  • the authorization signal 848 is transmitted when the wearable device 840 detects its location is in the vicinity of the doorway (e.g., based on GPS location, triangulation from Wi-Fi or cellular transmissions, and other similar detection methods).
  • the authorization signal 848 may be sent in response of receiving a communication, e.g., from the controller 849, indicating a request for the transmission of the authorization signal 848.
  • Transmission of the authorization signal 848 may cease in response to detecting certain conditions, such as detecting that the wearable device 840 is not in the vicinity of the doorway, that the wearable device 840 has passed through the doorway, and/or that the wearable device 840 might have been removed from the user wearing it.
  • Encryption and security are important factors of some of the embodiments described herein. This involves protection from eavesdropping and abuse by external parties; for example, parties intending to steal information about the user wearing the wearable device 840 and/or copy an authorization signal and transmit it on another occasion. Encryption and security are also helpful in protecting from abuse by wearers of the wearable device 840, e.g., in order to falsify the health state and/or identity of the wearer of the wearable device 840. There are many approaches, algorithms, and types of hardware known in the art that may be used to secure the wearable device 840, the computer 847, and the integrity of communications between these components (which include the authorization signal 848 and optionally other communications too). The following are some limited examples of approaches that may be used. Various security measures known in the art, which may be utilized in some embodiments (including additional approaches not mentioned below) are described in references mentioned below.
  • sensors on the wearable device 840 may incorporate a hardware-based layer of security.
  • the data they send to other components of the wearable device 840 and/or the computer 847 involve a method of data masking, such as encryption using a chaotic stream cipher.
  • An example of an implementation of such an approach for sensor-level encryption of temperature measurements is provided in Hedayatipour, et al. "A temperature sensing system with encrypted readout using analog circuits.” 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2019.
  • the computer 847 when transmitting the authorization signal 848, the computer 847 utilizes one or more cryptographic approaches to encrypt the authorization signal 848 and/or authenticate the wearable device 840.
  • the computer 847 may utilize a static token, which may be inaccessible to other hardware component unless the conditions for transmitting the authorization signal 848 are met.
  • synchronous dynamic tokens may be used, e.g., involving a timer to rotate through various combinations produced by a cryptographic algorithm. In this example, both a component receiving the authorization signal 848 and the computer 847 possess synchronized clocks.
  • asynchronous tokens may be generated by the computer 847 and used for the authorization signal 848 without the need for a synchronized clock, e.g., using an implementation of a one-time pad or a cryptographic algorithm.
  • the authorization signal 848 may be transmitted via a challenge and response scheme.
  • public key cryptography can be used to prove possession of a private key without revealing that key.
  • An authentication server may encrypt a challenge (typically a random number, or at least data with some random parts) with a public key; the computer 847 proves it possesses a copy of the matching private key by providing the decrypted challenge.
  • the computer 847 may utilize A Trusted Platform Module (TPM) to implement one or more of the various security measures described herein.
  • TPM may include a unique RSA key burned into it, which is used for asymmetric encryption. Additionally, the TPM may be used to generate, store, and protect other keys used in the encryption and decryption process.
  • the controller 489 is configured to command an automatic door to open and/or unlock, permitting the passage through the doorway, responsive to receiving the authorization signal 848.
  • the automatic door includes a barrier that restricts the passage through the doorway when the automatic door is in a closed and/or locked position.
  • FIG. 1 illustrates two positions for an automatic door, being closed (846A) and being open (846B), for example, following transmission of the authorization signal 848.
  • the controller 849 commands the automatic door to close and/or remain shut, thereby restricting the passage through the doorway, after detecting that the user has passed through the doorway and/or not receiving an additional transmission of the authorization signal 848 within a predetermined time. For example, each transmission of the authorization signal 848 opens the automatic door for a few seconds, and then the controller 849 commands it to shut (unless another authorization signal is transmitted). In some embodiments, the controller 849 may receive a signal indicating that the user has passed through the doorway (e.g., from the wearable device 840 or some other device), which triggers it to command the automatic door to shut and/or remain shut.
  • a signal indicating that the user has passed through the doorway e.g., from the wearable device 840 or some other device
  • the computer 480 may also transmit a second signal responsive to the health score not reaching the first threshold and/or the extent of the similarity not reaching the second threshold.
  • the controller 849 commands the automatic door to close and/or remain shut, thereby restricting the passage through the doorway.
  • FIG. 3 There are various types of automatic doors that may be controlled by embodiments of systems described herein. Some examples of types of automatic doors are illustrated in FIG. 3.
  • the automatic door is an entrance door to a room and/or building, and commanding the automatic door to open unlocks the door and/or moves the door to an open position, enabling the user to enter the interior of the room and/or building.
  • FIG. 3 illustrates two types of entrance doors to building that may controlled using embodiments of system described herein.
  • Sliding door 850A may be opened and/or closed based on commands of the controller 849.
  • Turnstile door 850B may commanded by the controller 849 to turn and/or enable the door to revolve when pushed.
  • the controller 849 may command the turnstile door 850B to stop turning and/or resist effort to force it to revolve (e.g., the door may move to a locked position that can resist force applied in an effort to make the turnstile door 850B revolve).
  • the automatic door belongs to a vehicle 850C, and commanding the automatic door to open unlocks the door and/or moves the door to an open position, enabling the user to enter the cabin of the vehicle.
  • the automatic door is a gate 850D that includes a turnstile, and commanding the automatic door to open enables the turnstile to revolve and/or revolving the turnstile, enabling the user to pass through the gate.
  • the health score of the user may be calculated in different ways by the computer 847. In some embodiments, this calculation involves utilizing differences between the baseline measurements and the current measurements of the user to determine whether there is a deviation from an expected baseline of the user and/or whether the deviation is indicative that the user may be ill and/or contagious and thus, in order to curb the spread of disease, e.g., COVID-19 or the flu, the user should not be permitted to pass through the doorway and put other people at risk.
  • this calculation involves utilizing differences between the baseline measurements and the current measurements of the user to determine whether there is a deviation from an expected baseline of the user and/or whether the deviation is indicative that the user may be ill and/or contagious and thus, in order to curb the spread of disease, e.g., COVID-19 or the flu, the user should not be permitted to pass through the doorway and put other people at risk.
  • calculation of the health score by the computer 847 involves calculating, based on the baseline measurements, an expected value of a physiological signal of the user.
  • the value of the physiological signal may be skin temperature, estimated core body temperature, blood oxygen saturation, heart rate, heart rate variability, extent of coughing, or blood pressure.
  • calculation of the health score by the computer 847 may involve calculating, based on the current measurements, a current value of the physiological signal (for which the expected value is calculated). Given these two values, the computer 847 can then set the value of the health score based on a difference between the expected value and the current value of the physiological signal.
  • the physiological signal is body temperature
  • calculating of the health score utilizes a function that returns a value that is below the first threshold when a current body temperature is greater than an expected body temperature by at least a certain margin.
  • the certain margin is at least 0.4°C.
  • the health score that is calculated in this embodiment is such that it falls below the first threshold.
  • the physiological signal is blood oxygen saturation (Sp0 2 ), and calculating of the health score utilizes a function that returns a value that is below the first threshold when a current Sp0 2 is lower than an expected Sp0 2 by at least a certain margin.
  • the certain margin is at least 0.03.
  • the health score that is calculated in this embodiment is such that it falls below the first threshold.
  • the health score may depend on a qualitative change in values of Sp0 2 - For example, if it is determined that a user’s baseline state is to have an Sp02 level that is always above a certain threshold (e.g., 0.92) and based on the current measurements, the Sp0 2 falls below the certain threshold, that can lead to assignment of a health score that is below the first threshold.
  • a certain threshold e.g. 0.2
  • calculation of the health score may depend on differences between expected values and current values of more than one physiological signal.
  • the calculation of the health score may be based differences between expected and current values of multiple physiological signals.
  • the health score may be a value that depends on a first difference between expected and current values of the user’s temperature and a second difference between expected and current values of the user’s blood oxygen saturation levels.
  • Calculation of the health score may be done in different ways, in different embodiments.
  • current values of one or more physiological signals and baseline values of the one or more of the physiological signals, and/or difference between these current and baseline values are provided to a predetermined function that calculates the health score.
  • the predetermined function may be represented as a lookup table that provides values of health scores determined manually, e.g., by medical experts based on their experience.
  • parameters of the predetermined function may be determined by regression that uses outcome variables that are health scores that were manually determined based on medical records of users.
  • Calculating the baseline values and/or the expected values of physiological signals may involve utilization of machine learning-based approaches.
  • calculating a current value of the physiological signal may involve generating feature values based on the current measurements, and utilizing a model to calculate the current value of the physiological signal based on the feature values.
  • calculating a baseline value of the physiological signal may involve generating additional feature values based on the baseline measurements, and utilizing the model to calculate the baseline value of the physiological signal based on the additional feature values.
  • the model is generated from training data that includes: previous measurements of the user taken with the wearable device 840, and values of the physiological signal (considered “labels” or “outcome values”) obtained utilizing a sensor that is not part of the wearable device 840.
  • the model may be generated from training data that includes: previous measurements of other users taken with units of the same type as the wearable device 840, and values of the physiological signal (considered “labels” or “outcome values”) obtained utilizing a sensor that is not part of the units of the same type as the wearable device 840.
  • At least some feature values utilized to calculate values of one or more physiological signals are derived from a PPG signal measured utilizing the PPG sensor 841.
  • various approaches may be employed, which are known in the art, in order to identify landmarks in a cardiac waveform (e.g., systolic peaks, diastolic peaks) may be employed, and/or extract various types of known values that may be derived from the cardiac waveform, as described in the following examples.
  • At least some of the feature values generated based on the PPG signal may be indicative of waveform properties that include: systolic -upstroke time, diastolic time, and the time delay between the systolic and diastolic peaks, as described in Samria, Rohan, et al. "Noninvasive cuffless estimation of blood pressure using Photoplethysmography without electrocardiograph measurement.” 2014 IEEE REGION 10 SYMPOSIUM. IEEE, 2014.
  • At least some of the feature values generated based on the PPG signal may be derived from another analysis approach of PPG waveforms, as described in US Patent Application US20180206733, entitled “Device, method and system for monitoring and management of changes in hemodynamic parameters”.
  • This approach assumes the cardiac waveform has the following structure: a minimum/starting point (A), which increases to a systolic peak (B), which decreases to a dicrotic notch (C), which increases to a dicrotic wave (D), which decreases to the starting point of the next pulse wave (E).
  • At least some feature values utilized to calculate the values of one or more physiological signals are generated from measurements of the temperature of the user, taken with the temperature sensor 842. Additionally or alternatively, one or more of the feature values may be generated from measurements of the temperature of the environment in which the user was in at the time, as measured for example, by the environment sensor 845. In one embodiment, the feature values include a temperature value itself (e.g., a value measured by the temperature sensor 842 and/or a value measured by the environment sensor 845). Additionally or alternatively, the feature values may include a difference between the temperature and a previously taken temperature (e.g., a temperature taken 10 minutes before or one hour before).
  • the feature values may include a difference between the temperature and a baseline temperature, which is determined based on the baseline measurement.
  • the feature values include a value indicative of the difference between a temperature of the user, and the average temperature of the user, as measured by the temperature sensor 842 on multiple previous days.
  • the feature values include a value indicative of the difference between temperature of the environment, and the average temperature measured in the environment on multiple previous days.
  • one or more of the feature values may be generated by the computer 847 from a signal indicative of movements of the user.
  • these one or more feature values are indicative of extents of one or more of the following movements: movements of the user’s body (e.g., due to walking, climbing stairs, etc.), movements of the head of user, an orientation of the head of the user with respect to the earth’s gravity (i.e., an angle between the head’s orientation and the direction in which gravity acts).
  • the computer 847 may generate at least some feature values utilized to calculate the values of one or more physiological signals, based on audio recordings of the user.
  • these generated feature values may be “raw” or minimally processed values, such as various acoustic features derived from the audio recordings, as described in are provided in US Patent No. 10,791,938, titled “Smartglasses for detecting congestive heart failure”, which is incorporated herein by reference.
  • the feature values may include higher level, respiration parameters calculated from the audio recordings such as: breathing rate, respiration volume, an indication whether the user is breathing mainly through the mouth or through the nose, exhale (inhale) duration, post-exhale (post-inhale) breathing pause, a dominant nostril, a shape of the exhale stream, smoothness of the exhale stream, and/or temperature of the exhale stream.
  • respiration parameters calculated from the audio recordings such as: breathing rate, respiration volume, an indication whether the user is breathing mainly through the mouth or through the nose, exhale (inhale) duration, post-exhale (post-inhale) breathing pause, a dominant nostril, a shape of the exhale stream, smoothness of the exhale stream, and/or temperature of the exhale stream.
  • feature values generated by the computer 847 in order to calculate values of one or more physiological signals include: intensities of fiducial points (systolic peaks and systolic notches) identified in PPG signals extracted from measurements taken by the PPG sensor 841. Additionally the feature values generated by the computer 847 in order to calculate values of one or more physiological signals include: temperatures of the user measured by the temperature sensor 842 and temperatures of the environment measured by the environment sensor 845. In another non-limiting example, feature values generated by the computer 847 in order to calculate values of one or more physiological signals include values obtained by binning according to filterbank energy coefficients, using MFCC transform on results of FFT of audio recordings recorded by the acoustic sensor 843.
  • Calculation of the health score by the computer 847 may involve, in some embodiments, utilization of various machine learning methods.
  • the computer 847 generates feature values based on data comprising the current measurements and the baseline measurements, which are taken by the wearable device 840, as described above.
  • the computer 847 can then utilize a model (also referred herein as the “health score model”) to calculate, based on the feature values, the health score.
  • the health score model may be generated based on data of multiple users, which is collected under different conditions.
  • the health score model is generated based on training data comprising a first set of training measurements of a plurality of users taken with wearable devices such as the wearable device 840 while the plurality of users were healthy and a second set of training measurements of the plurality of users, taken with the wearable devices, while the plurality of users were not healthy.
  • the data collected from the multiple users, which is used to generate the health score model may include measurements taken at different times, while the multiple users were in various conditions of health.
  • the training data included certain first and second measurements taken with a wearble device like the wearable device 840, while the certain user had certain first and second known extents of health and/or risks of being contagious, respectively.
  • the training data reflects measurements in which there is a known change in the state of the health, for the multiple users.
  • data of the multiple users is used to create samples, where each sample includes feature values generated based on measurements of a certain user and a label which is indicative of the health score that is to be assigned to the user at the time.
  • labels may be set by a physician who checked the certain user, self-reported by the certain user, and/or derived from medical records of the certain user.
  • the samples are generated based on measurements collected in diverse conditions (on different times of day, different locations, different environmental conditions, etc.)
  • the health score model includes parameters of at least one of the following types of models: a regression model, a neural network, a nearest neighbor model, a support vector machine, a support vector machine for regression, a naive Bayes model, a Bayes network, and a decision tree.
  • the computer 847 may generate various types of features based on the data it receives from the wearable device 840, such as the current measurements and baseline measurements. Additionally, some of the feature values may be generated based on the additional sources of data, such as additional sensors on the wearable device 840 or sensors that are not on the wearable device 840.
  • feature values utilized to calculate the health score include one or more of the following values: a value of a physiological signal of the user calculated based on the current measurements, a value of the physiological signal of the user calculated based on the baseline measurements, and a value indicative of a difference between the value of the physiological signal of the user calculated based on the current measurements and the value of the physiological signal of the user calculated based on the baseline measurements.
  • the physiological signal may be a value from among: skin temperature, estimated core body temperature, blood oxygen saturation, heart rate, heart rate variability, respiration rate, extent of coughing, or blood pressure.
  • the computer 847 may utilize machine learning-based approaches, as described above, to calculate the values of the physiological signal from the current and/or baseline measurements.
  • at least some of the feature values utilized to calculate the health score may maybe one or more of the various types of features values described herein (further above) as being utilized to calculate values of physiological signals from measurements taken by the wearable device 840.
  • feature values generated by the computer 847 based on the current measurements and the baseline measurements in order to calculate the health score of the user include: a baseline temperature of the user, a current temperature of the user, a baseline blood oxygen saturation level, and a current blood oxygen saturation level.
  • these values may be calculated using machine -learning based approaches, as already described further above.
  • feature values generated by the computer 847 based on the current measurements and the baseline measurements in order to calculate the health score of the user include: a baseline extent of coughing and a current extent of coughing.
  • these values may be calculated based on recordings of the user with the acoustic sensor 843 and/or measurements of movements of the user, as measured with the IMU 844.
  • feature values generated by the computer 847 in order to calculate the health score of the user include temperatures in the environment at different times, as measured with the environment sensor 845.
  • the computer 847 may employ one or more of the techniques described below in order to calculate the extent of the similarity between the characteristics of the PPG signal in the current measurements and the characteristics of the PPG signal in the baseline measurements.
  • Some embodiments described herein do not involve utilization of information that identifies the user being authenticated, and the process of comparing their PPG signals to previous measurements of PPG signals may not be referred to with the specific term “authentication”. Nonetheless, various teachings in the art for authenticating users based on PPG signals can be used in embodiments described herein by a simple adaptation. For example, instead of comparing a PPG signal in the current measurements to PPG signals and/or templates stored in a database, the PPG signal in the current measurements can be compared to a previously measured PPG signal from the baseline measurements (which may be stored locally, e.g., on the wearable device 840 and/or in a user’s own account). This process may not necessarily involve disclosure of the identity of the user, but nonetheless can utilize the same computational techniques known in the art for authenticating users based on PPG signals.
  • the computer 847 may utilize one or more procedures of that are part of an implementation of the teachings provided in Yadav, et al., "Evaluation of PPG biometrics for authentication in different states.” 2018 International Conference on Biometrics (ICB). IEEE, 2018, which is incorporated herein by reference.
  • Yadav et al. describe computational procedures in which PPG signals can be used for user authentication by employing a combination of Continuous Wavelet Transform (CWT) and Direct Linear Discriminant Analysis (DLDA), which is demonstrated to have robustness under different conditions involving different emotions (e.g., stress), physical exercise and time-lapse.
  • CWT Continuous Wavelet Transform
  • DLDA Direct Linear Discriminant Analysis
  • the computer 847 may utilize one or more of the pre-processing techniques described therein (filtering, peak detection, false peak removal, and segmentation).
  • the computer 847 may generate a baseline template from the PPG signal in the baseline measurements and a current template from the PPG signal in the current measurements utilizing the template generation approach described therein (CWT-based feature extraction and LDA-based dimensionality reduction).
  • calculating the extent of similarity between the characteristics of the PPG signal in the baseline measurements and the characteristics of the PPG signal in the current measurements may then be done by calculating the Pearson distance between vectors generated from the current and baseline templates, as described therein.
  • the computer 847 may utilize one or more procedures of that are part of an implementation of the teachings provided in Sancho, et al., "Biometric authentication using the PPG: A long-term feasibility study.” Sensors 18.5 (2018): 1525, which is incorporated herein by reference. Sancho et al. perform a comparative study of various computational approaches that may be used for PPG-based biometric authentication.
  • the computer 847 may utilize one or more of the pre processing techniques described therein (filtering, PPG cycle detection, cycle normalization and alignment).
  • the computer 847 may generate a baseline template from the PPG signal in the baseline measurements and a current template from the PPG signal in the current measurements utilizing one of the template generation approaches described therein that are based on various feature extraction procedures (Cycles Average, KLT Average, Multi-Cycles, KLT Multi-Cycles).
  • calculating the extent of similarity between the characteristics of the PPG signal in the baseline measurements and the characteristics of the PPG signal in the current measurements may then be done utilizing one or more of the matching techniques described therein (e.g., Manhattan distance or Euclidian distance between the templates).
  • user authentication based on the current and baseline measurements may done using additional signals measured by sensors on the wearable device 840.
  • voice analysis of recordings taken by the acoustic sensor 843 may be analyzed to determine that similar acoustic spectral properties appear in both sets of measurements.
  • gait characteristics of movements measured by the IMU 844 may be compared to determine whether the person wearing the wearable device 840 while the baseline measurements and the current measurements were measured are similar.
  • the authorization signal 848 may be desirable to ensure that following collection of the current measurements and/or transmission of the authorization signal 848, the person wearing the wearable device 840 does not remove it (e.g., in order to let someone else wear it an gain passage through the doorway). This is especially important in embodiments in which the authorization signal 848 does not include information that identifies the person wearing the wearable device 848. In these embodiments, the authorization signal 848 in essence attests that the person wearing the device is healthy and thus should be allowed through the doorway, thus it is important that that assumption still be true during passage through the doorway, otherwise the integrity of the doorway, and its ability to curb the spread of disease may be compromised.
  • the computer 847 determines, based on measurements taken with the wearable device 840, whether the wearable device was removed from the user’s body while the current measurements were taken or after the current measurements were taken, and responsive to making a determination that he wearable device 840 has been removed, the computer 847 refrains from transmitting the authorization signal 848 and/or transmits an additional signal that makes other components (e.g., the controller 489) ignore the authorization signal 848, if it has already been sent.
  • the computer 847 identifies when the wearable device 840 has been removed from the user wearing it based on detecting an interference in the amplitude of the PPG signal and/or phase shift of detected reflected light measured by the PPG sensor 841 that exceeds a certain threshold.
  • Large interferences in measured PPG signals often occur when a PPG sensor’s contact with the body is weakened or broken (such as when the wearable device 840 is removed). These interferences occur because ambient light and interferences of ambient light are much stronger than the signal detected when the PPG sensor is attached to the body (for contact PPG sensors).
  • Video camera-based PPG sensors (e.g., used for iPPG) will also experience dramatic signal changes when the device is removed because, for a certain period, the images captured by video camera will have completely different color schemes. Thus, virtually any removal of the PPG sensor 841 from the body causes a large interference in the measured PPG signal which is typically not observed when the device housing the PPG sensor is firmly in place.
  • the computer 847 identifies when the wearable device 840 is removed from the user wearing it based on detecting a rapid change in temperatures measured by the temperature sensor 842.
  • Physiological body temperature e.g., core body temperature and skin temperature
  • the temperature sensor 842 is likely to measure the environment and/or other regions of the body, at least for a short period (e.g., until the wearable device 840 is worn again by a person). Nonetheless, such a removal typically generates a spike in temperature that exceeds a predetermined threshold characteristic of temperature changes observed when the wearable device 840 is firmly in place.
  • the computer 847 needs to re-establish that the same person who previously wore the wearable device 840 is wearing it again.
  • the computer 847 performs the following steps responsive to making the determination that the wearable device 840 has been removed.
  • the computer 847 receives additional measurements of the user, taken by the wearable device 840 at most three hours after the current measurements were taken.
  • the computer 847 calculates an additional similarity between characteristics of the PPG signal in the current measurements and characteristics of the PPG signal in the additional measurements. If the additional similarity reaches the second threshold (and the previously calculated health score reaches the first threshold), the computer 847 transmits the authorization signal 848.
  • the additional similarity reaching the second threshold is indicative of a probability that the current measurements and the additional measurements are of the same person is above a predetermined threshold. It is to be noted that such a reauthorization may be done, in some embodiments, in a short period and not require extensive collection of additional measurements. In one example, the additional measurements are collected for less than one minute. In another example, the additional measurements are collected for less than 15 seconds.
  • the computer 847 may report to the user the calculated health score. Since this is sensitive information, it may be prudent to determine that the person receiving this information is indeed the user. To this ends, the computer 847 may receive additional measurements of the user, taken with the wearable device 840, and then calculate an additional extent of similarity between characteristics of the PPG signal in the additional measurements and characteristics of the PPG signal in the baseline measurements. The computer 847 also calculates an additional health score based on a difference between the baseline measurements and the additional measurements. If the extent of similarity reaches the second threshold, the computer 847 may report the additional health score to the user and/or provide the user with an indication of whether the health state of the user permits passage through the doorway.
  • a system configured to grant passage through a doorway based on health state, comprising: a wearable device comprising: a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user, and a second sensor configured to measure a temperature of the user; and a computer configured to: receive current measurements of the user, taken with the wearable device; receive baseline measurements of the user, taken with the wearable device on one or more earlier days; calculate a health score based on a difference between the baseline measurements and the current measurements; calculate an extent of similarity between characteristics of the PPG signal in the current measurements and characteristics of the PPG signal in the baseline measurements; and transmit an authorization signal responsive to the health score reaching a first threshold and the extent of the similarity reaching a second threshold; whereby transmission of the authorization signal
  • PPG signal photoplethysmogram signal
  • the controller is further configured to command the automatic door to close and/or remain shut, thereby restricting the passage through the doorway, responsive to detecting that the user has passed through the doorway and/or not receiving an additional transmission of the authorization signal within a predetermined time. 4.
  • the system of claim 2 wherein the automatic door belongs to a vehicle, and commanding the automatic door to open unlocks the door and/or moves the door to an open position, enabling the user to enter the cabin of the vehicle. 5.
  • the system of claim 2, wherein the automatic door is an entrance door to a room and/or building, and commanding the automatic door to open unlocks the door and/or moves the door to an open position, enabling the user to enter the interior of the room and/or building. 6.
  • the automatic door is a gate comprising a turnstile or a revolving door, and commanding the automatic door to open enables the turnstile or the revolving door to revolve and/or revolving the turnstile or the revolving door, enabling the user to pass through the gate.
  • the computer is further configured to transmit a second signal responsive to the health score not reaching the first threshold and/or the extent of the similarity not reaching the second threshold.
  • a controller configured to command an automatic door to close and/or remain shut, thereby restricting the passage through the doorway, responsive to receiving the second signal.
  • the authorization signal does not include information identifying the user. 10.
  • calculation of the health score by the computer comprises: calculating, based on the baseline measurements, an expected value of a physiological signal of the user; calculating, based on the current measurements, a current value of the physiological signal; and calculating the health score based on a difference between the expected value and the current value.
  • the physiological signal is body temperature
  • the calculating of the health score utilizes a function that returns a value that is below the first threshold when a current body temperature is greater than an expected body temperature by at least a certain margin; and wherein the certain margin is at least 0.4°C.
  • calculating the current value of the physiological signal comprises: generating feature values based on the current measurements, and utilizing a model to calculate, based on the feature values, the current value of the physiological signal; and wherein the model was generated from training data comprising: previous measurements of the user taken with the wearable device, and values of the physiological signal obtained utilizing a sensor that is not part of the wearable device. 14.
  • the computer is further configured to: determine, based on the measurements taken with the wearable device, whether the wearable device was removed from the user’s body while the current measurements were taken or after the current measurements were taken, and responsive to making a determination that he wearable device has been removed, to refrain from transmitting the authorization signal.
  • the computer is further configured to perform the following steps responsive to making the determination that the wearable device was removed: receive additional measurements of the user, taken at most three hours after the current measurements were taken; calculate an additional similarity between characteristics of the PPG signal in the current measurements and characteristics of the PPG signal in the additional measurements; and transmit the authorization signal responsive to the health score reaching the first threshold and the additional similarity reaching the second threshold; whereby the additional similarity reaching the second threshold is indicative of a probability that the current measurements and the additional measurements are of the same person is above a predetermined threshold. 17.
  • the system of claim 1, wherein the computer is further configured to: receive additional measurements of the user; calculate an additional extent of similarity between characteristics of the PPG signal in the additional measurements and characteristics of the PPG signal in the baseline measurements; calculate an additional health score based on a difference between the baseline measurements and the additional measurements; and responsive to the extent of similarity reaching the second threshold, reporting the additional health score to the user and/or providing the user with an indication of whether the health state of the user permits passage through the doorway. 18.
  • the computer is further configured to: generate feature values based on data comprising the current measurements and the baseline measurements, and utilize a model to calculate, based on the feature values, the health score; and wherein the model was generated based on training data comprising a first set of training measurements of a plurality of users taken while the plurality of users were healthy and a second set of training measurements of the plurality of users taken while the plurality of users were not healthy. 19.
  • the system of claim 18, further comprising a temperature sensor configured to measure temperature of the environment (T env ); wherein the computer is further configured to generate one or more of the feature values based on first and second values of T env measured while the baseline measurements and the current measurements were taken, respectively, and to utilize the one or more of the feature values to calculate the health score; whereby the one or more of the feature values are indicative of a change to T env between when the baseline measurements were taken and when the current measurements were taken.
  • the first sensor is a video camera configured to capture images of a skin region on the user’s head
  • calculating the extent of similarity between the characteristics of the PPG signal in the current measurements and the characteristics of the PPG signal in the baseline measurements comprises calculating an extent of similarity between imaging photoplethysmography signals recognizable in images belonging to the current measurements and imaging photoplethysmography signals recognizable in images belonging to the baseline measurements.
  • Wearble-based health state verification which can be provided by systems such as embodiments illustrated in FIG. 1, can pave the way to novel applications that involve incorporating measures intended to curb the spread of disease into well-established practices.
  • One such scenario involves making reservations that reserve a place for a user in a space that is shared with other users (e.g., a reservation at a restaurant, reserving a seat in public transportation, etc.). Since the space is shared by others, it can be very beneficial to make sure that all the people in the shared space are healthy and/or non-contagious in order to curb the spread of disease.
  • the following embodiments demonstrate how wearable devices can be used to provide health-state verifications in order to make reservations in a safer more efficient way.
  • FIG. 5 illustrates steps that may be part of embodiments of a method for managing reservations with wearable -based health state verifications.
  • the method may be implemented using embodiments of systems illustrated in FIG. 4, which is discussed further below.
  • the steps described below may be performed by running a computer program having instructions for implementing the method.
  • the instructions may be stored on a computer-readable medium, which may optionally be a non-transitory computer-readable medium.
  • the instructions In response to execution by a system including a processor and memory, the instructions cause the system to perform steps from among the steps illustrated in FIG. 5 and/or additional steps mentioned below.
  • the steps of the method may be divided into certain steps that are performed while making a reservation, and additional steps that are performed after the reservation is made and/or upon arrival of a user to the venue for which the reservation was made.
  • Embodiments of the method illustrated in FIG. 5 include several steps involved in making a reservation:
  • Step 851A receiving (e.g., by a computer 854, which is discussed below), a request to make a reservation that involves occupying a place in a space shared with other people.
  • the request is made by the wearer of a wearble device that is used to take measurements of a user (e.g., user 850, illustrated in FIG. 4).
  • Step 851B receiving a first indication generated based on first measurements taken during a first period by the wearable device.
  • the first measurements include values of physiological signals of the wearer of the wearable device during the first period, and the first indication indicates said wearer is healthy.
  • the first indication does not include information identifying the wearer of the wearable device.
  • the first measurements are taken over a duration of at least five minutes.
  • the first measurements are taken at least an hour before a time for which the reservation is made.
  • the first measurements are taken while the user 850 is not in the vicinity of the space that is to be shared with other people.
  • the method includes an optional step of providing an interface through which the request to make the reservation is entered in response to receiving the first indication.
  • the method includes a step of providing an identifier of the reservation, which reserves the place at a certain time for the wearer of the wearable device during the first period.
  • neither the reservation nor the identifier of the reservation include information that identifies the person for whom the reservation is made (i.e., the person wearing the wearable device).
  • the identifier may include a certain code that is not easy to guess or forge, and thus only the maker of the reservation is like to be able to produce the code if requested.
  • the first measurements include a signal indicative of a PPG signal of the wearer of the wearable device and a temperature of the wearer of the wearable device.
  • the wearable device used to provide the first measurements received in Step 85 IB is the wearable device 840 that includes PPG sensor 841 and temperature sensor 842, which provide the aforementioned PPG signal and temperature of the wearer of the wearable device.
  • the first indication is generated by a certain computer, such as the computer 847, by calculating a value indicative of the health state of the wearer of the wearble device that is based on the first measurements.
  • the certain computer may utilize one or more of the approaches described above, with respect to the calculation of the health score of a user by the computer 847.
  • the value indicative of the health state of the wearer of the wearable device is calculated by a function that evaluates the first measurements and compares them to certain thresholds. For example, if the temperature is below 37.5°C and the blood oxygen saturation is above 0.92, that person is considered healthy.
  • the certain computer may utilize one or more the machine learning approaches described with respect to calculation of the health score by the computer 847, such as generating feature values based on the first measurements and utilizing a model to calculate, based on the feature values, a value that indicates whether the wearer of the wearable device is healthy and/or non-contagious (which is used to decide whether to send the first indication).
  • the first indication is the authorization signal 848 and/or the first indication is sent based on the same criteria that would lead to sending the authorization signal 848, by the computer 847.
  • the first indication is sent by the computer 847 following calculation of a health score for the wearer of the wearable device, which reaches the first threshold and calculation of similarity of PPG signals that reaches the second threshold.
  • the first measurements may be considered the “current measurements” mentioned with respect to embodiments illustrated in FIG. 1.
  • the first measurements are compared to baseline measurements, taken at earlier times by the wearable device, as described above in the discussion regarding embodiments illustrated in FIG. 1.
  • the reservation may involve reserving a vehicle, whose cabin space is shared with a driver and/or other vehicles.
  • the certain time of the reservation corresponds to an expected arrival time of the vehicle.
  • the reservation involves reserving a place at the certain time in a building housing an eating establishment and/or entertainment complex, which may be shared by multiple patrons.
  • the reservation is indicative of a certain seat reserved for the wearer of the wearable device.
  • the reservation is for a seat in one or more of the following: a public transport vehicle, a passenger train car, an aircraft, and a ferry.
  • the reservation is indicative of a certain seat reserved for the wearer of the wearable device.
  • Embodiments of the method illustrated in FIG. 5 include additional steps that may take place some time after the reservation is made:
  • Step 582A receiving a second indication generated based on second measurements taken by the wearable device during a second period that is after the first period.
  • the second measurements include values of physiological signals of the wearer of the wearable device during the second period.
  • the second indication indicates: (i) the wearer of the wearable device during the second period is the same person who wore the wearable device during the first period, and (ii) that same person is still healthy.
  • the second indication does not include information the identifies the wearer of the wearable device during the first and/or second periods.
  • Step 852B approving access to the space to the wearer of the wearable device.
  • the wearable device may be sent an access code enabling entrance to the space.
  • the wearable device may transmit information identifying the wearer of the wearable device, which may be utilized to grant the wearer to access to the space. In this example, identifying information of the wearer of the wearable device is only provided if the wearer is healthy and about to make use of the reservation. No identifying information is provided if the wearer of the wearable device does not want to keep the reservation, or if it turns out that the wearer is not healthy.
  • the second period takes place near the time of the reservation.
  • the second measurements can reflect the health status of the wearer of the wearable device at the certain time for which the reservation is made.
  • the second period ends less than three hours before the certain time (to which the reservation corresponds).
  • the second period ends less than five minutes before the certain time.
  • the second period overlaps with an arrival time of the wearer of the wearable device at a venue of the reservations (i.e., in vicinity of the shared space that is to be shared with other people).
  • the second indication is similar in its nature to the first indication, and thus, can involve using similar computational approaches used to generate the first indication that is received in Step 85 IB. For example, determining that the wearer of the wearable device is still healthy can be done by calculating a second value indicative of the health state of the wearer of the wearble device that is based on the second measurements. In the case that the computational approach involves calculation of a health score based on differences between current measurements and baseline measurements, the second measurements may be used as the “current measurements” for the purpose of calculation of the health score.
  • the second indication also indicates that the wearer of the wearable device during the second period is the same person who wore the wearable device during the first period.
  • this fact is determined by calculating an extent of similarity between characteristics of the PPG signal in the second measurements and characteristics of the PPG signal in the first measurements.
  • this extent of similarity is compared with the second threshold, and if it reaches it, a determination is made that the first measurements and second measurements are of the same person.
  • Embodiments of the method illustrated in FIG. 5 may optionally include additional steps that may take place upon arrival to a venue of the reservation (i.e., arrival in the vicinity of the space that is to be shared with others). Optionally, these steps involve operating an automatic door the facilitates access to the space.
  • the method optionally includes step 853A, which involves commanding an automatic door that facilitates passage into the space to open and/or remain open, responsive to receiving an indication that the wearable device is in a vicinity of the automatic door and that the wearer of the wearable device at that time is the same person as the wearer of the wearable device during the first period.
  • the indication is generated by receiving transmissions from the wearable device that can be detected only when the wearable device is near (e.g., up to 10 meters) from the automatic door. Additionally or alternatively, multiple receivers near the automatic door may be utilized to triangulate transmission of the wearable device and determine its location.
  • determining that the wearer of the wearable device at that time is the same person as the wearer of the wearable device during the first period may done by calculating an extent of similarity of characteristics of PPG signal in measurements taken when the wearer is near the automatic door with characteristics of PPG signals in the first measurements, and observing that the extent of similarity reaches the second threshold.
  • the method optionally includes step 853B, which involves commanding an automatic door that facilitates passage into the space to close and/or remain shut, thus restricting passage into the space, responsive to receiving an indication indicating that the wearable device is in a vicinity of the automatic door and that the wearer of the wearable device at that time is not the same person as the wearer of the wearable device during the first period.
  • determining that the wearer of the wearable device at that time is not the same person as the wearer of the wearable device during the first period may done by calculating an extent of similarity of characteristics of PPG signals in measurements taken when the wearer is near the automatic door with characteristics of PPG signals in the first measurements, and observing that the extent of similarity does not reach the second threshold.
  • the method may optionally include Step 85 ID that involves providing a description of a protocol for behavior that is to be adhered to (by the wearer of the wearable device and/or the wearable device itself) in order to preserve the reservation.
  • the description describes at least one of the following: restrictions involving locations in which to remain, locations to avoid, instructions pertaining to removal of the wearable device (e.g., prohibiting the removal of the wearable device), and instructions pertaining to extent of measurements that need to be provided with the wearable device (e.g., frequency and/or duration of measurements that should be taken using the wearable device).
  • the method may include a step that involves canceling the reservation and/or revoking an approval of access to the space given to the wearer of the wearable device during the first period, responsive to receiving an indication indicating that the wearer of the wearable device did not adhere to the protocol. For example, if it is detected from transmissions of the wearable device that the wearer went into a forbidden area and/or that at least a certain extent of measurements were not taken, then the reservation may be canceled.
  • the integrity of managing reservations by verifying health states relies on the fact that reservations should be kept for users who are healthy and for whom this state is verifiable. If a user is not healthy and/or if this fact cannot be verified, the user’s reservation should be canceled.
  • the method me optionally include Step 852C, which involves canceling the reservation and/or revoking an approval of access to the space given to the wearer of the wearable device during the first period, responsive to receiving an indication that said wearer is no longer healthy.
  • this indication may be sent automatically by the computer 847 as part of a protocol according to which the wearable device and/or the computer 847 are to adhere.
  • the integrity of managing reservations by verifying health states relies on the fact that reservations should only be honored for users who made them. For example, it is undesirable for it to be possible for one person, who is healthy, to make a reservation and then give the wearable device used to make the reservation to another person, whose health state has not been verified, in order for that person to gain access to shared space.
  • the method optionally includes Step 852D, which involves canceling the reservation and/or revoking an approval of access to the space given to the wearer of the wearable device during the first period responsive to receiving an indication indicating the wearable device has been removed from said wearer.
  • this indication may be sent automatically by the computer 847.
  • FIG. 4 illustrates components of an embodiment of a system configured to manage access using reservations and wearable -based health state verifications.
  • the system include the wearable device 840, which includes at least: a first sensor (the PPG sensor 841) that measures a signal indicative of a photoplethysmogram signal (PPG signal) of a wearer of the wearable device 840, and a second sensor (temperature sensor 842) that measures a temperature of said wearer.
  • the system also includes a computer 854, and optionally, an automatic door 855.
  • the computer 854 manages the process of making and managing reservations, and in this process communicates with the wearable device 840 and/or a computer that sends indications on behalf of the wearable device 840 (and/or on behalf of the wearer of the wearable device 840), such as the computer 847.
  • the computer 854 receives a request to make a reservation that involves occupying a place in a space shared with other people.
  • the request may be transmitted from a device used by a user wearing the wearable device 840, a computer that is in communication with the wearable device 840, such as the computer 847 (which may optionally be part of the wearable device 840), or some other computer.
  • the computer 854 receives a first indication generated based on first measurements taken during a first period by the wearable device 840. In one example, the first period ends at most three hours before the first indication is generated.
  • the first indication is generated by the computer 847 and it indicates that the wearer of the wearable device 840 is healthy.
  • the computer 854 provides an identifier of the reservation, which reserves the place at a certain time for the wearer of the wearable device 840 during the first period.
  • the computer 854 receives a second indication generated based on second measurements taken by the wearable device 840 during a second period that is after the first period.
  • the second measurements are taken less than three hours before the certain time, and the second indication indicates: (i) the wearer of the wearable device during the second period is the same person who wore the wearable device during the first period, (ii) that said same person is still healthy, and (iii) that said same person is in the vicinity of an automatic door 855 that facilitates passage into the space.
  • the second indication is generated by the computer 847.
  • the computer 854 commands the automatic door 855 to open and/or remain open.
  • this command is issued following a detection of transmissions of the wearable device 840 indicating that the wearable device is near the automatic door 855.
  • the computer 854 commands the automatic door 855 to close and/or remain shut, thus restricting passage into the space, responsive to receiving a third indication, sent after the second indication, indicating that the wearer of the wearable device at that time is not the same person as the wearer of the wearable device during the first period.
  • the computer 847 may send the third indication if an extent of similarity between characteristics of PPG signals in additional measurements taken while the wearable device 840 was near the automatic door 855 and characteristics of PPG signals in the first or second measurements fall below the second threshold.
  • a method for managing reservations with wearable-based health state verifications comprising: receiving a request to make a reservation that involves occupying a place in a space shared with other people; receiving a first indication generated based on first measurements taken during a first period by a wearable device; wherein the first measurements comprise values of physiological signals of the wearer of the wearable device during the first period, and the first indication indicates said wearer is healthy; providing an identifier of the reservation that reserves the place at a certain time for the wearer of the wearable device during the first period; receiving a second indication generated based on second measurements taken by the wearable device during a second period that is after the first period; wherein at least some of the second measurements were taken less than three hours before the certain time, the second measurements comprise values of physiological signals of the wearer of the wearable device
  • the space is an interior of a cabin of a vehicle that accommodates a driver and/or a plurality of passengers.
  • the space is an interior of a building housing an eating establishment and/or entertainment complex, and the space accommodates multiple patrons; and wherein the reservation is indicative of a certain seat reserved for the wearer of the wearable device.
  • the space is an interior of one of the following: a cabin of a public transport vehicle, a passenger train car, a cabin of an aircraft, and a ferry; and wherein the reservation is indicative of a certain seat reserved for the wearer of the wearable device. 5.
  • the wearable device comprises a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user, and a second sensor configured to measure a temperature of the user. 6.
  • PPG signal photoplethysmogram signal
  • the method of claim 1 further comprising providing an interface through which the request to make the reservation is entered in response to receiving the first indication. 7.
  • the method of claim 9, further comprising canceling the reservation and/or revoking an approval of access to the space given to the wearer of the wearable device during the first period responsive to receiving a fourth indication indicating that the wearer of the wearable device did not adhere to the protocol.
  • a system configured to manage access using reservations and wearable-based health state verifications, comprising: a wearable device comprising: a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a wearer of the wearable device, and a second sensor configured to measure a temperature of said wearer; and a computer configured to: receive a request to make a reservation that involves occupying a place in a space shared with other people; receive a first indication generated based on first measurements taken during a first period by the wearable device; wherein the first indication indicates a wearer of the wearable device is healthy; provide an identifier of the reservation that reserves the place at a certain time for the wearer of the wearable device during the first period; receive a second indication generated based on second measurements taken by the wearable device during a second period that is after the first period; wherein at least some of the second measurements were taken less than three hours before the certain time, and the second indication indicates: (i) the wearer of the wearable device
  • the computer is further configured to command the automatic door to close and/or remain shut, thus restricting passage into the space, responsive to receiving a third indication, sent after the second indication, indicating that the wearer of the wearable device at that time is not the same person as the wearer of the wearable device during the first period.
  • the automatic door belongs to a vehicle, and commanding the automatic door to open unlocks the door and/or moves the door to an open position, enabling to enter the cabin of the vehicle.
  • the automatic door is an entrance door to a room and/or building, and commanding the automatic door to open unlocks the door and/or moves the door to an open position, enabling to enter the interior of the room and/or building.
  • a non-transitory computer readable medium storing one or more computer programs configured to cause a processor based system to execute steps comprising: receiving a request to make a reservation that involves occupying a place in a space shared with other people; receiving a first indication generated based on first measurements taken during a first period by a wearable device; wherein the first measurements comprise values of physiological signals of the wearer of the wearable device during the first period, and the first indication indicates said wearer is healthy; providing an identifier of the reservation that reserves the place at a certain time for the wearer of the wearable device during the first period; receiving a second indication generated based on second measurements taken by the wearable device during a second period that is after the first period; wherein at least some of the second measurements were taken less than three hours before the certain time, the second measurements comprise values of physiological signals of the wearer of the wearable device during the second period, and the second indication indicates: (i) the wearer of the wearable device during the second period is the same person who wore the wearable device during the first
  • FIG. 6 is a schematic illustration of a doorway system that includes a doorway 858 that facilitates passage from an inside to an outside, and/or from the outside to the inside.
  • the doorway 858 includes a barrier 859, disposed in the doorway 858, that moves between an opened position and a closed position based on commands sent by a computer 860. When in the closed position, the barrier 859 restricts passage through the doorway 858, and when in the opened position, the barrier 859 does not restrict the passage through the doorway.
  • the doorway system includes one or more sensors that measure: a first signal indicative of whether there is a first user 863A on the outside of the doorway, and a second signal indicative of whether there is a second user 863B on the inside of the doorway.
  • the doorway system includes at least one of: a first sensor 861A that is capable of detecting whether the first user 863A is outside and a second sensor 861B that is capable of detecting whether the second user 863B is on the inside.
  • the computer 860 operates the doorway 858 in a manner that helps restrict contact between people that may be dangerous and contribute to the spread of disease. Optionally, this is done by restricting entrance of people who are not healthy through the doorway 858 in to the inside.
  • Examples of computers that may be utilized to perform the calculations of one or more computers that may be collectively referred to as “the computer 860” are computer 400 or computer 410, illustrated in FIG. 14A and FIG. 14B, respectively.
  • the computer 860 operates the doorway 858 in a manner that restricts passage through the doorway 858 when the first user 863A is on the outside, the second user 863B is on the inside, and at least one of them is not verified as being healthy and/or non-contagious.
  • this characteristic of the doorway 858 is implemented by the computer 860 as follows:
  • the computer 860 determines whether there are users on either side of the doorway 858. This involves detecting based on the first signal whether the first user 863A is on the outside, and detecting based on the second signal whether the second user 863B is on the inside.
  • the first user 863A may be admitted if a first indication is received, indicating that the first user 863A is healthy and/or non-contagious.
  • the first indication is received from a first device 862A carried and/or worn by the first user 863A.
  • the first indication does not include information identifying the first user 863A.
  • receiving the first indication is sufficient for the computer 860 to command barrier 859 to move to an open position and/or remain in the opened position (since there is no risk that the first user 863A will put people inside at risk).
  • the computer 860 may restrict the entrance of the first user 863A if that will put the first user 863A at risk because someone else, whose health state is not verified as being healthy and/or non-contagious is on the inside.
  • the computer 860A if the computer 860A detects the first user 863A is on the outside and the first indication indicates the first user 863A is healthy, but the computer 860 detects the second user 863B is on the inside, the computer 860 will not allow the first user 863A without verifying the health state of the second user 863B. Thus, in such a situation, the computer 860 commands the barrier 859 to move to an opened position and/or remain in the opened position, responsive to receiving, from a second device 862B carried and/or worn by the second user 863B, a second indication indicating the second user 863B is healthy.
  • the first device 862A carried and/or worn by the first user 863A receives measurements of physiological signals of the first user 863A.
  • the physiological signals include a PPG signal and a temperature signal (i.e., one or more measurements of the temperature of the first user 863A).
  • the physiological signals are sent by the wearable device 840.
  • the first indication is sent by the computer 847.
  • the first device 862A carried and/or worn by the first user 863A is the wearable device 840.
  • the second device 862B carried and/or worn by the second user 863B receives measurements of physiological signals of the second user 863B.
  • the physiological signals include a PPG signal and a temperature signal (i.e., one or more measurements of the temperature of the second user 863B).
  • the physiological signals are sent by the wearable device 840.
  • the second indication is sent by the computer 847.
  • the second device 862B carried and/or worn by the second user 863B is the wearable device 840.
  • the second indication does not include information identifying the second user 863B.
  • the computer 860 commands the barrier 859 to move to the closed position and/or remain in the closed position, under certain conditions.
  • One condition that may cause the computer 860 to do so is if it detects, based on the first signal that the first user 863A is on the outside, it detects, based on the second signal that the second user 863B is not on the inside, and does not receive the first indication indicating the first user 863A is healthy.
  • Another condition under which the computer 860 may command the barrier 859 to move to the closed position and/or remain in the closed position is if the computer 860 detects, based on the first signal that the first user 863A is on the outside, it detects, based on the second signal that the second user 863B is on the inside, and does not receive at least one of the first indication indicating the first user 863A is healthy and the second indication indicating the second user 863B is healthy, respectively.
  • FIG. 3 Various examples of doorways that may be controlled by the system illustrated in FIG. 6 are illustrated in FIG. 3.
  • the barrier 859 is a door that belongs to a vehicle 850C, and commanding the barrier to move to the opened position and/or remain in the opened position comprises commanding the door to unlock and/or move to a position that enables the first user 863A to enter a passenger cabin of the vehicle 850C.
  • the barrier 859 is an entrance door to a room and/or building (e.g., door 850A), and commanding the barrier to move to the opened position and/or remain in the opened position comprises commanding the entrance door to unlock and/or move to a position that enables the first user 863A to enter the interior of the room and/or building.
  • a room and/or building e.g., door 850A
  • commanding the barrier to move to the opened position and/or remain in the opened position comprises commanding the entrance door to unlock and/or move to a position that enables the first user 863A to enter the interior of the room and/or building.
  • the barrier 859 is a turnstile or a revolving door belonging to a gate (e.g., door 850B or gate 850D), and commanding the barrier to move to the opened position and/or remain in the opened position comprises enabling the turnstile or the revolving door to revolve and/or revolving the turnstile or the revolving door, which enables the first user 863A to pass through the gate.
  • a presence of multiple users are on the inside and/or on the outside may require the computer 860 to adjust the operation of the doorway 858 in order to help reduce unwanted contacts with users whose health state is not verified as being healthy and/or non-contagious.
  • the computer 860 commands the barrier 859 to move to the closed position and/or remain in the closed position, responsive to detecting, based on the first signal, that a plurality of users are on the outside, and not receiving, for each user from among the plurality of the users, an indication indicating said user is healthy, which is sent by a device carried and/or worn by said user.
  • the computer 860 may command the barrier 859 to move to the closed position and/or remain in the closed position, responsive to: detecting, based on the second signal, that a plurality of users are on the inside, and not receiving, for each user from among the plurality of the users, an indication indicating that said user is healthy, which is sent by a device carried and/or worn by said user.
  • the first and/or second indications mentioned above may be transmitted at the request of the computer 860.
  • the computer 860 transmits a request for the first indication indicating the first user is healthy, responsive to detecting that the first user 863A is on the outside, and/or transmits a request for the second indication indicating the second user 863B is healthy, responsive to detecting that the second user 863B is on the inside.
  • the first and second signals may be signals generated by devices worn and/or carried by the first user 863 A and the second user 863B, respectively.
  • the one or more sensors may include a receiver that detects the first and second signals and/or a plurality of receivers that triangulate locations of the devices that sent these signals.
  • the first and second signals may be signals from which the computer 860 detects the presence of the first user 863A and the second user 863B, respectively.
  • the one or more sensors include a camera aimed to the outside, the first signal includes images of the outside, and detecting the first user 863A is outside involves identifying presence of a person in the images.
  • the one or more sensors include a thermal sensor aimed to the outside, the first signal includes thermal measurements of the outside, and detecting the first user 863A is outside involves identifying a thermal signature corresponding to a person in the thermal measurements.
  • the one or more sensors include a pressure sensor disposed in a surface on the outside, the first signal includes values indicative of pressure applied to the pressure sensor, and detecting the first user 863A is outside involves identifying the values reflect application of a pressure corresponding to a weight of a person.
  • FIG. 8 illustrates a flowchart according to which the computer 860 may command the barrier 859 to open and/or close.
  • Steps 865A and 866A involve receiving the first and second signals, respectively.
  • Steps 865B and 866B involve determining whether the first user 863A is outside and the second user 863B is inside, respectively.
  • Steps 865C and 866C involve receiving the first and second indications, respectively.
  • Steps 865D and 866D involve determining whether the first user 863A is healthy and whether the second user 863B is healthy, respectively.
  • Information determined based on some, or all of the aforementioned steps is provided to the computer 860, which in step 867 operates the barrier according to the logic described in the table included in that the illustration of that step.
  • the steps illustrated in FIG. 8 may be used to implement a method for controlling the doorway 858. This method may be implemented using an embodiment of a system illustrated in FIG. 6, which is discussed above. The steps described below may be performed by running a computer program having instructions for implementing the method. Optionally, the instructions may be stored on a computer- readable medium, which may optionally be a non-transitory computer-readable medium. In response to execution by a system including a processor and memory, the instructions cause the system to perform steps mentioned below.
  • the method for controlling the doorway 858 includes the following steps: [0186] In Step 865A, receiving a first signal indicative of whether there is a first user on an outside of the doorway 858.
  • Step 865B detecting based on the first signal that the first user is on the outside.
  • Step 865C receiving, from a first device carried and/or worn by the first user, a first indication indicating the first user is healthy.
  • Step 866A receiving a second signal indicative of whether there is a second user on the inside of the doorway.
  • Step 866B detecting based on the second signal whether the second user is on the inside.
  • Step 867 operating the barrier 859 according to the logic in the table in FIG. 8, which involves commanding the barrier 859 to move to the opened position and/or remain in the opened position, responsive to: (i) detecting that the second user is not on the inside (in Step 866B), or (ii) detecting that the second user is on the inside (in Step 866B) and receiving , from a second device carried and/or worn by the second user, a second indication (in Step 866C), which in Step 866D is determined to indicate the second user is healthy.
  • the method for controlling the doorway 858 may optionally include a step of commanding the barrier to move to the closed position and/or remain in the closed position, responsive to: (i) detecting based on the first signal that the first user is on the outside (in Step 865B), detecting based on the second signal that the second user is not on the inside (in Step 866B), and not receiving the first indication indicating the first user is healthy, or (ii) detecting based on the first signal that the first user is on the outside (in Step 865B), detecting based on the second signal that the second user is not on the inside (in Step 866B), and not receiving at least one of the first indication indicating the first user is healthy and the second indication indicating the second user is healthy.
  • the method for controlling the doorway 858 may optionally include the following steps: commanding the barrier to move to the closed position and/or remain in the closed position, responsive to detecting, based on the first signal, that a plurality of users are on the outside, and not receiving, for each user from among the plurality of the users, an indication indicating said user is healthy, which is sent by a device carried and/or worn by said user.
  • the method for controlling the doorway 858 may optionally include the following steps: commanding the barrier to move to the closed position and/or remain in the closed position, responsive to: detecting, based on the second signal, that a plurality of users are on the inside, and not receiving, for each user from among the plurality of the users, an indication indicating that said user is healthy, which is sent by a device carried and/or worn by said user.
  • the method for controlling the doorway 858 may optionally include the following step: transmitting a request for the first indication indicating the first user is healthy, responsive to detecting that the first user is on the outside.
  • a doorway system comprising: a doorway that facilitates passage from an inside to an outside, and/or from the outside to the inside; a barrier, disposed in the doorway, configured to move between an opened position and a closed position based on commands sent by a computer; wherein, when in the closed position, the barrier restricts passage through the doorway, and when in the opened position, the barrier does not restrict the passage through the doorway; one or more sensors configured to measure: a first signal indicative of whether there is a first user on the outside of the doorway, and a second signal indicative of whether there is a second user on the inside of the doorway; and the computer is configured to: detect based on the first signal that the first user is on the outside; receive, from a first device carried and/or worn by the first user, a first indication
  • the computer is further configured to command the barrier to move to the closed position and/or remain in the closed position, responsive to: (i) detecting based on the first signal that the first user is on the outside, detecting based on the second signal that the second user is not on the inside, and not receiving the first indication indicating the first user is healthy, or (ii) detecting based on the first signal that the first user is on the outside, detecting based on the second signal that the second user is on the inside, and not receiving at least one of the first indication indicating the first user is healthy and the second indication indicating the second user is healthy, respectively.
  • the doorway of claim 1 wherein the computer is further configured to command the barrier to move to the closed position and/or remain in the closed position, responsive to: detecting, based on the second signal, that a plurality of users are on the inside, and not receiving, for each user from among the plurality of the users, an indication indicating that said user is healthy, which is sent by a device carried and/or worn by said user. 5.
  • the doorway of claim 1 wherein the first indication does not comprise information identifying the first user. 6.
  • the second indication does not comprise information identifying the second user. 7.
  • the doorway of claim 1, wherein the barrier is a door that belongs to a vehicle, and commanding the barrier to move to the opened position and/or remain in the opened position comprises commanding the door to unlock and/or move to a position that enables the first user to enter a passenger cabin of the vehicle.
  • the barrier is an entrance door to a room and/or building, and commanding the barrier to move to the opened position and/or remain in the opened position comprises commanding the entrance door to unlock and/or move to a position that enables the first user to enter the interior of the room and/or building.
  • the computer is further configured to transmit a request for the first indication indicating the first user is healthy, responsive to detecting that the first user is on the outside and/or to transmit a request for the second indication indicating the second user is healthy, responsive to detecting that the second user is on the inside. 11.
  • a method for controlling a doorway comprising: receiving a first signal indicative of whether there is a first user on an outside of a doorway; wherein the doorway facilitates passage from an inside to the outside, and/or from the outside to the inside and the doorway comprises a barrier configured to move between an opened position and a closed position; and wherein, when in the closed position, the barrier restricts passage through the doorway, and when in the opened position, the barrier does not restrict passage through the doorway; detecting based on the first signal that the first user is on the outside; receiving, from a first device carried and/or worn by the first user, a first indication indicating the first user is healthy; receiving a second signal indicative of whether there is a second user on the inside of the doorway; detecting based on the second signal whether the second user is on the inside; and commanding the barrier to move to the opened position and/or remain in the opened position, responsive to: (i) detecting that the second user is not on the inside, or (ii) detecting that the second user is on the
  • the method of claim 14, further comprising commanding the barrier to move to the closed position and/or remain in the closed position, responsive to: (i) detecting based on the first signal that the first user is on the outside, detecting based on the second signal that the second user is not on the inside, and not receiving the first indication indicating the first user is healthy, or (ii) detecting based on the first signal that the first user is on the outside, detecting based on the second signal that the second user is on the inside, and not receiving at least one of the first indication indicating the first user is healthy and the second indication indicating the second user is healthy, respectively. 16.
  • the method of claim 14, further comprising commanding the barrier to move to the closed position and/or remain in the closed position, responsive to detecting, based on the first signal, that a plurality of users are on the outside, and not receiving, for each user from among the plurality of the users, an indication indicating said user is healthy, which is sent by a device carried and/or worn by said user.
  • the method of claim 14, further comprising commanding the barrier to move to the closed position and/or remain in the closed position, responsive to: detecting, based on the second signal, that a plurality of users are on the inside, and not receiving, for each user from among the plurality of the users, an indication indicating that said user is healthy, which is sent by a device carried and/or worn by said user. 18.
  • a non-transitory computer readable medium storing one or more computer programs configured to cause a processor based system to execute steps comprising: receiving a first signal indicative of whether there is a first user on an outside of a doorway; wherein the doorway facilitates passage from an inside to the outside, and/or from the outside to the inside and the doorway comprises a barrier configured to move between an opened position and a closed position; and wherein, when in the closed position, the barrier restricts passage through the doorway, and when in the opened position, the barrier does not restrict passage through the doorway; detecting based on the first signal that the first user is on the outside; receiving, from a first device carried and/or worn by the first user, a first indication indicating the first user is healthy; receiving a second signal indicative of whether there is a second user on the inside of the doorway; detecting based on the second signal whether
  • non-transitory computer readable medium of claim 19 further comprising instructions for executing steps comprising: commanding the barrier to move to the closed position and/or remain in the closed position, responsive to: (i) detecting based on the first signal that the first user is on the outside, detecting based on the second signal that the second user is not on the inside, and not receiving the first indication indicating the first user is healthy, or (ii) detecting based on the first signal that the first user is on the outside, detecting based on the second signal that the second user is on the inside, and not receiving at least one of the first indication indicating the first user is healthy and the second indication indicating the second user is healthy, respectively.
  • Managing physical access to locations can be especially challenging when precautions need to be taken in order to curb the spread of diseases such as the flu or COVID-19.
  • Some embodiments described herein use authenticated wearable-based health state verifications in order to authorize access to such locations, which can help curb the spread of these diseases.
  • FIG. 7 is a schematic illustration of components of a system configured to authorize physical access to a location, such as a work place, a public building, etc., based on an authenticated health score.
  • the system includes at least the wearable device 840 and the computer 847.
  • the computer 847 utilizes measurements of a user 874 taken with the wearable device 840, that day and on earlier days, to determine both if the user’s health state permits access to the location, and also to authenticate the user 874.
  • the system may optionally include additional elements such as an access control system 871, which is configured to allow or deny access to the location based on indications received from the computer 847.
  • an access control system 871 which is configured to allow or deny access to the location based on indications received from the computer 847.
  • FIG. 7 share many of the components and characteristics of embodiments of the system illustrated in FIG. 1, which is discussed in detail above, possibly with one or more differences.
  • One of the differences involves the computer 847 calculating an authentication score in order to provide or revoke an access privilege 872.
  • This process involves conveying information about the identity of the user being authenticated, which is not aspect that is necessarily present in embodiments of the system illustrated in FIG. 1.
  • Some of the embodiments of the system illustrated in FIG. 1 do not involve providing information that may identify the user wearing the wearable device 840.
  • the computer 847 analyzes measurements taken by the wearable device 840 of the user 874 and optionally, of the environment the user 874 is in at the time. This analysis involves calculations involving measurements taken at different times: (i) “current measurements”, which are taken with the wearable device 840 during a period that starts a certain time before the analysis is performed (e.g., a few hours before) and/or leading up to when the analysis is performed, and (ii) “baseline measurements” taken with the wearable device 840 on or more earlier days.
  • the current measurements are taken over a duration of at least five minutes.
  • the baseline measurements include more than an hour of measurements taken over a period of several days.
  • the computer 847 calculates a health score for the user 874 based on a difference between the baseline measurements and the current measurements, as explained in detail above (see description of embodiments according to FIG. 1). Additionally, the computer 847 calculates an authentication score based on a similarity between characteristics of a PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements. Optionally, the authentication score is proportional to the extent of similarity between characteristics of a PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements. Calculation of the extent of said similarity is explained in detail above (see description of embodiments according to FIG. 1). In some embodiments, the authentication score equals the extent of the similarity between characteristics of a PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements.
  • the computer 847 grants the user 874 the access privilege 872, which enables the user 874 to access the location.
  • granting the access privilege 872 involves transmitting an indication to the access control system 871, which may be a system that controls entryways into the location.
  • this transmitted indication includes information identifying the user 874 (e.g., a name, an employee number, a national identification number, or some other identifier) and/or information indicating the health state of the user 874.
  • granting access to the location involves adding an identifier of the user 874 to a list of people permitted to enter the location.
  • revoking access to the location involves removing an identifier of the user 874 from the list of people permitted to enter the location.
  • An access privilege previously granted to the user 874 may be revoked under certain conditions, such as it not being clear if it is still safe to let the user 874 enter the location.
  • the computer 847 revokes the access privilege 872, responsive to the health score not reaching the first threshold and/or the authentication score not reaching the second threshold.
  • knowledge about the health state of people who typically access the location can be used to set the first threshold. For example, if many of those people became ill, this may mean that there is an outbreak of an illness associated somehow with the location. In such a case, it may be desirable to increase the first threshold in order to reduce the chance of people who may be beginning to become ill, which may be only slightly symptomatic, of gaining access to the location.
  • the computer 847 increases the first threshold responsive to receiving a certain indication indicative of number of people, who are ill and who accessed the location in a preceding period of time, reaches a third threshold.
  • increasing the first threshold reduces tendency to deny and/or revoke privileges to access the location.
  • the calculated health score may be utilized to generate a certificate indicative of the health state of the user 874.
  • the computer 847 may provide an indication the user 874 is healthy, responsive to the health score reaching the first threshold and the authentication score reaching the second threshold.
  • the computer 847 may provide an indication that the user 874 is ill (a “sick note”), responsive to the health score not reaching the first threshold and the authentication score reaching the second threshold.
  • these indications regarding the health state of the user 874 may include information identifying the user 874.
  • the computer 847 receives additional measurements of the user 874 taken with the wearable device 840 at least four hours after the current measurements were taken.
  • the computer 847 calculates an additional health score based on a difference between the baseline measurements and the additional measurements.
  • the computer 847 also calculates an additional user authentication score based on a similarity between characteristics of the PPG signal in the additional measurements and the characteristics of the PPG signal in the baseline measurements. The computer 847 then provides an indication that the user 874 is no longer ill responsive to the additional health score reaching the first threshold and the additional user authentication score reaching the second threshold.
  • the computer 847 When the health state of multiple users is tracked using the system illustrated in FIG. 7, this can provide insights into the dynamics of illness, which can be used to predict how long the user 874 may be ill.
  • the computer 847 generates feature values based on the current measurements and the baseline measurements (e.g., feature values described herein as being generated from that data), and utilizes a model to calculate, based on the feature values, a value indicative of a duration of illness of the user 874.
  • the model is generated based on data comprising a first set of training measurements of a plurality of users taken while the plurality of users were not ill, a second set of training measurements of the plurality of users taken during illnesses of the plurality of users, and indications of durations of the illnesses.
  • the training measurements were taken using wearable devices, such as the wearable device 840.
  • FIG. 9 illustrates steps that may be part of embodiments of a method for managing authorization of access to a location based on authenticated health scores.
  • the method may be implemented using embodiments of systems illustrated in FIG. 7, which is discussed above.
  • the steps described below may be performed by running a computer program having instructions for implementing the method.
  • the instructions may be stored on a computer-readable medium, which may optionally be a non-transitory computer-readable medium.
  • the instructions In response to execution by a system including a processor and memory, the instructions cause the system to perform steps from among the steps illustrated in FIG. 9 and/or additional steps mentioned below.
  • the method for managing authorization of access to a location based on authenticated health scores includes at least the following steps: [0209] In Step 876 A, receiving current measurements of a user taken with a wearable device that includes: a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user, and a second sensor configured to measure a temperature of the user.
  • a wearable device that includes: a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user, and a second sensor configured to measure a temperature of the user.
  • PPG signal photoplethysmogram signal
  • the current measurements may be taken with the wearable device 840.
  • Step 876B receiving baseline measurements of the user taken with the wearable device during one or more earlier days.
  • Step 876C calculating a health score based on a difference between the baseline measurements and the current measurements.
  • Step 876D calculating an authentication score based on a similarity between characteristics of a PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements.
  • Step 876 responsive to determining the health score reaches a first threshold and the authentication score reaches a second threshold, granting the user a privilege to access the location.
  • the method may optionally include Step 876F, which involves revoking the privilege of the user to access the location, responsive to the health score not reaching the first threshold and/or the authentication score not reaching the second threshold.
  • the method may optionally include a step involving increasing the first threshold responsive to receiving a certain indication indicative of number of people, who are ill and who accessed the location in a preceding period of time, reaches a third threshold.
  • increasing the first threshold reduces tendency to revoke privileges to access the location.
  • a system configured to authorize physical access to a location based on an authenticated health score, comprising: a wearable device, comprising a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user, and a second sensor configured to measure a temperature of the user; and a computer configured to: receive current measurements of the user taken with the wearable device; receive baseline measurements of the user taken with the wearable device during one or more earlier days; calculate a health score based on a difference between the baseline measurements and the current measurements; calculate an authentication score based on a similarity between characteristics of a PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements; and responsive to the health score reaching a first threshold and the authentication score reaching a second threshold, grant the user a privilege
  • PPG signal photoplethysmogram signal
  • the computer is further configured to revoke the privilege of the user to access the location, responsive to the health score not reaching the first threshold and/or the authentication score not reaching the second threshold.
  • the computer is further configured to increase the first threshold responsive to receiving a certain indication indicative of number of people, who are ill and who accessed the location in a preceding period of time, reaches a third threshold; whereby increasing the first threshold reduces tendency to deny and/or revoke privileges to access the location. 4.
  • calculation of the health score by the computer comprises: calculating, based on the baseline measurements, an expected value of a physiological signal of the user; calculating, based on the current measurements, a current value of the physiological signal; and calculating the health score based on a difference between the expected value and the current value.
  • the physiological signal is body temperature
  • the calculating of the health score utilizes a function that returns a value that is below the first threshold when a current body temperature is greater than an expected body temperature by at least a certain margin; and wherein the certain margin is at least 0.4°C. 6.
  • calculating the current value of the physiological signal by the computer comprises: generating feature values based on the current measurements, and utilizing a model to calculate, based on the feature values, the current value of the physiological signal; and wherein the model was generated from training data comprising: previous measurements of the user taken with the wearable device, and values of the physiological signal obtained utilizing a sensor that is not part of the wearable device. 7.
  • the system of claim 1, wherein the computer is further configured to: determine, based on measurements taken with the wearable device, whether the wearable device was removed from the user’s body while the current measurements were taken or after the current measurements were taken, and responsive to making a determination that he wearable device has been removed, to revoke the privilege of the user to access the location.
  • the computer is further configured to perform the following steps responsive to making the determination that the wearable device was removed: receive additional measurements of the user, taken with the wearable device at most three hours after the current measurements were taken; calculate an additional similarity between the characteristics of the PPG signal in the current measurements and characteristics of a PPG signal in the additional measurements; and grant the user a privilege to access the location responsive to the health score reaching the first threshold and the additional similarity reaching the second threshold; whereby the additional similarity reaching the second threshold is indicative of a probability that the current measurements and the additional measurements are of the same person is above a predetermined threshold.
  • the system of claim 1, wherein the computer is further configured to: receive additional measurements of the user taken with the wearable device; calculate an additional authentication score based on a similarity between the characteristics of the PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements; calculate an additional health score based on a difference between the baseline measurements and the additional measurements; and responsive to additional authentication score reaching the second threshold, reporting the additional health score to the user and/or providing the user with an indication of whether a health state of the user permits access to the location.
  • the computer is further configured to provide an indication that the user is healthy responsive to the health score reaching the first threshold and the authentication score reaching the second threshold. 12.
  • the computer is further configured to: receive additional measurements of the user taken with the wearable device at least four hours after the current measurements were taken; calculate an additional health score based on a difference between the baseline measurements and the additional measurements; calculate an additional user authentication score based on a similarity between characteristics of the PPG signal in the additional measurements and the characteristics of the PPG signal in the baseline measurements; and provide an indication that the user is no longer ill responsive to the additional health score reaching the first threshold and the additional user authentication score reaching the second threshold. 14.
  • the computer is further configured to: generate feature values based on the current measurements and the baseline measurements, and utilize a model to calculate, based on the feature values, a value indicative of a duration of illness of the user; and wherein the model was generated based on data comprising a first set of training measurements of a plurality of users taken while the plurality of users were not ill, a second set of training measurements of the plurality of users taken during illnesses of the plurality of users, and indications of durations of the illnesses. 15.
  • the computer is further configured to: generate feature values based on data comprising the current measurements and the baseline measurements, and utilize a model to calculate, based on the feature values, the health score; and wherein the model was generated based on training data comprising a first set of training measurements of a plurality of users taken while the plurality of users healthy and a second set of training measurements of the plurality of users taken while the plurality of users were not healthy.
  • the system of claim 15, further comprising a temperature sensor configured to measure temperature of the environment (T env ); wherein the computer is further configured to generate one or more of the feature values based on first and second values of T env measured while the baseline measurements and the current measurements were taken, respectively, and to utilize the one or more of the feature values to calculate the health score; whereby the one or more of the feature values are indicative of a change to T env between when the baseline measurements were taken and when the current measurements were taken. 17.
  • a temperature sensor configured to measure temperature of the environment (T env )
  • the computer is further configured to generate one or more of the feature values based on first and second values of T env measured while the baseline measurements and the current measurements were taken, respectively, and to utilize the one or more of the feature values to calculate the health score; whereby the one or more of the feature values are indicative of a change to T env between when the baseline measurements were taken and when the current measurements were taken. 17.
  • a method for managing authorization of access to a location based on authenticated health scores comprising: receiving current measurements of a user taken with a wearable device that comprises: a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user, and a second sensor configured to measure a temperature of the user; receiving baseline measurements of the user taken with the wearable device during one or more earlier days; calculating a health score based on a difference between the baseline measurements and the current measurements; calculating an authentication score based on a similarity between characteristics of a PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements; and responsive to the health score reaching a first threshold and the authentication score reaching a second threshold, granting the user a privilege to access the location revoking the privilege of the user to access the location, responsive to the health score not reaching the first threshold and/or the authentication score not reaching the second threshold.
  • PPG signal photoplethysmogram signal
  • the method of claim 17, further comprising providing an indication that the user is ill responsive to the health score not reaching the first threshold and the authentication score reaching the second threshold.
  • the method of claim 18, further comprising: receiving additional measurements of the user taken with the wearable device at least four hours after the current measurements were taken; calculating an additional health score based on a difference between the baseline measurements and the additional measurements; calculating an additional user authentication score based on a similarity between characteristics of a PPG signal in the additional measurements and the characteristics of the PPG signal in the baseline measurements; and providing an indication that the user is no longer ill responsive to the additional health score reaching the first threshold and the additional user authentication score reaching the second threshold.
  • a non-transitory computer readable medium storing one or more computer programs configured to cause a processor based system to execute steps comprising: receiving current measurements of a user taken with a wearable device that comprises: a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user, and a second sensor configured to measure a temperature of the user; receiving baseline measurements of the user taken with the wearable device during one or more earlier days; calculating a health score based on a difference between the baseline measurements and the current measurements; calculating an authentication score based on a similarity between characteristics of a PPG signal in the current measurements and characteristics of a PPG signal in the baseline measurements; and responsive to the health score reaching a first threshold and the authentication score reaching a second threshold, granting the user a privilege to access the location revoking the privilege of the user to access the location, responsive to the health score not reaching the first threshold and/or the authentication score not reaching the second threshold.
  • PPG signal photoplethysmogram signal
  • Some embodiments disclosed herein utilize wearable devices that measure physiological signals of users in order to determine whether people who were at a location were healthy, and thus be able to certify the location as contagion-safe. For example, this can be useful for certifying a nursing home is contagion-safe, and then prevent admission of new residents who may be carrying disease.
  • FIG. 10 is a schematic illustration of an embodiment of a system configured to certify a premises 881 as contagion-safe.
  • the system includes wearable devices 878 that take measurements 879 of users 882 who are wearing the wearable devices 878.
  • the measurements 879 include photoplethysmogram signals of the users 882 and temperature signals of the users 882.
  • each of the wearable devices 878 is an embodiment of the wearable device 840, described in detail further above.
  • at least some of the wearable devices 878 are smartglasses, such as the smartglasses illustrated in FIG. 2.
  • Embodiments of the system illustrated in FIG. 10 also include a computer 880 which performs several steps in order to determine whether to certify the premises 881 as contagion-safe.
  • the computer 880 calculates health scores of the users 882 based on measurements 879 of the users 882 taken while the users were not on the premises 881.
  • the computer 880 identifies which of the users 882 are non-symptomatic users based on their health scores reaching a threshold (such as the first threshold mentioned in the context of embodiments illustrated in FIG. 1).
  • the computer 880 also authenticates the identities of the non-symptomatic users based on at least some of the measurements 879 (i.e., at least some of the measurements 879 that are of the non-symptomatic users).
  • the predetermined period is set according to characteristics of an epidemic for which the system protects.
  • the predetermined period may be set to a value between one day and ten days, depending on the time it typically takes for symptoms of the epidemic to manifest with infected individuals.
  • calculation of the health scores of the users 882 based on the measurements 879 by the computer 880 may be done in the same manner described in embodiments disclosed herein involving the computer 847 calculating health scores based on current and baseline measurements (in which case the measurements 879 include measurements taken over multiple days).
  • calculation of the health scores of the users 882 based on the measurements 879 by the computer 880 may be done in the same manner described in embodiments disclosed herein involving the computer 847 calculating health scores by utilizing one or more the machine learning approaches described with respect to calculation of health scores by the computer 847, such as generating feature values based on measurements of a user, from among the measurements 879, and utilizing a model to calculate, based on the feature values, a value that indicates whether that user is healthy and/or non-contagious.
  • authenticating the identities of the non-symptomatic users based on at least some of the measurements 879 may be done by the computer 880 in the same manner described in embodiments disclosed herein involving the computer 847.
  • the computer 880 may calculate the extent of similarity of PPG signals of a certain user in measurements from among the measurements 879 with a template generated based on previously measured PPG signals of that certain user.
  • the extent of similarity exceeds a threshold, the certain user may be considered authenticated.
  • authenticating the certain user may utilize additional signals from among measurements 879 mentioned herein as useful for authentication, such as acoustic signals and/or movement signals.
  • the computer 880 determines whether to certify the premises 881 as contagion-safe.
  • certifying the premises 881 as contagion-safe means providing an indication to one or more of the users 882, other people, and/or other computer systems, that the premises 881 is contagion-safe.
  • An indication of a certification of the premises 881 as contagion-safe can be used for various applications, such as deciding on quarantine or stay-at-home orders for people who visited the premises 881, assessment of risk these people are ill, and/or assessment of a risk of exposure to people form among the users 882.
  • the indication is indicative of the fact that only the non- symptomatic users, whose authentication was successful, entered the premises 881 during the predetermined period.
  • the indication is indicative of the fact that the non-symptomatic users whose authentication was successful comprise at least a certain predetermined proportion of all of the users 882 who visited the premises 881.
  • de-certifying the premises 881 as contagion-safe means sending an a second indication canceling the indication sent when certifying the premises 881 as contagion-safe and/or sending an indication to one or more of the users 882, other people, and/or other computer systems, indicating that the premises is not contagion-safe.
  • the computer 880 certifies the premises 881 as contagion-safe responsive to determining that, from among the users 882, only non-symptomatic users, whose authentication was successful, entered the premises 881 during a predetermined period.
  • the computer 880 certifies the premises 881 as contagion-safe responsive to determining that that the non-symptomatic users whose authentication was successful comprise at least a certain predetermined proportion of all of the users 882 who visited the premises 881.
  • the predetermined proportion may be selected by the operator at the premises 881. For example, the operator may decide that the threshold is 90% of non-symptomatic users in the premises 881, whose authentication was successful, in order to certify the premises 881 as contagion-safe. And if the percent of the non- symptomatic authenticated users falls below 90% then the certification of the premises as contagion-safe is revoked. Additionally or alternatively, the operator may decide that the threshold is density below 0.3 per square meter of non-symptomatic users, density below 0.06 per square meter of users for which symptom status is unknown, and density below 0.03 per square meter of symptomatic users.
  • the computer 880 may present, e.g., via a user interface, an indication proportional to at least one of percent and/or density of the following: the non-symptomatic users in the premises 881, symptomatic users in the premises 881, and users for which symptom status is unknown.
  • the presented indications support decision of other users whether to visit the premises 881 at that time.
  • the computer 880 may receive a location of a certain user at the premises 881, and recommend the certain user use certain personal protection equipment based on the indication proportional to the at least one of the percent and/or the density. This recommendation can help the certain user to decide whether personal protection equipment is required, and to what extent. For example, whether using face mask should be enough, and whether gloves are also needed.
  • the computer 880 may refer to different components and/or a combination of components.
  • the computer 880 may be a server or a collection of servers (e.g., on a computing cloud).
  • at least some of the functionality attributed to the computer 880 may be performed by computers associated with those users, such as cloud-based servers hosting accounts of those users and/or processors on devices of those users (e.g., smartphones) or wearable devices of those users.
  • references to calculations being performed by the “computer 880”, and the like, should be interpreted as calculations being performed utilizing one or more computers, as described in the examples above.
  • Examples of computers that may be utilized to perform the calculations of one or more computers that may be collectively referred to as “the computer 880” are computer 400 or computer 410, illustrated in FIG. 14A and FIG. 14B, respectively.
  • the computer 880 may notify certain users, e.g., via user interfaces of devices the carry (e.g., screens of smartphones) or user interfaces of the wearable devices 878, whether they are permitted on the premises 881.
  • a user interface may be used to notify a non- symptomatic user that said non-symptomatic user is allowed on the premises 881.
  • the computer 880 may identify some of the users 882 as symptomatic users based on their measurements taken while not on the premises 881. For example, their health scores may be below a threshold.
  • a user interface may be utilized to notify a symptomatic user, prior that user’s arriving to the premises 881, that that user is not allowed on the premises 881.
  • the computer 880 receives identities of at least some of the users 882 who arrived at the premises 881 and determines based on the identities, whether a user, who is not among the non-symptomatic users, entered the premises 881.
  • the identities may be received via various systems. In one example, the identities are received from a security system that utilizes video cameras and image recognition to determine who entered the premises 881. In another example, the identities are received from a security system that logs entry to the premises 881 via a key card mechanism. In still another example, the identities may be received via identification of transmissions of the wearable devices 878 and/or other mobile devices carried by the users 882 (e.g., smartphones).
  • the computer 880 identifies some of the users 882 as symptomatic users based on their health scores being below the threshold, and decertifies the premises 881 as contagion-safe responsive to detecting that a symptomatic user entered the premises 881 after the predetermined period.
  • the computer 880 receives an indication of a time at which the symptomatic user left the premises 881, and re-certifies the premises 881 as contagion-safe after a predetermined duration from that time.
  • obtaining the time the symptomatic user left the premises 881 may be done using one of more of the techniques mentioned above (e.g., image processing, access control system or time card system, etc.).
  • the computer 880 may identify that a person not wearing one of the wearable devices 878 (a non -cleared person) entered the premises 881 after the predetermined period, and decertify the premises 881 as contagion-safe responsive to detecting that the non-cleared person entered the premises 881.
  • the computer 880 may identify, after the predetermined period, that a user on the premises 881 became ill, and decertify the premises 881 as contagion-safe.
  • the health scores are calculated with respect to a certain disease, and certification of the premises 881 as contagion-safe is indicative that only non-symptomatic users with respect to the certain disease, whose authentication was successful, entered the premises 881 during the predetermined period.
  • the computer 880 may confirm, based on external medical records, immunity of one or more people who had the certain disease and refrain from decertifying the premises 881 due to their entry to the premises 881 during the predetermined period.
  • FIG. 12 illustrates steps that may be part of embodiments of a method for certifying a premises as contagion-safe.
  • the method may be implemented using embodiments of systems illustrated in FIG. 10, which is discussed above.
  • the steps described below may be performed by running a computer program having instructions for implementing the method.
  • the instructions may be stored on a computer-readable medium, which may optionally be a non-transitory computer-readable medium.
  • the instructions In response to execution by a system including a processor and memory, the instructions cause the system to perform steps from among the steps illustrated in FIG. 12 and/or additional steps mentioned below.
  • the method for certifying a premises as contagion-safe includes at least the following steps:
  • Step 884A receiving measurements of users measured with wearable devices (e.g., units of the wearable device 840), while the users were not on the premises.
  • the measurements include photoplethysmogram signals of users and temperature signals of the users.
  • Step 884B calculating health scores of the users based on the measurements.
  • Step 884C identifying which of the users are non-symptomatic users based on their health scores being reaching a threshold.
  • Step 884D authenticating identities of the non-symptomatic users based on at least some of their measurements.
  • Step 884E certifying the premises as contagion-safe responsive to determining that, from among the users, only non-symptomatic users, whose authentication was successful, entered the premises during a predetermined period.
  • the method may optionally include Step 884F involving notifying the non- symptomatic users that they are allowed on the premises. Additionally or alternatively, the method may include optional steps involving: identifying some of the users as symptomatic users based on their measurements measured while not on the premises, and notifying the symptomatic users, prior to their arriving to the premises, that they are not allowed on the premises.
  • the method may optionally include Step 884G involving: identifying some of the users as symptomatic users based on their health scores being below the threshold, and decertifying the premises as contagion-safe responsive to detecting that a symptomatic user entered the premises after the predetermined period.
  • the method may also include steps involving: receiving an indication of a time when the symptomatic user left the premises, and re-certifying the premises as contagion-safe after a predetermined duration from that time.
  • the method may optionally include a step involving: identifying, after the predetermined period, that a user on the premises became ill, and decertifying the premises as contagion- safe.
  • a system configured to certify a premises as contagion-safe, comprising: wearable devices configured to take measurements of users wearing the wearable devices; wherein the measurements comprise photoplethysmogram signals and temperature signals; and a computer configured to: calculate health scores of the users based on measurements of the users taken while the users were not on the premises; identify which of the users are non-symptomatic users based on their health scores reaching a threshold; authenticate identities of the non-symptomatic users based on at least some of said measurements; and certify the premises as contagion-safe responsive to determining that, from among the users, only non-symptomatic users, whose authentication was successful, entered the premises during a predetermined period.
  • each wearable device from among the wearable devices comprises a first sensor configured to measure a signal indicative of a photoplethysmogram signal (PPG signal) of a user wearing the wearable device, and a second sensor configured to measure a temperature of the user.
  • PPG signal photoplethysmogram signal
  • the wearable device further comprises an acoustic sensor configured to take audio recordings of the user; and the computer is further configured to utilize, in calculation of a health score of the user, and extent of coughing recognizable in the audio recordings of the user.
  • the computer is further configured to receive identities of at least some of the users who arrived at the premises and to determine, based on the identities, whether a user, who is not among the non-symptomatic users, entered the premises.
  • the computer is further configured to: identify some of the users as symptomatic users based on their health scores reaching the threshold, and decertify the premises as contagion-safe responsive to detecting that a symptomatic user entered the premises after the predetermined period.
  • the computer is further configured to receive an indication of a time when the symptomatic user left the premises, and to re-certify the premises as contagion-safe after a predetermined duration from that time.
  • the computer is further configured to identify that a person not wearing one of the wearable devices (a non-cleared person) entered the premises after the predetermined period, and decertify the premises as contagion-safe responsive to detecting that the non-cleared person entered the premises.
  • the computer is further configured to identify, after the predetermined period, that a user on the premises became ill, and decertify the premises as contagion-safe. 11.
  • the computer is further configured to confirm, based on external medical records, immunity of one or more people who had the certain disease and to refrain from decertifying the premises due to their entry to the premises during the predetermined period.
  • a system configured to certify a premises as contagion-safe, comprising: wearable devices configured to take measurements of users comprising photoplethysmogram signals of the users and temperature signals of the users; and a computer configured to: calculate health scores of the users based on measurements of the users taken while the users were not on the premises; identify which of the users are non-symptomatic users based on their health scores reaching a threshold; authenticate identities of the non-symptomatic users based on at least some of their measured physiological signals; and certify the premises as contagion-safe responsive to determining that the non-symptomatic users whose authentication was successful comprise at least a certain predetermined proportion of all of the users who visited the premises. 14.
  • the system of claim 13, further comprising a user interface configured to present an indication proportional to at least one of percent and/or density of the following: the non-symptomatic users in the premises, symptomatic users in the premises, and users for which symptom status is unknown; whereby the presented indications supports decision of other users whether to visit the premises at that time.
  • the computer is further configured to receive location of a certain user in the premises, and recommend the certain user use certain personal protection equipment based on the indication proportional to the at least one of the percent and/or the density.
  • a method for certifying a premises as contagion-safe comprising: receiving measurements of users measured with wearable devices while the users were not on the premises; wherein the measurements comprise photoplethysmogram signals of users and temperature signals of the users; calculating health scores of the users based on the measurements; identifying which of the users are non-symptomatic users based on their health scores reaching a threshold; authenticating identities of the non-symptomatic users based on at least some of their measurements; and certifying the premises as contagion-safe responsive to determining that, from among the users, only non-symptomatic users, whose authentication was successful, entered the premises during a predetermined period. 17.
  • the method of claim 16 further comprising notifying the non-symptomatic users that they are allowed on the premises. 18.
  • the method of claim 16 further comprising: identifying, after the predetermined period, that a user on the premises became ill, and decertifying the premises as contagion- safe.
  • Some embodiments disclosed herein utilize wearable devices that measure physiological signals of users in order to determine whether the users are healthy, and thus should be allowed to enter a location that is assumed to be contagion-sage. In one example, this can be useful for certifying a nursing home is contagion-safe, and then screening new residents prior to their admission in order to keep the nursing home free of disease. In another example, this approach can be used to pre-screen passengers intending to take a flight, in order to keep off the aircraft any passengers who may be symptomatic and spread a disease onboard.
  • FIG. 11 is a schematic illustration of an embodiment of a system for managing access to a contagion-safe premises.
  • the system includes wearable devices 878 that take measurements of users 888 who are wearing the wearable devices 878. Additionally, the system includes a computer 886, which performs several steps in order to manage access to the contagion-safe premises.
  • the wearable devices 878 take measurements of the users 888 that include photoplethysmogram signals of the users 888 and temperature signals of the users 888.
  • each of the wearable devices 878 is an embodiment of the wearable device 840, described in detail further above.
  • at least some of the wearable devices 878 are smartglasses, such as the smartglasses illustrated in FIG. 2.
  • the measurements of the users 888 taken with the wearable devices 878 include current measurements 883 of the users 888 and baseline measurements 884 of the users 888.
  • the current measurements 883 include for each user from among the users 888, measurements of the user, taken with a wearable device from among the wearable devices 878, up to 4 hours before an intended arrival time of the user to a premises 889.
  • current measurements 883 include measurements that are intended to reflect the state of the user during the hours leading up to an intended time of arriving at the premises 889.
  • the baseline measurements 884 include for each user from among the users 888, measurements of the user, taken with a wearable device from among the wearable devices 878 at least 10 hours before the intended arrival time of the user (i.e., the baseline measurements are taken 10 hours before the intended arrival or even earlier than 10 hours before the intended arrival). These measurements are intended to reflect a typical state of the user at an earlier time (e.g., the user’s baseline state).
  • the computer 886 calculates health scores of the users 888 based on differences between the current measurements 883 and the baseline measurements 884.
  • the health score of each certain user from among the users 888 is calculated based on current measurements of the certain user, from among the current measurements 883, and baseline measurements of the certain user, from among the baseline measurements 884. Calculation of the health score for the certain user may be done in the same manner described herein in which the computer 847 calculates the health score based on differences between the current measurements and baseline measurements in embodiments illustrated in FIG. 1.
  • the calculation of the health score of the certain user is performed by a processor on a device of the certain user.
  • the computer 886 utilizes the health scores of the users 888 in order to identify a subset of the users 888 as non-symptomatic users.
  • this identification is done by comparing the health scores of the users 888 to a threshold, and selecting the users whose health score reaches the threshold (e.g., this threshold may be the first threshold mentioned in the context of embodiments illustrated in FIG. 1).
  • the computer 886 also authenticates identities of the non-symptomatic users based on at least some of their current measurements (i.e., measurements from among the current measurements 883 that are taken from them).
  • such an authentication is performed by the computer 886 in the same manner described in embodiments disclosed herein involving the computer 847.
  • the computer 886 may calculate the extent of similarity of PPG signals of a certain user in current measurements from among the current measurements 883 with a template generated based on previously measured PPG signals of that certain user (which may be in a database).
  • the extent of similarity exceeds a threshold, the certain user may be considered authenticated.
  • authenticating the certain user may utilize additional signals from among current measurements 883 mentioned herein as useful for authentication, such as acoustic signals and/or movement signals.
  • the computer 886 may then utilize authentications of non-symptomatic users in order to manage access to the premises 889.
  • the computer 886 notifies the non-symptomatic users, prior to their respective intended arrival times, that they are allowed on the premises 889. [0261] In one embodiment, the computer 886 receives additional measurements of a certain user among the non-symptomatic users, taken with a wearable device from among the wearable devices 878 after the current measurements of the certain user were taken, calculates an additional health score of the certain user based on differences between the additional measurements of the certain user and baseline measurements of the certain user, detects that the additional health score does not reach the threshold, and notifies the certain user that he/she not allowed on the premises 889.
  • the computer 886 identifies a second subset of the users 888 as symptomatic users based on their health scores not reaching the threshold, and notifies the symptomatic users, prior to their respective arrival times, that they are not allowed on the premises 889.
  • the computer 886 certifies the premises 889 as contagion-safe responsive to receiving an indication that none of the symptomatic users entered the premises 889 during a predetermined period.
  • the indication that none of the symptomatic users entered the premises is received from a physical access security system that identifies the person at the gate/door/premises, such as: proximity card access system, smart card access system, swipe card access system, multi-technology access system, keypad access system, biometric access system, mobile access system, and/or video intercom access system.
  • the premises 889 is an airplane
  • the intended arrival time is a boarding time to the airplane.
  • the computer 886 directs the non-symptomatic users and people who were not identified as non-symptomatic users to different airplanes.
  • the computer 886 places the users 888 in the airplane according to cohorts, such that >75% of the passengers who sit in proximity of up to two rows from people who were not identified as non-symptomatic users are also people who were not identified as non-symptomatic users, and >75% of the passengers who sit in proximity of up to two rows from the non-symptomatic users are non-symptomatic users.
  • the premises 889 is a train passenger car
  • the computer 886 directs the non-symptomatic users and people who were not identified as non-symptomatic users to different cars.
  • FIG. 13 illustrates steps that may be part of embodiments of a method for managing access to a contagion-safe premises.
  • the method may be implemented using embodiments of systems illustrated in FIG. 11 , which is discussed above.
  • the steps described below may be performed by running a computer program having instructions for implementing the method.
  • the instructions may be stored on a computer-readable medium, which may optionally be a non-transitory computer-readable medium.
  • the instructions In response to execution by a system including a processor and memory, the instructions cause the system to perform steps from among the steps illustrated in FIG. 13 and/or additional steps mentioned below.
  • the method for managing access to a contagion-safe premises includes at least the following steps:
  • Step 890A receiving measurements of users, measured with wearable devices, comprising photoplethysmogram signals and temperature signals.
  • the measurements include, for each users from among the users, current measurements and baseline measurements.
  • the current measurements of the user are measured with a wearable device up to 4 hours before an intended arrival time of the user to a premises, and baseline measurements of the user are measured with the wearable device at least 10 hours before the intended arrival time of the user.
  • Step 890B calculating, for each user from among the users, a health score of the user based on a difference between current measurements of the user and baseline measurements of the user.
  • Step 890C identifying a subset of the users as non-symptomatic users based on their health scores reaching a threshold.
  • Step 890D authenticating identities of the non-symptomatic users based on at least some of their current physiological signals.
  • Step 890E notifying the non-symptomatic users, prior to their respective intended arrival times, that they are allowed on the premises.
  • the method optionally includes Step 890F that involves: identifying a second subset of the users as symptomatic users based on their health scores not reaching the threshold, and notifying the symptomatic users, prior to their respective arrival times, that they are not allowed on the premises.
  • the method optionally includes a step of certifying the premises as contagion-safe responsive to receiving an indication that none of the symptomatic users entered the premises during a predetermined period.
  • the method optionally includes the following steps: receiving additional measurements of a certain user among the non-symptomatic users, taken after the current measurements of the certain user were taken, calculating an additional health score of the certain user based on differences between the additional measurements of the certain user and baseline measurements of the certain user, detecting that the additional health score does not reach the threshold, and notifying the certain user that he/she not allowed on the premises.
  • a system for managing access to a contagion-safe premises comprising: wearable devices configured to take measurements of users wearing the wearable devices; wherein the measurements comprise photoplethysmogram signals and temperature signals; and a computer configured to: receive for each user from among the users: current measurements of a user, taken with a wearable device up to 4 hours before an intended arrival time of the user to a premises, and baseline measurements of the user, taken with the wearable device at least 10 hours before the intended arrival time of the user; calculate health scores of the users based on differences between their current measurements and their baseline measurements; identify a subset of the users as non- symptomatic users based on their health scores reaching a threshold; authenticate identities of the non- symptomatic users based on at least some of their current measurements; and notify the non-symptomatic users, prior
  • the computer is further configured to receive additional measurements of a certain user among the non-symptomatic users, taken with a wearable device after the current measurements of the certain user were taken, calculate an additional health score of the certain user based on differences between the additional measurements of the certain user and baseline measurements of the certain user, detect that the additional health score does not reach the threshold, and notify the certain user that he/she not allowed on the premises.
  • the computer is further configured to identify a second subset of the users as symptomatic users based on their health scores not reaching the threshold, and notify the symptomatic users, prior to their respective arrival times, that they are not allowed on the premises. 4.
  • the system of claim 3, wherein the computer is further configured to certify the premises as contagion-safe responsive to receiving an indication that none of the symptomatic users entered the premises during a predetermined period.
  • the premises is an airplane
  • the intended arrival time is a boarding time to the airplane
  • the computer is further configured to direct the non-symptomatic users and people who were not identified as non-symptomatic users to different airplanes. 6.
  • the wearable devices further comprise acoustic sensors configured to take audio recordings of the users; and the computer is further configured to calculate the health scores also based on extent of coughing recognizable in the audio recordings; wherein a health score of a user is proportional to a difference between an extent of coughing recognizable in current audio recordings of the user and an extent of coughing recognizable in baseline audio recordings of the user taken at least one day earlier.
  • calculation of a health score of a user by the computer comprises: calculating, based on the baseline measurements of the user, an expected value of a physiological signal of the user; calculating, based on the current measurements of the user, a current value of the physiological signal; and calculating the health score based on a difference between the expected value and the current value.
  • the physiological signal is body temperature
  • the calculating of the health score of the user utilizes a function that sets the health score to a value below the threshold when a current body temperature is greater than an expected body temperature by at least a certain margin; and wherein the certain margin is at least 0.4°C.
  • calculating the current value of the physiological signal by the computer comprises: generating feature values based on the current measurements, and utilizing a model to calculate, based on the feature values, the current value of the physiological signal; and wherein the model was generated from training data comprising: previous measurements of the user taken with a wearable device, and values of the physiological signal obtained utilizing a sensor that was not part of the wearable device. 11.
  • a method for managing access to a contagion-safe premises comprising: receiving measurements of users, measured with wearable devices, comprising photoplethysmogram signals and temperature signals; calculating, for each user from among the users, a health score of the user based on a difference between current measurements of the user and baseline measurements of the user; wherein the current measurements of the user were measured with a wearable device up to 4 hours before an intended arrival time of the user to a premises, and baseline measurements of the user were measured with the wearable device at least 10 hours before the intended arrival time of the user; identifying a subset of the users as non -symptomatic users based on their health scores reaching a threshold; authenticating identities of the non-symptomatic users based on at least some of their current physiological signals; and notifying the non-symptomatic users, prior to their respective intended arrival times, that they are allowed on the premises.
  • the method of claim 12 further comprising: identifying a second subset of the users as symptomatic users based on their health scores not reaching the threshold, and notifying the symptomatic users, prior to their respective arrival times, that they are not allowed on the premises. 15.
  • the premises is an airplane, the intended arrival time is a boarding time to the airplane, and further comprising placing the users in the airplane according to cohorts, such that >75% of passengers who sit in proximity of up to two rows from and people who were not identified as non-symptomatic users are also people who were not identified as non-symptomatic users, and >75% of passengers who sit in proximity of up to two rows from the non-symptomatic users are non-symptomatic users. 18.
  • the physiological signal is body temperature
  • the calculating of the health score of the user utilizes a function that sets the health score to a value below the threshold when a current body temperature is greater than an expected body temperature by at least a certain margin; and wherein the certain margin is at least 0.4°C. 20.
  • a non-transitory computer readable medium storing one or more computer programs configured to cause a processor based system to execute steps comprising: receiving measurements of users, measured with wearable devices, comprising photoplethysmogram signals and temperature signals; calculating, for each user from among the users, a health score of the user based on a difference between current measurements of the user and baseline measurements of the user; wherein the current measurements of the user were measured with a wearable device up to 4 hours before an intended arrival time of the user to a premises, and baseline measurements of the user were measured with the wearable device at least 10 hours before the intended arrival time of the user; identifying a subset of the users as non-symptomatic users based on their health scores reaching a threshold; authenticating identities of the non-symptomatic users based on at least some of their current physiological signals; and notifying the non-symptomatic users, prior to their respective intended arrival times, that they are allowed on the premises.
  • these paragraphs illustrate various inward-facing head-mounted cameras coupled to an eyeglasses frame, illustrate cameras that capture regions on the periorbital areas, illustrate an optional computer that may include a processor, memory, a battery and/or a communication module, illustrate inward-facing head-mounted cameras coupled to an augmented reality devices, illustrate head-mounted cameras coupled to a virtual reality device, illustrate head-mounted cameras coupled to a sunglasses frame, illustrate cameras configured to capture various regions, such as the forehead, the upper lip, the cheeks, and sides of the nose, illustrate inward-facing head-mounted cameras mounted to protruding arms, illustrate various inward-facing head-mounted cameras having multi-pixel sensors (FPA sensors) configured to capture various regions, illustrate head-mounted cameras that are physically coupled to a frame using a clip-on device configured to be attached/detached from a pair of eyeglasses in order to secure/release the device to/from the eyeglasses, illustrate a clip-on device holds at least an inward-facing camera, a processor, a battery,
  • a camera represents one or more cameras, where each camera may have the same field of view (FOV) and/or different FOVs.
  • a camera includes multiple sensing elements, and the illustrated region captured by the camera usually refers to the total region captured by the camera, which is made of multiple regions that are respectively captured by the different sensing elements.
  • the positions of the cameras in the figures are just for illustration, and the cameras may be placed at other positions.
  • HMS head-mounted system
  • the HMS may include a battery, a computer, sensors, and a transceiver.
  • FIG. 14A and FIG. 14B are schematic illustrations of possible embodiments for computers (400, 410) that are able to realize one or more of the embodiments discussed herein that include a “computer”.
  • the computer (400, 410) may be implemented in various ways, such as, but not limited to, a microcontroller, a computer on a chip, a system-on-chip (SoC), a system-on-module (SoM), a processor with its required peripherals, a server computer, and/or any other computer form capable of executing a set of computer instructions.
  • references to a computer or a processor include any collection of one or more computers and/or processors (which may be at different locations) that individually or jointly execute one or more sets of computer instructions.
  • a computer is intended to imply one or more computers, which jointly perform the functions attributed to “the computer”.
  • some functions attributed to the computer may be performed by a computer on a wearable device (e.g., smartglasses) and/or a computer of the user (e.g., smartphone), while other functions may be performed on a remote computer, such as a cloud-based server.
  • the computer 400 includes one or more of the following components: processor 401, memory 402, computer readable medium 403, user interface 404, communication interface 405, and bus 406.
  • the computer 410 includes one or more of the following components: processor 411, memory 412, and communication interface 413.
  • Computer-readable media may include computer-readable storage media, which corresponds to a tangible medium such as data storage media, and/or communication media including any medium that facilitates transfer of a computer program from one place to another.
  • Computer-readable medium may be any media that can be accessed by one or more computers to retrieve instructions, code, data, and/or data structures for implementation of the described embodiments.
  • a computer program product may include a computer -readable medium.
  • the computer-readable medium 403 may include one or more of the following: RAM, ROM, EEPROM, optical storage, magnetic storage, biologic storage, flash memory, or any other medium that can store computer readable data.
  • a computer program (also known as a program, software, software application, script, program code, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages.
  • the program can be deployed in any form, including as a standalone program or as a module, component, subroutine, object, or another unit suitable for use in a computing environment.
  • a computer program may correspond to a file in a file system, may be stored in a portion of a file that holds other programs or data, and/or may be stored in one or more files that may be dedicated to the program.
  • a computer program may be deployed to be executed on one or more computers that are located at one or more sites that may be interconnected by a communication network.
  • Computer-readable medium may include a single medium and/or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store one or more sets of instructions.
  • a computer program, and/or portions of a computer program may be stored on a non-transitory computer-readable medium, and may be updated and/or downloaded via a communication network, such as the Internet.
  • the computer program may be downloaded from a central repository, such as Apple App Store and/or Google Play.
  • the computer program may be downloaded from a repository, such as an open source and/or community run repository (e.g., GitHub).
  • At least some of the methods described herein are “computer-implemented methods” that are implemented on a computer, such as the computer (400, 410), by executing instructions on the processor (401, 411). Additionally, at least some of these instructions may be stored on a non-transitory computer- readable medium.
  • references to "one embodiment” mean that the feature being referred to may be included in at least one embodiment of the invention.
  • Separate references to embodiments may refer to the same embodiment, may illustrate different aspects of an embodiment, and/or may refer to different embodiments.
  • Sentences in the form of “X is indicative of Y” mean that X includes information correlated with Y, up to the case where X equals Y.
  • Sentences in the form of “provide/receive an indication (of whether X happened)” may refer to any indication method.
  • the word “most” of something is defined as above 51% of the something (including 100% of the something). Both a “portion” of something and a “region” of something refer to a value between a fraction of the something and 100% of the something.
  • the word “region” refers to an open-ended claim language, and a camera said to capture a specific region on the face may capture just a small part of the specific region, the entire specific region, and/or a portion of the specific region together with additional region(s).
  • the phrase “based on” indicates an open-ended claim language, and is to be interpreted as “based, at least in part, on”.
  • Variations of the terms “utilize” and “use” indicate an open-ended claim language, such that sentences in the form of “detecting X utilizing Y” are intended to mean “detecting X utilizing at least Y”, and sentences in the form of “use X to calculate Y” are intended to mean “calculate Y based on X”.
  • a predetermined value is a fixed value and/or a value determined any time before performing a calculation that utilizes the predetermined value.
  • the word “value” may indicate a “predetermined value”.
  • the word “threshold” indicates a “predetermined threshold”, which means that the value of the threshold, and/or the logic used to determine whether the threshold is reached, is known before start performing computations to determine whether the threshold is reached.
  • the embodiments of the invention may include any variety of combinations and/or integrations of the features of the embodiments described herein. Although some embodiments may depict serial operations, the embodiments may perform certain operations in parallel and/or in different orders from those depicted. Moreover, the use of repeated reference numerals and/or letters in the text and/or drawings is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. The embodiments are not limited in their applications to the order of steps of the methods, or to details of implementation of the devices, set in the description, drawings, or examples. Moreover, individual blocks illustrated in the figures may be functional in nature and therefore may not necessarily correspond to discrete hardware elements.

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Abstract

Certains aspects de la présente divulgation impliquent le recours à des technologies portées sur soi, telles que des lunettes intelligentes à capteurs intégrés, afin de surveiller la santé des utilisateurs et gérer l'accès à des lieux d'une manière sûre pouvant réduire le risque de propager des maladies telles que la grippe ou la COVID-19.
PCT/IB2021/054072 2020-05-13 2021-05-12 Recours à des vérifications d'état de santé fondées sur des technologies portées sur soi afin d'enrayer la propagation d'épidémies WO2021229477A1 (fr)

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US202063024471P 2020-05-13 2020-05-13
US63/024,471 2020-05-13
US202063048638P 2020-07-06 2020-07-06
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US202063113846P 2020-11-14 2020-11-14
US63/113,846 2020-11-14
US202063122961P 2020-12-09 2020-12-09
US63/122,961 2020-12-09
US202163140453P 2021-01-22 2021-01-22
US63/140,453 2021-01-22

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