WO2021188999A2 - Health monitoring system for limiting the spread of an infection in an organization - Google Patents

Health monitoring system for limiting the spread of an infection in an organization Download PDF

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Publication number
WO2021188999A2
WO2021188999A2 PCT/US2021/023323 US2021023323W WO2021188999A2 WO 2021188999 A2 WO2021188999 A2 WO 2021188999A2 US 2021023323 W US2021023323 W US 2021023323W WO 2021188999 A2 WO2021188999 A2 WO 2021188999A2
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WO
WIPO (PCT)
Prior art keywords
user
wearable device
users
proximity
computing device
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Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2021/023323
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English (en)
French (fr)
Other versions
WO2021188999A3 (en
Inventor
Jerome J. NOVAK JR.
Omar Ahmed
Ammar Al-Ali
Kostas MICHALOPOULOS
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Masimo Corp
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Masimo Corp
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Publication of WO2021188999A2 publication Critical patent/WO2021188999A2/en
Publication of WO2021188999A3 publication Critical patent/WO2021188999A3/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Definitions

  • wearable devices that can detect proximity to other, separate wearable devices which may be associated with other users, thereby enabling, in turn, determinations of proximity between various users, for example, in an organization, over one or more time periods.
  • Various systems, devices, and methods are disclosed which enable a computing device (e.g., a mobile computing device such as a smart phone) to receive one or more physiological parameters associated with a user from one or more wearable devices coupled with the user and/or receive proximity data indicative of the user’ s proximity to one or more other users, for example, over a given time period (e.g., 3 days, 5 days, 7 days, 10 days, 14 days, etc.).
  • such computing device can act as a hub (for example, a network and/or communication point) and can transmit information received from the one or more wearable devices to a remote monitoring system (for example, over a network), which can be located at, accessible by, and/or otherwise associated with an organization and/or a monitor user who is tasked with monitoring and/or taking action with respect to the remote monitoring system.
  • a hub for example, a network and/or communication point
  • a remote monitoring system for example, over a network
  • Such organization can be, for example, a company, a school, a hospital, a sports or concert venue, etc.
  • the remote monitoring system can receive information from such computing device associated with a user along with similar information from a plurality of other computing devices associated with a plurality of other users (for example, users associated with the organization) and can monitor such information for the purpose of limiting transmission and/or contraction of one or more infections.
  • such remote monitoring system can be utilized and/or monitored by a “monitor user” associated with an organization.
  • the remote monitoring system can allow an organization to not only monitor health statuses and/or contact tracing information regarding users, but also provide instructions (automatically and/or manually) and/or information (e.g., exposure levels, risk states, etc.) to such users via associated computing devices.
  • the remote monitoring system can allow an organization to dynamically and simultaneously monitor and manage health statuses of its employees to limit the spread of various infections, and relatedly, allow the organization to safely carry out its purpose (e.g., conduct business, manufacture products, care for patients, provide educational services, provide services, etc.).
  • a system for remotely monitoring and managing health statuses of a plurality of users of an organization to limit a spread of an infection can comprise software instructions storable on a memory device usable by a computing device.
  • said contact tracing data can comprise information indicative of: physical proximity of the one of the plurality of users to said at least one other one of the plurality of users, said physical proximity can be determined based on a detected wireless signal strength between a first wearable device of the one of the plurality of users and a second wearable device of the at least one other one of the plurality of users when the first and second wearable devices are worn. In some aspects, said physical proximity can be determined based on a detected Bluetooth ® signal strength between the first and second wearable devices.
  • said software instructions can further cause said hardware processor of the computing device to determine: an accumulated duration, over a first time period, that said physical proximity between said one of the plurality of users and each other one of the plurality of users confirmed to have said infection is within a threshold proximity; and said exposure level for the one of the plurality of users based on a summation of all of said accumulated durations.
  • said exposure level can be determined based on at least one of an average of said summation of all of said accumulated durations and a maximum of said summation of all of said accumulated durations.
  • a wearable device for monitoring risk of spreading a contagious infection in an organization can comprise: a temperature sensor configured to generate one or more signals responsive to a thermal energy of a first user; a wireless transceiver configured to communicate with a mobile computing device of the first user; and a processor.
  • the processor can be configured to: receive said one or more signals generated by the temperature sensor and determine one or more body temperature values of the first user; and instruct the wireless transceiver to transmit, to the mobile computing device, said one or more body temperature values; determine one or more proximity values indicative of distance between the wearable device and a separate wearable device that is coupled to a second user.
  • the wearable device does not include any other physiological sensors.
  • the wearable device can further comprise a housing configured to at least partially enclose the temperature sensor, wireless transceiver, and processor.
  • the wearable device can further comprise one or more substrates configured to secure the wearable device to skin of the first user.
  • the processor can be configured to determine said one or more proximity values when the wearable device and the separate wearable device are within a threshold proximity to one another.
  • said threshold proximity can comprise about 20 ft.
  • the processor can be configured to determine said one or more proximity values based on a detected wireless signal strength between said wearable device and said separate wearable device.
  • a system can comprise the wearable device of any one of the preceding paragraphs and said mobile computing device.
  • said wireless transceiver of said wearable device can be configured to transmit said one or more body temperature values, said first identifier, said second identifier, and said one or more proximity values to said mobile computing device via a first wireless communication protocol
  • said mobile computing device can be configured to wirelessly transmit said first identifier, said second identifier, said one or more proximity values, and said one or more body temperature values to said remote monitoring system via a second wireless communication protocol that can be different than said first wireless communication protocol.
  • said one or more physiological parameters can comprise one or more body temperature values of the first user
  • said mobile software application can be configured to execute commands to enable the mobile computing device to wirelessly receive, from the wearable device, said one or more body temperature values at a first time interval.
  • said mobile software application can be configured to execute commands to enable the mobile computing device to wirelessly transmit said one or more body temperature values of said first user, said first identifier, said second identifier, and said determined one or more proximity values at said first time interval.
  • said first time interval can comprise every minute.
  • said mobile software application can be configured to execute commands to enable the mobile computing device to wirelessly transmit, to the remote monitoring system, information indicative of a test result of the first user associated with said infection and inputted by the first user via the mobile software application.
  • said mobile software application can be configured to execute commands to enable the mobile computing device to wirelessly transmit, to the remote monitoring system, information indicative of one or more symptoms of the first user associated with said infection and inputted by the first user via the mobile software application.
  • said wearable device can be configured to detect only one type of physiological parameter of the first user, said one type of physiological parameter being body temperature.
  • said threshold proximity can be about 30 ft.
  • the mobile software application can be configured to execute commands to enable the mobile computing device to: wirelessly receive, from the wearable device when said proximity is within a first threshold, a first identifier associated with the first user of the wearable device and a second identifier associated with the second user of the separate wearable device; wirelessly transmit said first identifier and said second identifier to a remote monitoring system when said proximity is within the first threshold; wirelessly receive, from the remote monitoring system, a notification configured to alert the first user of at least one of an exposure of the first user to said infection and a risk state of the first user, said risk state associated with a likelihood that said first user has said infection; generate a graphical user interface on a display of the mobile computing device; and display, in at least a portion of the graphical user interface, at least one of said notification received from said remote monitoring system and a visual representation associated with said notification.
  • said displaying, on said at least said portion of the graphical user interface comprises displaying said risk state and an instruction associated with said risk state. In some aspects, said displaying, on said at least said portion of the graphical user interface further comprises displaying said visual or audio representation of said risk state.
  • said one or more physiological parameters of the first user comprise one or more body temperature values. In some aspects, said one or more physiological parameters comprise only one type of physiological parameter, said one type of physiological parameter being body temperature.
  • said operations can further comprise: receiving said one or more physiological parameters, said proximity data, and said first identifier from the first wearable device over a first wireless communication protocol; and transmitting said first identifier, said second identifier, said one or more physiological parameters, and said proximity data to the remote monitoring system over a second wireless communication protocol, said second wireless communication protocol being different than said first wireless communication protocol.
  • the processor can be configured to: receive said one or more signals generated by the temperature sensor and determine one or more body temperature values of the first user based on said received one or more signals; instruct the first wireless transceiver to transmit to the mobile computing device, at a first time interval, said determined one or more body temperature values; and determine one or more proximity values indicative of distance between the first wireless transceiver and a second wireless transceiver of a separate wearable device that is coupled to a second user when said first and second wireless transceivers are within a threshold proximity to one another, said one or more proximity values can be determined based on a detected wireless signal strength between the first and second wireless transceivers.
  • the wearable device can be configured to determine only one type of physiological parameter of the first user, said type of physiological parameter being temperature of the first user.
  • the wearable device can further comprise one or more substrates configured to secure the wearable device to skin of the first user.
  • said threshold proximity can comprise about 20 ft. In some aspects, said threshold proximity can comprise about 30 ft.
  • the processor can be configured to instruct the first wireless transceiver to transmit, to the mobile computing device, said first identifier and said one or more proximity values only when said first and second wireless transceivers are within said threshold proximity, and the processor can be configured to instruct the first wireless transceiver to transmit, to the mobile computing device, said one or more body temperature values continuously at said first time interval regardless of whether said first and second wireless transceivers are within said threshold proximity.
  • said first time interval can comprise every minute.
  • the wearable device can further comprise a battery. In some aspects, the wearable device can further comprise a housing configured to be coupled to the first user. In some aspects, said one or more proximity values can be determined based on a detected Bluetooth ® signal strength between the first and second wireless transceivers.
  • said at least one physiological sensor can comprise a temperature sensor configured to generate one or more signals responsive to a thermal energy of the first user
  • said processor can be further configured to: receive said one or more signals generated by the temperature sensor and determine one or more body temperature values of the first user based on said received one or more signals; instruct the first wireless transceiver to transmit said determined one or more body temperature values to the mobile computing device at a first time interval; and determine one or more proximity values based on a detected wireless signal strength between the first and second wireless transceivers.
  • said software instructions can further cause one or more hardware processors of the computing device to: determine an accumulated duration, over a second time period, that said proximity between the first and third ones of the plurality of users is within the threshold proximity; and determine said exposure level for the first one of the plurality of users based on said contact tracing data, said accumulated durations, and a risk state of the third one of the plurality of users associated with a likelihood that said third one of the plurality of users had said one or more infections during at least a portion of said second time period.
  • wearable devices 104, 114 can be configured to secure to various locations of a user’s body including, but not limited to, chest, torso, back, shoulder, arms, legs, neck, or head.
  • Various means can be used to attach the wearable devices 104, 114 to a user.
  • the wearable devices 104, 114 can be secured to the skin of a user with an adhesive.
  • the wearable devices 104, 114 can be attached to a user with a fastener, such as tape, laid over at least a portion of the wearable devices 104, 114.
  • the wearable devices 104, 114 can be attached to a user via one or more straps.
  • wearable device 200 can include any of processor 302, storage device 304, wireless transceiver 306, power source 308, information element 310, physiological sensor(s) 312, and/or other sensor(s) 314 discussed below with respect to Figure 2J.
  • Any of the processor, storage device, wireless transceiver, battery, information element, and/or one or more temperature sensors of wearable device 200 can be mounted and/or coupled with a circuit layer of the wearable device 200, such as a circuit board 205 of the wearable device 200, which can be enclosed or at least partially enclosed by the housing 202 (and/or a portion of the housing 202) and/or one or more substrates 204a, 204b, 204c, 204d, 204e, 204f.
  • wearable device 200 is configured to determine only one type of physiological parameter, for example, body temperature. In such configurations, a battery life of the wearable device 200 can be maximized.
  • the wearable device 200 can include one or more temperature sensors, and such one or temperature sensors can be or include, a thermocouple and/or a thermistor, for example.
  • a thermocouple can produce a voltage when the contact spot differs from a reference temperature. Thermocouples may be self-powered and therefore may not require an external power source for operation.
  • a thermistor is a type of resistor whose resistance value can vary depending on its temperature. Thermistors typically offer a high degree of precision within a limited temperature range.
  • the one or more temperature sensors of the wearable device 200 can be a chip that is electrically and mechanically coupled with the circuit board 205.
  • FIG. 2E illustrates another example wearable device 230.
  • Wearable device 230 can be, for example, a smartwatch configured to measure and/or monitor one or more physiological parameters of a user (e.g., oxygen saturation, pulse rate, heart rate) and/or other information of a user (e.g., location and/or movement data determined from accelerometer(s), gyroscope(s), magenetometer(s) of the smartwatch).
  • wearable device 230 can be configured to detect proximity to other wearable devices that may be associated with (e.g., attached to) other users, in a similar or identical manner as that discussed elsewhere herein.
  • Wearable device 230 can wirelessly transmit such data to a computing device 206.
  • FIG. 2F illustrates another example wearable device 240.
  • Wearable device 240 can be a fingertip pulse oximeter, for example, the MightySat® Rx Fingertip Pulse Oximeter by Masimo Corporation, Irvine, CA.
  • Wearable device 240 can be configured to wirelessly communicate one or more physiological parameters of the user (e.g., oxygen saturation, pulse rate, heart rate) to the user computing device 206.
  • physiological parameters of the user e.g., oxygen saturation, pulse rate, heart rate
  • any of the wearable devices discussed herein can be similar or identical to any of the devices for measuring and/or monitoring one or more physiological parameters disclosed in U.S. Pat. Pub. No. 2020/0329993, published on October 22, 2020, titled “ELECTROCARDIOGRAM DEVICE,” which is hereby incorporated by reference in its entirety.
  • FIGS 3A-3B illustrate a first wearable device 200 coupled to a user 102 and a second wearable device 200’ coupled to another user 112.
  • Wearable device 200’ can be identical to wearable 200 or alternatively, can be different (for example, can be the same as any other wearable device discussed herein).
  • Wearable device 200, 200’ can secure to a portion of a user’s body, such as a torso, chest, back, arm, neck, leg, among other portions of the user’s body.
  • multiple different, similar, or same wearable devices can be removably secured to virtually any one or more portions of the users’ bodies.
  • Such signal(s) can be communicated over one or more, or a plurality of wireless communication protocols, including but not limited to Wi-Fi (802.1 lx), Bluetooth ® , ZigBee ® , Z-wave ® , cellular telephony, infrared, RFID, satellite transmission, proprietary protocols, near-field communication (NFC), combinations of the same, and the like.
  • Such proximity threshold can be, for example, 200 ft, 100 ft, 80 ft, 70 ft, 60 ft, 50 ft, 40 ft, 30 ft, 20 ft, 15 ft, 10 ft, 9 ft, 8 ft, 7 ft, 6 ft, 5 ft, 4 ft, 3 ft, 2 ft, 1 ft, or any value between any of these values, or any range bounded by any combination of these values, although values outside these values or ranges can be used in some cases.
  • Figures 3A-3B illustrate just wearable device 200, 200’ coupled to a user 102, 112
  • various other numbers and/or types of wearable devices can be coupled to a user 102, 112 at once and can be configured to communicate with other wearable devices on the same user 102, 112 and/or other wearable devices coupled to other users.
  • remote monitoring system 120 can be configured to communicate with (for example, receive data from and/or transmit data to) any number of user computing devices 106, 116, connectivity hubs 108, 118, and/or wearable devices 104, 114 associated with any number of users 102, 112.
  • remote monitoring system 120 can advantageously be used by an organization (e.g., business, school, hospital), and/or a user thereof (for example, a “monitor user” of the organization), to monitor and/or manage health statuses of users 102, 112 associated with the organization in order to limit the spread of an infectious disease or otherwise monitor the health of such users 102, 112.
  • the remote monitoring system 120 can be utilized by an organization to facilitate clearance of one or more users for an event or gathering (e.g., by a sports or concert venue).
  • FIG. 4 illustrates exemplary components any or all of which can be incorporated into remote monitoring system 120.
  • the remote monitoring system 120 can include several subsystems and/or modules that can be implemented in hardware and/or software.
  • the example modules or components shown may group functionality of examples of the remote monitoring system 120 together under logical descriptions. It should be understood, however, that the various modules and systems shown in the remote monitoring system 120 or portions thereof could be implemented together in a single system. In addition, not all of the systems or modules shown need be implemented on the same computing device but could instead be implemented in separate computing devices. Further, some of the modules shown may be omitted in various examples.
  • the computing resources may include hardware computing, networking and/or storage devices configured with specifically configured computer-executable instructions. Hosted computing environments can be referred to as “cloud computing” environments.
  • the remote monitoring system 120 can be utilized and/or accessed by one or more computing devices, for example, by a monitor user of the organization via an application (e.g., web and/or mobile) usable on a computing device (e.g., desktop, laptop, smartphone, tablet).
  • an application e.g., web and/or mobile
  • monitoring portal 406 of the remote monitoring system 120 can provide a user interface that can be accessed by a monitor user of the organization.
  • monitor user can be a user or users affiliated with the organization who are tasked with monitoring and/or managing aspects of the remote monitoring system 120, for example, monitoring health-related information associated with user of the organization, viewing and/or modifying exposure levels and/or risk states of the users in the organization, sending notifications and/or instructions to users in the organization, among other things.
  • the monitoring portal 406 may, for example, be implemented in one or more web pages, mobile applications, or other network applications and may provide information including and/or associated with the information received from the user computing devices 106, 116, connectivity hubs 108, 118, and/or wearable devices 102, 112.
  • the monitoring portal 406 can display health-related information, exposure levels, and/or risk states of one or more users, each of which are discussed in more detail elsewhere herein.
  • Example health-related information can be any of that discussed herein, including, without limitation: physiological information of one or more users; information related to proximity of the user to one or more (or a plurality of) other users (for example, for determination of contact tracing and/or exposure to potential infections and/or diseases); information and/or data related to a user’s diagnosis and/or test result(s) with respect to one or more infections and/or diseases (e.g., positive and/or negative test results, diagnosis obtained from a medical professional); and information and/or data related to symptom(s) experienced by the user (which can be input by the user into a computing device operated by a user, for example).
  • physiological information of one or more users information related to proximity of the user to one or more (or a plurality of) other users (for example, for determination of contact tracing and/or exposure to potential infections and/or diseases); information and/or data related to a user’s diagnosis and/or test result(s) with respect to one or more infections and/or diseases (e.g.
  • the contact tracing engine 416 and/or risk engine 418 can receive such other information that may be related to such proximity data from one or more user computing devices 106, 116, connectivity hubs 108, 118, and/or wearable devices 104, 114.
  • the contact tracing engine 416 which is described in more detail further below, can keep track of locations and/or interactions of any of the plurality of users in the organization and determine potential exposure(s) that any of such users had to users who may be infected with an infectious disease (e.g., COVID-19) over a period of time.
  • an infectious disease e.g., COVID-19
  • the contact tracing engine 416 can advantageously allow the remote monitoring system 120 to send notifications and/or instructions to any user in the organization related to determinations made by the contact tracing engine 416 and/or risk engine 418, such as notifications that a particular user was within a threshold proximity (e.g., 100 ft, 50 ft, 20 ft, 6ft) of a user during some time period who was confirmed for an infectious disease, for example, within that same time period.
  • a threshold proximity e.g., 100 ft, 50 ft, 20 ft, 6ft
  • the risk engine 418 can be configured to calculate a risk state (which also be referred to herein as a “risk level”) associated with any or all of the users of an organization associated with the remote monitoring system 120.
  • risk state can be representative of and/or indicative of a user’ s risk or likelihood of having one or more infections.
  • the risk engine 418 can determine if a user falls under one of four risk categories that is associated with the user’s likelihood of being infected with a disease or illness, for example, COVID-19.
  • Such information transmitted to the one or more of the plurality of user computing devices 106, 116 can include, among other things, a risk state of a user associated with the user computing device 106, 116, instructions that may be related to such risk state (e.g., instructions to avoid coming into the organization’s facilities or to quarantine a certain amount of time), and/or notifications such as exposure to other users who may be confirmed as having a particular infection.
  • a risk state of a user associated with the user computing device 106, 116 can include, among other things, a risk state of a user associated with the user computing device 106, 116, instructions that may be related to such risk state (e.g., instructions to avoid coming into the organization’s facilities or to quarantine a certain amount of time), and/or notifications such as exposure to other users who may be confirmed as having a particular infection.
  • Figure 5B illustrates exemplary risk states that can be determined and/or transmitted by the remote monitoring system 120 to user computing devices 206 associated with users. While Figure 5 illustrates mobile phones (smart phones) as user computing devices 206, any other type of computing device can be used as discussed elsewhere herein. Accordingly, the discussion below with respect to risk states being sent to and/or displayed on user computing devices 206 is equally applicable to any of the user computing devices discussed herein.
  • risk states determined and transmitted by the remote monitoring system 120 to the user computing devices 206 can be: “Clean” or “Negative” or “No risk” which can represent that a user does not have and/or is not at risk for having a particular infection and/or that the user is at no or low risk to infect others with the infection; “Suspected without signs or symptoms” which can represent that a user is suspected to have a particular infection (for example, based on contact tracing data in relation to other users who may be positive for the infection) but does not appear to currently have symptoms that may be associated with the particular infection; “suspected with signs or symptoms” which can represent that a user is suspected to have a particular infection (for example, based on contact tracing data in relation to other users who may be positive for the infection) and has one or more symptoms that may be associated with the particular infection; and/or “Confirmed” or “Positive” which can represent that a user does have a particular infection.
  • risk states can be determined by the remote monitoring system 120 (for example, via the risk engine 418) based on one or more of physiological data, contact tracing data, diagnosis and/or test result data, and/or symptom(s) data, each of which are discussed elsewhere herein.
  • the remote monitoring system 120 can send such risk state(s) and/or instructions or notifications associated with such risk states to user computing devices 106, 116.
  • the user computing devices 106, 116 can be configured to display, for example, on a display thereof, the risk states and/or instructions or notifications associated with such risk states.
  • the user computing devices 206 can illuminate, for example, a portion or an entirety of a graphical user interface on a display thereof, a certain color which can be associated with said risk states.
  • User computing device 106, 116 can communicate with an electronic device different than such exemplary nametag discussed above in a similar manner.
  • use computing device 106, 116 can communicate information and/or instructions associated with such risk states to an electronic screening device such as a handheld wand or walkthrough screening device which can have similar electronic components and/or functionality as that discussed above with reference to the nametag.
  • an electronic screening device such as a handheld wand or walkthrough screening device which can have similar electronic components and/or functionality as that discussed above with reference to the nametag.
  • Such handheld wand or walkthrough screening device can be configured to notify a screener (for example, a person associated with the organization) of a user’s risk state.
  • the user computing device 106, 116 can instruct the handheld wand or walkthrough screening device to illuminate the color associated to the user’s risk state (such as “green”, “yellow”, “orange”, or “red” as discussed above with reference to the described risk states).
  • the color associated to the user such as “green”, “yellow”, “orange”, or “red” as discussed above with reference to the described risk states.
  • contact tracing data, diagnosis or test result data, and/or symptoms information can be received by the remote monitoring system 120 from the user computing devices 102, 112 and/or the wearable devices 104, 114and can be utilized to determine risk state(s).
  • the remote monitoring system 120 may automatically determine that a user is in the orange category based on high-level of exposure to a user who was determined to be in the red category and/or the user experiencing symptoms of the infection.
  • Figures 6A-6B also illustrate how signs or symptoms can be used by the risk engine 418 to adjust a risk state (see “S&S” in Figure 6A).
  • Such automatic determination by the remote monitoring system 120 allows for efficient and continuous monitoring and/or management of up to a vast amount of users and brings significant improvements to conventional approaches at limiting a spread of an infection at an organization.
  • an authorized user of the organization can request a report of all the individual risk states of the users associated with the organization.
  • an employer who owns a warehouse may want to monitor the employees’ individual risks of being infected with COVID-19.
  • the remote monitoring system 120 can be utilized to produce a report for the employer, which shows the risk state for each of the employees.
  • wearable device 200 can be configured to detect proximity to one or more other wearable devices coupled to one or more other users.
  • wearable device 200 can be configured to detect proximity form wearable device 200’ and/or 200” simultaneously or non-simultaneously, based on detected signal strength between the devices 200’ , 200” and the wearable device 200.
  • the wearable device 200 can wirelessly communicate with wearable devices 200’, 200” over any wireless communication protocol such as those discussed herein and signals transmitted and/or received over such protocols can be used for such proximity detection.
  • wearable device 200 can be configured to receive and/or transmit identifier(s) between wearable devices 200’, 200’ which can be associated with the users 112, 112’.
  • Such information is advantageous as it allows the wearable device 200, and an associated user computing device 106, to keep track of each user that comes into proximity with user 102 over various time periods, as well as keeping track of actual proximity values (e.g., distances).
  • wearable device 200 can detect proximity values when the wearable devices 200’, 200” are within some threshold proximity, as discussed above (e.g., within 200 ft, 100 ft, 50 ft, 30 ft, 20 ft, 15 ft, 10ft, 6 ft, 3 ft etc.) and can transmit such information to the user computing device 106 at various time intervals (e.g., every second, every 3 seconds, every 5 seconds, every 30 seconds, every minute, every 2 minutes, every 5 minutes, every 10 minutes, every 30 minutes, every hour, etc.).
  • time intervals e.g., every second, every 3 seconds, every 5 seconds, every 30 seconds, every minute, every 2 minutes, every 5 minutes, every 10 minutes, every 30 minutes, every hour, etc.
  • wearable device 200, user computing device 106, and/or remote monitoring system 120 categorizes a user’s 102 proximity to one or more other users (such as user 112, 112’). For example, in some implementations, wearable device 200, user computing device 106, and/or remote monitoring system 120 categorizes a user’ s proximity to user 112, 112’ as “far”, “medium”, and/or “close” based on one or more proximity values determined between the wearable devices 200, 200’ , 200” , as illustrated in Figure 7B.
  • the “far” category can be between about 20 ft and about 200 ft, between about 20 feet and about 100 feet, between about 20 feet and about 50 feet, between about 30 ft and about 200 ft, between about 30 feet and about 100 feet, between about 30 feet and about 50 feet, or any number within these ranges or bounded by any range including any value within these ranges.
  • the “close” category can between about 6 inches and about 20 ft, between about 1 ft and about 20 ft, between about 1 ft and about 15 ft, between about 1 ft and about 10 ft, between about 1 ft and about 6 ft, within 20 ft, within 15 ft, within 10 ft, within 6 ft, within 3 ft, or any number within these ranges or bounded by any range including any value within these ranges.
  • the user computing device 106 and/or the remote monitoring system 120 can categorize a contact event of any two users as a “medium time period” or “medium exposure” if such users were within a threshold proximity for between about 5 minutes and 30 minutes, between about 10 minutes and 25 minutes, between about 10 minutes and 20 minutes, between about 10 minutes and 1 hour, or any value therebetween or any range bounded by any value therebetween.
  • the user computing device 106 and/or the remote monitoring system 120 can categorize a contact event of any two users as a “long time period” or “long exposure” if such users were within a threshold proximity for greater than or equal to 10 minutes, greater than or equal to 15 minutes, greater than or equal to 20 minutes, greater than or equal to 25 minutes, greater than or equal to 30 minutes, greater than or equal to 40 minutes, greater than or equal to 50 minutes, greater than or equal to 1 hour, between about 15 minutes and about 1 hour, between about 30 minutes and about 5 hours, between about 30 minutes and about 2 hours, among other values and/or ranges.
  • Remote monitoring system 120 (for example, via contact tracing engine 416 or risk engine 418) can be configured to determine a variety of metrics related to a user’s exposure level to various other users (for example, associated with an organization) who may be or are infected with a communicable infection based on the above-described contact tracing data.
  • a user’s exposure level can include any information and/or data that may be associated with, representative of, and/or indicative of a user’s exposure to one or more other users who may or may not be infected with a particular infection.
  • Remote monitoring system 120 can dynamically store, for each user associated with an organization, contact tracing data such as that described herein along with other health-related and other information, over time.
  • Such contact tracing data can be indicative of all of the exposure (e.g., contact events) for each user, proximity data indicative of the distance(s) between each user and other users, and/or duration of time of each contact event and/or accumulated duration of contact time over a given time period (e.g., 3 days, 5 days, 7 days, 10 days, 14 days, etc.).
  • weight factors can be applied to contact events depending on the associated proximity(ies) values of such contact events and/or the duration of such contact events.
  • the remote monitoring system 120 can determine total number of users (in the organization) with confirmed infections and/or a ratio of confirmed infections over the total number of users.
  • a user’s exposure level can be determined based on (and/or can be indicative of) a summation, over a given time period (e.g., 3 days, 5 days, 7 days, 10 days, 14 days) of the time for each and every contact event with a user who was confirmed for the infection (e.g., in the “red” category described above) as described below with reference to Equations 1 and 2.
  • a given time period e.g., 3 days, 5 days, 7 days, 10 days, 14 days
  • Ei can represent a summation of each contact event where a user was within a threshold proximity to an infected user multiplied by the time of such contact event.
  • threshold proximity here can be any of the “far”, “medium”, or “close” categories discussed above or any of the other values discussed herein with respect to threshold proximity.
  • threshold proximity utilized in Equation 1 can be 20 ft, 15 ft, 10 ft, 6 ft, or 3 ft, for example.
  • a user’ s exposure level can be determined based on
  • Equation 3 the average exposure of a user can be determined based on an average of the exposure of Etotai discussed above in view of the total number of infected contacts (represented by “n” in Equation 3). (Equation 3)
  • the remote monitoring system 120 can determine (for example, via the contact tracing engine 416) an exposure density of a group of users or all users in an organization, which can be the ratio of the number of infected users (i.e., users in the red category) to a total number of users in that group or organization.
  • an employer may want to monitor the exposure density of a subset of the organization, for example, that work in a particular office, facility, or building.
  • the exposure density of the particular subset is the ratio of the number of infected employees/users to the total number of employees/users that within that subset.
  • the remote monitoring system 120 can determine (for example, via the contact tracing engine 416) exposure levels of users based on additional or alternative information. For example, information such as: whether a contact event was inside a large or small confined space or outside; ambient weather conditions (temperature being hot or mild, humidity, weather), and/or other information. The above described exposure levels can be modified based on such additional information.
  • the remote monitoring system 120 can determine (for example, via the contact tracing engine 416) isolation levels of one or more users in the organization.
  • isolation level can be defined by and/or representative of a total number of contact events (e.g., for a particular user) weight by proximity(ies) between users associated with the contact events.
  • Remote monitoring system 120 can be configured to maintain contact tracing table(s) and/or lists for each user associated with an organization that records various information related to the users.
  • Figure 7C illustrates an exemplary contact tracing table 702 that can be associated with a user in the organization.
  • Such contact tracing table 702 can include a plurality of columns that can show: a timestamp of when a contact event occurred; a user or subject identifier of the other user involved in the contact event; a risk state of the other user; a distance between the user and the other user (i.e., between at least one wearable device coupled with each user); a proximity level of the contact event; a disease or infection state of the other user; and/or a quarantine state of the other user.
  • Such “Risk” column in table 702 can include values (e.g., numbers) that can represent a risk state of the user in a similar manner as that described herein with reference to the color coordinated risk states (“red”, “green”, “yellow”, “orange”). Such risk state can be assigned and/or created by the organization to aid convenient categorization of infection risks of users of the organization.
  • the “Proximity Level” column in table 702 can include values (e.g., numbers) that can represent a category of the proximity between users in a similar manner as that described above with reference to the categories “far”, “medium”, and “close”.
  • a proximity level of “3” can be associated with proximity between users of between 1 ft and 6 ft and a proximity level of “2” can be associated with proximity between users of between 6 ft and 15 ft, between 6 ft and 20ft, or between 6 ft and 30 ft, for example.
  • a proximity level of “0” can be associated with proximity between users of at least 15 ft, at least 20 ft, at least 30 ft, or at least 50 ft, for example.
  • the “Disease State” column in table 702 can reflect whether the other user has been confirmed to be infected or not with a particular infection.
  • the “Disease State” column in table 702 can have a “1” for users who have tested positive and/or have otherwise been determined to be positive for an infection and a “0” for users who have tested negative and/or are otherwise determined to be negative for an infection, or vice versa.
  • the remote monitoring system 120 can dynamically update such table 702 over time simultaneously for a plurality of users in the organization as various types of information is received and/or determined by the remote monitoring system 120.
  • the remote monitoring system 120 can dynamically update the table with external information or instructions (e.g., supervisor escalation or approval, positive or negative test results).
  • the “Quarantine State” column of table 702 can reflect whether a user is in a state of isolation from others. For example, a value of “1” in such column can reflect that the user is (or is supposed to be) in a state of quarantine from others, and a value of “0” in such column can reflect that the user is not in a state of quarantine from others, or vice versa.
  • remote monitoring system 120 generates, stores, and/or update (e.g., continuously over time), a contact tracing table (such as table 702) for every user associated with the organization (for example, every user in an organization including a plurality of users such as any of the numbers of users discussed herein).
  • remote monitoring system 120 determines exposure levels for any or all users associated with the organization based on contact tracing tables associated with each user (such as table 702) alone or in combination with one or more of the exemplary methods listed above with respect to determining exposure levels (e.g., via any of Equations 1-4 and/or combinations thereof).
  • remote monitoring system 120 may be configured to execute certain administrative protocols or include certain features that are designed to avoid bias or retribution towards certain users.
  • the protocols and/or features can also be configured to prevent manipulation by a user, such as an individual in the organization and/or a monitor user of the organization who is tasked with monitoring the organization’s users over the remote monitoring system 120.
  • a user such as an individual in the organization and/or a monitor user of the organization who is tasked with monitoring the organization’s users over the remote monitoring system 120.
  • an employee can be required to present a screen with their user computing device 106 (e.g., smartphone) before entering a building of an organization. If the user computing device 106 is illuminated green, then the employee can be allowed into the building.
  • their user computing device 106 e.g., smartphone
  • the user computing device 106 may request the employee to stay home to prevent the spread of a communicable disease.
  • the user’s user computing device 106 can be configured to present a unique daily barcode, which can be an encrypted version of the user’ s ID and the current date so the organization’ s remote monitoring system 120 can log in the employee. If a screener at the entrance to the building scans the barcode and there’s an issue, then the remote monitoring system 120 can notify the screener.
  • a unique daily barcode can help prevent an infected employee (i.e., an employee in the red category) from showing the screener a screenshot of a green screen from a different day and being allowed into the building.
  • Such implementations can also advantageously be used in other types of settings, such as sports or concert venues.
  • a first user not infected with a communicable disease e.g., COVID-19
  • a second user infected with the disease may both spend at least some overlapping time in a subway station.
  • the first and second users were in the same station for a certain period of time. If the users stay a certain distance apart (such as six feet or more apart), as determined by wearable devices of the users (such as any of those discussed herein), then the risk state of the first user can remain green. If the users are in close proximity with one another (for example, within 6 ft) for a certain period of time (e.g., 5 minutes or more), then the risk state of the first user may change to yellow.
  • Any of the user computing devices discussed herein can include one or more applications can be configured to execute various commands and/or operations which allow users to view their risk state and a plurality of other risks states of other users.
  • a user may be using a mobile or web application on their user computing device to find a restaurant nearby.
  • the application can show the user which restaurants have the lowest risk based on the people currently at the restaurant. For example, a first restaurant may have five people in the red category and a second restaurant may have one person in the red category and four people in the yellow/orange categories.
  • the application can indicate this, for example, by having a green, yellow, orange, or red indicator next to the restaurant.
  • a ridesharing application may include a risk level based on the driver’s risk level and/or the passengers’ risk level.
  • Users can set a minimum risk level threshold such that only drivers that are at or below the threshold can pick up the user. For example, a user can set the threshold to be yellow so that only drivers in green or yellow categories can pick them up. Additionally, drivers can set a minimum risk level threshold such that only riders with certain risk levels will appear on the drivers’ application.
  • Figures 8A-8B illustrate exemplary methods 800, 820 by which the remote monitoring system 120, user computing device(s) 106, and wearable device 104 can interact to facilitate determination of an exposure level and/or risk state of one or more users associated with the remote monitoring system 120 (for example, associated with an organization utilizing a remote monitoring system 120).
  • remote monitoring system 120 receives health-related information from one or more user computing devices.
  • Remote monitoring system 120 can receive a plurality of sets of health- related information from a plurality of user computing devices associated with a plurality of users and a plurality of wearable devices that can be coupled to such plurality of users.
  • One or more wearable devices can be coupled and/or otherwise associated with each user to obtain physiological information and/or other information related to the user.
  • a user computing device (such as any of the user computing devices discussed herein) of and/or used by the user can receive physiological and/or other information from the one or more wearable devices, for example, over any wired and/or wireless communication (such as any of the wireless communications protocols discussed herein).
  • Contact tracing data can include any of that which is discussed elsewhere herein. Such contact tracing data can be indicative of physical proximity of the user to one or more other users which can be determined based on detected wireless signal strengths between one or more wearable device coupled to each of the user and the one or more other users. As discussed elsewhere herein, accumulated duration(s) of time where a user was within a threshold proximity to one or more other users (for example, any of the threshold proximities discussed herein) over a first time period (e.g., 1 day, 2 days, 3 days, 5 days, 7 days, 10 days, 14 days, etc.) can be determined by the remote monitoring system 120 (and/or user computing devices) based on data received from the user computing devices and/ro wearable devices.
  • a first time period e.g., 1 day, 2 days, 3 days, 5 days, 7 days, 10 days, 14 days, etc.
  • one or more risk states associated with other users with which a given user has encountered can be utilized as contact tracing data by the remote monitoring system to determine exposure levels and/or risk states of the given user.
  • Each set of health-related information received by the remote monitoring system can additionally or alternatively include information/data related to a user’s diagnosis and/or test result(s) with respect to one or more infections and/or diseases.
  • diagnosis and/or test result information can be manually input by a user and/or input by a third party (e.g., a medical professional) who has access to the remote monitoring system and/or accessibility to interact with an application on the user’s user computing device in order to input such diagnosis.
  • Each set of health-related information received by the remote monitoring system can additionally or alternatively include information/data related to symptom(s) experienced by the user.
  • symptom(s) can be manually input by the user into a user into a user computing device operated by a user, for example.
  • Including an ability for a user to enter experienced symptom(s) can advantageously capture how a user is “subjectively” feeling, and can useful to supplement more “objectively” obtained information (e.g., physiological information obtained by the wearable device(s) coupled to the user).
  • Such symptom(s) can include, without limitation, fever, chills, cough, shortness of breath or difficulty breathing, fatigue, muscle or body aches, headache, loss of taste or smell, congestion or runny nose, nausea or vomiting, diarrhea, among others).
  • the method 800 can further include receiving other information from the user computing device(s), such as location data, movement data, orientation data, among other things, measured by a magnetometer, accelerometer, and/or gyroscope or other components of the wearable device and/or user computing device.
  • location data such as location data, movement data, orientation data, among other things, measured by a magnetometer, accelerometer, and/or gyroscope or other components of the wearable device and/or user computing device.
  • the remote monitoring system determines an exposure level for a user.
  • Such exposure level can be determined in any of the manners described elsewhere herein for all or a subset of users in an organization simultaneously or non- simultaneously. Further, such exposure level can be continuously and dynamically updated as information is received from user computing devices and/or wearable devices over time.
  • the remote monitoring system determines a risk state for a user (and/or all or a subset of users in an organization).
  • risk state also referred to herein as “risk level”
  • risk level can be determined in any of the manners described elsewhere herein.
  • a risk state of a particular user can be determined based on one or more of user physiological information, contact tracing data, diagnosis and/or test result data, symptom(s) information, exposure levels, and/or risk state(s) of other users if available.
  • the remote monitoring system sends (e.g., over a network) the determined risk state and/or other information or instructions associated with such risk state to the user computing device(s).
  • Such other information or instructions can be, without limitation: instructions to the user concerning whether to quarantine (e.g., stay home) or come into a facility of the organization; and/or information related to exposure and/or risk states of any other users who may have come into contact with the user over a period of time and/or any visual representation thereof (e.g., graphs, tables, lists illustrating such information).
  • the method 800 described above can be carried out for each user computing device and user associated with a given organization simultaneously, but such method 800 can be carried out on an ongoing basis, continuously determining exposure levels and risk states of such users and updating the users with such information.
  • the method 800 can additionally involve allowing for adjustment of exposure level(s) and/or risk state(s), for example, by a monitor user of an organization tasked with overseeing the remote monitoring system. Such adjustment can be as that described elsewhere herein (e.g., with respect to Figures 6A-6B).
  • FIG. 8B illustrates a method 820 by which a user computing device (such as any of those discussed herein) can interact with one or more wearable devices associated with a user (such as any of the wearable devices discussed herein) and a remote monitoring system (such as any of the remote monitoring systems described herein).
  • the user computing device such as a smart phone
  • the user computing device receives physiological information from one or more wearable devices associated with (e.g., coupled to) the user, such as any of the physiological information/data discussed herein.
  • the user computing device also receives other information, such as location data and/or movement data as discussed elsewhere herein.
  • the user computing device only receives contact tracing data (e.g., proximity data) when the user is within the threshold proximity, but continuously receives physiological information (for example, regardless of whether the user is within the threshold proximity to other users) from a wearable device.
  • contact tracing data e.g., proximity data
  • physiological information for example, regardless of whether the user is within the threshold proximity to other users
  • Each of the user interfaces shown includes one or more user interface elements or controls that can be selected by a user.
  • the user interface elements shown are merely illustrative examples and can be varied in other embodiments. For instance, any of the user interface elements shown may be substituted with other types of user interface elements.
  • each of the user interface elements may be selected by a user using one or more input options, such as a mouse, touch screen input (e.g., finger or pen), or keyboard input, among other user interface input options.
  • input options such as a mouse, touch screen input (e.g., finger or pen), or keyboard input, among other user interface input options.
  • a sharing configuration user interface can allow a user to modify their sharing permissions, such as by identifying and/or modifying other users (for example, within a remote monitoring system) that are permissioned to view at least some the user’s data/receive alerts regarding the user.
  • FIG. 10B illustrates an example dashboard user interface 1000’ of the application.
  • the dashboard user interface 1000’ can include one or more physiological parameter summaries 1010A, 1010B, 1010C, 1010D. As shown, each of the example physiological parameter summaries 1010A, 1010B, 10 IOC, 1010D can be associated with different physiological parameters.
  • the dashboard user interface 1000’ can include more or less physiological parameter summaries based on the particular configuration or embodiment.
  • the physiological parameter summaries 1010A, 1010B, 1010C, 1010D can allow a user to review physiological parameters.
  • the one or more physiological parameter summaries 1010A, 1010B, 1010C, 1010D can be associated with physiological parameters including, but not limited to, blood pressure, blood oxygen saturation, heart rate, respiration rate, body weight, or body temperature.
  • a user can select the one or more physiological parameter summaries 1010A, 1010B, 1010C, 1010D to access additional details related to the physiological parameter associated with the selected physiological parameter summary 1010A, 1010B, 1010C, 1010D.
  • the dashboard user interface 1000’ can include one or more elements 1030 that indicate users that are authorized to view and/or access user data, such as the physiological parameter summaries 1010A, 1010B, 1010C, 1010D. Accordingly, a user of the application can readily identify who has access to the physiological parameter summaries 1010A, 1010B, 1010C, 1010D. A user may add other users as authorized users via the add user element 1040. Once added as authorized users, those other users may be able to view and/or access the physiological parameter summaries 1010A, 1010B, 1010C, 1010D associated with the user. User selection of the add user element 1040 may cause the application to present a graphical user interface that can allow the user to identify one or more users to be added as authorized users.
  • the visualization 100 IB can use different indicators to display different data points in.
  • the visualization 1001B can use the color green for data points within a predetermined range, the color yellow for data points within a different predetermined range, and the color red for data points outside of those predetermined ranges.
  • FIG. 11B illustrates another example user interface 1100’.
  • the user interface 1100’ can include an input area 1112 for a question and/or action item (here an item to receive a user’ s temperature as user input). As shown, a user can input a temperature value.
  • a user interface instead of being received via manual user input, a user interface be configured to display one or more temperature values of the user obtained and received from one or more wearable devices, as discussed elsewhere herein.
  • the user interface 1100” can further include several items 1124A, 1124B, 1124C.
  • the example items 1124A, 1124B, 1124C can be questions and/or action items, which can be completed by the user.
  • the item 1124A with the prompt (such as “Are you having trouble breathing?”) can elicit a yes/no response to be provided from the user.
  • the user can select the second item 1124B that can cause presentation of the user interface 1100’ of Figure 11B.
  • the third item 1124C (shown as a respiration rate item) can be an item that can receive user input and/or that displays physiological information derived from one or more wearable devices in communication with the user computing device.
  • the items 1122, 1124A, 1124B, 1124C of Figure 11C can likewise be directed towards the novel coronavirus and/or COVID-19.
  • the items 1122, 1124A, 1124B, 1124C of Figure 11C can be directed towards the symptoms of COVID-19 or any other respiratory disease (that can potentially be very dangerous) such as low oxygen saturation, high body temperature, difficulty breathing, and/or too low or too high of a respiration rate.
  • any of the user interfaces 1100, 1100’, 1100 can be directed to diseases other than COVID-19, for example, to flu or common cold.
  • the user interface 1200 can display user names, user statuses (for example, risk states such as those discussed elsewhere herein), and/or can include various other information that can help efficiently and simply convey such statuses, such as color coding associated with risk state (“red”, “yellow”, such as that discussed elsewhere herein) and/or a risk state/status label (such as “Confirmed”, “Symptomatic”, “Exposed”, “Cleared”, etc.).
  • Figure 12B illustrates another exemplary user interface 1201.
  • User interface 1201 can represent a view that can appear if the monitor user selected one of the box icons in user interface 1200 which included a particular user (e.g., “User 1”).
  • User interface 1201 can advantageously present information specific to the particular user, including but not limited to, contact information (e.g., email, phone number, location, job title, groups within the organization that the particular user is associated with, etc.). As shown, information concerning status, tasks or instructions, and/or contact tracing can be displayed. For example, as shown, the user interface 1201 can display tasks related to a user quarantining for a given period of time (e.g., “48 days of quarantine left”) and/or tests for a particular infection (e.g., COVID-19). As also shown, user interface 1201 can display activity and/or history of the particular user, for example, along a timeline. Such activity and/or history information can include specific tasks, status, and/or daily questions.
  • contact information e.g., email, phone number, location, job title, groups within the organization that the particular user is associated with, etc.
  • information concerning status, tasks or instructions, and/or contact tracing can be displayed. For example, as shown, the user interface 1201 can
  • User interface 1201 can represent a view that a monitor user would see if accessing an application via the a computing device of the remote monitoring system and/or can represent a view that a particular user would see if the particular user accessed the application via a computing device such as a laptop or desktop via a web browser. Where accessed in such manner by the particular user, in some implementations the application allows the user to input information and edit various aspects of the application.
  • User interface 1201 can allow the monitor user and/or the user represented in the user interface 1201 to edit the user’s profile and/or status.
  • User interface 1203 in Figure 12C illustrates a view that can appear if the monitor user and/or another user selected the “Update Status” icon in user interface 1201.
  • various aspects of a user’s status can be modified/updated, such as a “Health Status” (e.g., “symptomatic”, “clean”, “confirmed”, “infected”, “asymptomatic”, etc.), “Symptom Starting Date” (e.g., an “onset” date of symptoms), “Symptoms” (e.g., fever or temperature over a threshold such as 100.4°F or 38°C), chills, cough, sore throat, fatigue, shortness of breath, vomiting, diarrhea, loss of taste and/or smell, or other symptoms, and/or “Notes” which can include other information such as whether the user was asked to self-quarantine.
  • Symptom Starting Date e.g., an “onset” date of symptoms
  • Symptoms e.g., fever or temperature over a threshold such as 100.4°F or 38°C
  • chills cough, sore throat, fatigue, shortness of breath, vomiting, diarrhea, loss of taste and/or smell, or other symptoms
  • “Notes” which can include other information such
  • User interface 1205 can display a list of contacts (e.g., users), groups which may be a subset of the organization to which a particular user belongs, a box which can be indicative of an exposure (see “Exposed” text), and a “Notes” list which can allow entry and/or verification of descriptions related to contact events.
  • contacts e.g., users
  • groups which may be a subset of the organization to which a particular user belongs
  • a box which can be indicative of an exposure see “Exposed” text
  • a “Notes” list which can allow entry and/or verification of descriptions related to contact events.
  • Figures 12E illustrates another exemplary user interface 1207 which allowing viewing and/or modification of groups of users within an organization.
  • User interface 1207 can advantageously facilitate subdividing all the users in an organization into groups which can be defined by sets of users who work together in certain portions of the organization’s facilities and/or who share similar tasks or job descriptions. The viewing and/or modification of such groups can allow simple and efficient monitoring and management of users.
  • a plurality of groups can be created which subdivide the users in the organization by job title and/or location, for example, “Engineering”, “Marketing”, “Warehousing”, “Central Warehouse”, “Eastside Warehouse”, “Westside Warehouse”, etc.). Selection of any of such plurality of groups can allow “Bulk Actions” to be undertaken, such as modifying risk states and/or instructions for all users within a particular group.
  • Figure 12F illustrates another exemplary user interface 1207.
  • User interface 1207 illustrates an exemplary “Settings” view that can allow, for example, a monitor user to change various settings of the remote monitoring system and/or an application associated therewith which can affect how the application is executed on any user computing device of any of the plurality of users of an organization.
  • user interface 1207 can allow the creation and/or modification of, without limitation: risk labels or risk states (see “Label” column); associated visual characteristics (e.g., “Red” “Yellow”, “White”, “Dark grey”, “light grey”, etc.); risk label/state descriptions (see “Description” column); quarantine time (see “Quarantine (Days)” column); and whether a given risk label/state is “Active”.
  • user interface 1207 can allow modification of exposure and/or risk state determination settings. For example, if a member of a group (such as the groups discussed above) is either symptomatic or confirmed to be infected, other members of that group might have been exposed.
  • the user interface 1207 can configure the a remote monitoring system and/or application associated therewith to automatically change a risk state of all members in such group to “Exposed” or alternatively, to qualify exposure of all members based on one or more parameters such as whether the member worked with a symptomatic/confirmed member whether the user can identify who they were in contact with, and subsequent to that qualification, determine whether to label the user as “exposed.”
  • User interface 1207 can also allow configuration for exposure notification messages (e.g., alerts) to be sent out to one or more users of a group if a determination is made that a user from that group was infected.
  • Figure 12G illustrates another exemplary user interface 1209.
  • User interface 1209 illustrates an exemplary “Stats” view that can allow, for example, a monitor user to view statistics on all users of the organization or a subset (e.g., a group) of users within the organization.
  • user interface 1209 can include information and/or a visual representation associated with: total number of cases of an infection (e.g., number of diagnosed users, number of symptomatic users, number of exposed users); trending information and/r graphs indicative of the number of open cases over a given time period (e.g., 1 day, 3 days, 5 days, 7 days, 14 days, 1 month, 2 months, 6 months, one year, etc.); “Daily Check-in” information which can be indicative of the number of users that are checking in (e.g., by registering their user computing device with a screening device or in another manner) to a facility of the organization; and/or “Estimated Return Date” information that can represent a timeline of return dates for users who are quarantining.
  • total number of cases of an infection e.g., number of diagnosed users, number of symptomatic users, number of exposed users
  • trending information and/r graphs indicative of the number of open cases over a given time period (e.g., 1 day, 3 days, 5 days,
  • Figures 13A-13E illustrate exemplary user interfaces 1300, 1302, 1304, 1306, 1308 that can be utilized in a mobile application of a user computing device (such as any of the user computing devices discussed herein). However, all or portions of such user interfaces 1300, 1302, 1304, 1306, 1308 can be utilized by a web application of a user computing device, for example, via a browser.
  • Figure 13A illustrates a user interface 1300 that can include, among other things, a prompt for a user to answer daily questions that can be related to and/or indicative of an infection. Such daily questions can be any of the questionnaire and questions discussed elsewhere herein, for example, with reference to symptom information.
  • Figures 14A-14B illustrate additional exemplary user interfaces 1400, 1400’ that may be generated by a one or more hardware processors of a computing device via a mobile and/or web based application executed by the computing device.
  • User interfaces 1400, 1400’ advantageously can illustrate contact tracing data in a simple and effective manner.
  • User interfaces 1400, 1400’ can illustrate, over a period of time and/or along a timeline, one or more contact events that a user has with one or more other users, for example, in an organization.
  • Proximity data can be obtained from a wearable device (such as any of the wearable devices discussed herein) and can be transmitted to a user computing device (such as any of the user computing devices discussed herein) associated with (e.g., belonging to) a user.
  • a user computing device such as any of the user computing devices discussed herein
  • Such user computing device e.g., smartphone
  • a remote monitoring system such as any of the remote monitoring systems discussed herein.
  • proximity data can be obtained from the wearable device and can be directly transmitted to the remote monitoring system (e.g., without utilization of the user computing device).
  • Such actions can include, for example: receiving proximity data from the wearable device (either directly or via a user computing device), the proximity data indicative of distance between the wearable device and a separate wearable device coupled to a second user; receiving a first identifier associated with the user and/or the wearable device of the user; receiving a second identifier associated with the second user and/or the separate wearable device; store said proximity data over time along with the first and second identifiers; and/or determine one or more contact events based on the proximity data, where each of the one or more contact events is representative of the first and second users being within a threshold proximity (such as any of the threshold proximities discussed herein) for a continuous period of time.
  • a threshold proximity such as any of the threshold proximities discussed herein
  • Such actions can additionally include generating a graphical user interface on a display of the computing device associated with the remote monitoring system (e.g., computing device used by a monitor user) and generating a timeline (that can be continuously updated over time) and a visual representation of such one or more contact events along a timeline.
  • the remote monitoring system e.g., computing device used by a monitor user
  • a timeline that can be continuously updated over time
  • Such visual representation(s) can be in the form of a shape and/or can have a color, for example.
  • Such visual representation(s) can be a bubble, as illustrated in Figures 14A-14B.
  • a size and/or other characteristic of bubble correlates with and/or is indicative of the period of time in a contact event. For example, a first contact event between two users where the two users were within a threshold proximity (e.g., 6 ft) from one another for 20 minutes can be represented by a bubble that has a greater size, shape, perimeter, and/or other characteristic (e.g., radius, diameter) than a second contact event where the two users were within the threshold proximity for 5 minutes.
  • each contact event can be represented by a circle, where a diameter of the circle corresponds to the length of time of the contact event (e.g., the duration of time that a user was within a threshold proximity of another user).
  • a first point along a perimeter of a bubble representing a contact event can represent the time at which the contact event began and a second point along the perimeter of the bubble can represent the time at which the contact event ended.
  • the bubble(s) can be color coordinated for each user (e.g., each user is represented with a different color) or can be color coordinated based on risk state of each user (e.g., user’s confirmed with an infection can be represented by a “red” bubble and user’s not infected can be represented by a “green” bubble).
  • multiple bubbles can be generated along the timeline to represent, for example, multiple, distinct contact events between the same users.
  • user interface 1400, 1400’ can be generated, for example, continuously, for every user of an organization, and can be viewed by the object user and/or a monitor user of an organization. Such user interface 1400, 1400’ accordingly presents a dynamic method by which contact events can be conveniently be monitored.
  • Conditional language used herein such as, among others, “can,” “could,” “might,” “may,” “e.g.,” and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain features, elements, and/or steps are optional. Thus, such conditional language is not generally intended to imply that features, elements, and/or steps are in any way required or that one or more embodiments necessarily include logic for deciding, with or without other input or prompting, whether these features, elements, and/or steps are included or are to be always performed.
  • Any methods disclosed herein need not be performed in the order recited.
  • the methods disclosed herein may include certain actions taken by a practitioner; however, they can also include any third-party instruction of those actions, either expressly or by implication.
  • the methods and tasks described herein may be performed and fully automated by a computer system.
  • the computer system may, in some cases, include multiple distinct computers or computing devices (e.g., physical servers, workstations, storage arrays, cloud computing resources, etc.) that communicate and interoperate over a network to perform the described functions.
  • Each such computing device typically includes a processor (or multiple processors) that executes program instructions or modules stored in a memory or other non-transitory computer-readable storage medium or device (e.g., solid state storage devices, disk drives, etc.).
  • the various functions disclosed herein may be embodied in such program instructions, and/or may be implemented in application- specific circuitry (e.g., ASICs or FPGAs) of the computer system.
  • the computer system may, but need not, be co located.
  • the results of the disclosed methods and tasks may be persistently stored by transforming physical storage devices, such as solid state memory chips and/or magnetic disks, into a different state.
  • the computer system may be a cloud-based computing system whose processing resources are shared by multiple distinct business entities or other users.
  • various illustrative logical blocks and modules that may be described in connection with the disclosure herein can be implemented or performed by a machine, such as a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.
  • a general purpose processor can be a microprocessor, but in the alternative, the processor can be a controller, microcontroller, or state machine, combinations of the same, or the like.
  • a processor can include electrical circuitry configured to process computer- executable instructions.
  • a processor can include an FPGA or other programmable device that performs logic operations without processing computer-executable instructions.
  • a processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
  • a processor may also include primarily analog components. For example, some or all of the rendering techniques described herein may be implemented in analog circuitry or mixed analog and digital circuitry.
  • a computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.
  • a software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of a non- transitory computer-readable storage medium.
  • An exemplary storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium.
  • the storage medium can be integral to the processor.
  • the processor and the storage medium can reside in an ASIC.
  • the ASIC can reside in a user terminal ⁇
  • the processor and the storage medium can reside as discrete components in a user terminal.

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