WO2017146643A1 - Système de surveillance de patient - Google Patents

Système de surveillance de patient Download PDF

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Publication number
WO2017146643A1
WO2017146643A1 PCT/SG2017/000004 SG2017000004W WO2017146643A1 WO 2017146643 A1 WO2017146643 A1 WO 2017146643A1 SG 2017000004 W SG2017000004 W SG 2017000004W WO 2017146643 A1 WO2017146643 A1 WO 2017146643A1
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WO
WIPO (PCT)
Prior art keywords
movement
sensor
data
control unit
person
Prior art date
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PCT/SG2017/000004
Other languages
English (en)
Inventor
Kyaw Ko Ko HTET
Arun Shankar NARAYANAN
Original Assignee
Apeiron Technology Pte Ltd
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Publication date
Application filed by Apeiron Technology Pte Ltd filed Critical Apeiron Technology Pte Ltd
Publication of WO2017146643A1 publication Critical patent/WO2017146643A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
    • A61B5/1115—Monitoring leaving of a patient support, e.g. a bed or a wheelchair
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A61B5/1122—Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
    • A61B5/1128—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique using image analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
    • 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
    • G08B21/0407—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis
    • G08B21/043—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis detecting an emergency event, e.g. a fall
    • 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
    • G08B21/0492—Sensor dual technology, i.e. two or more technologies collaborate to extract unsafe condition, e.g. video tracking and RFID tracking
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
    • G08B29/18—Prevention or correction of operating errors
    • G08B29/20—Calibration, including self-calibrating arrangements
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1116—Determining posture transitions
    • A61B5/1117—Fall detection
    • 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
    • G08B21/0407—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis
    • G08B21/0423—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis detecting deviation from an expected pattern of behaviour or schedule

Definitions

  • a patient monitoring system A patient monitoring system
  • the present invention relates to a patient monitoring system, and more particularly relates to a patient monitoring system for use with a patient who is at a high risk of a fall. It is known to use technology to monitor a patient that is at risk of falling accidentally. Conventional systems use sensors, such a cameras, infrared sensors, pressure sensors or light curtains to detect the movement of a person and alert a carer to a fall. There are benefits and disadvantages to using each of these types of sensors in a patient monitoring scenario.
  • a camera can be reliable but it is the least preferred option as it is perceived to intrude on the patient's privacy.
  • the system can either be a manual type of monitoring method by a dedicated personnel or an automated one in which, some intelligent algorithm would be able to detect abnormality after processing the image and alerting a caregiver when necessary.
  • An infrared sensor is more viable than a camera for patient monitoring as it is non-intrusive to the patient's privacy and, with proper algorithms, the accuracy can be very high.
  • a static background would be already eliminated from the infrared sensor's vision and, as a result, only warm objects such as a human body will be left in the frame. This makes it easier for an algorithm to detect the motion pattern of a body.
  • drawbacks in using an infrared sensor such as the relatively high price point of an infrared sensor and the difficulty of using an infrared sensor for wider coverage.
  • Another patient monitoring system detects a patient moving out of position using a cord of which is attached at one end to a patient and at the other end to a switch, if the patient moves and extends the cord is further than a fixed length, the switch is activated to trigger the system to sound an alarm.
  • the problem with this system is that the mechanism can be easily bypassed by the patient simply removing the cord from their body. The system is therefore not deemed to be tamper resistant.
  • US-A-6166644 also includes the use of pressure sensors as another viable option to achieve similar purpose.
  • Some hospitals are known to use this method in which an electro mechanical pressure mat mounted on the bed provides the pressure map according to the patient's position on the bed and generates an alert signal if the patient is detected to be moving out of the bed. This is a good solution that can help prevent fall, especially in the case of high fall risk patients.
  • the accuracy of the method is known to be low with many false alerts even with the patient still in bed.
  • a patient monitoring system comprising: a control unit; a memory coupled to the control unit, the memory storing predetermined movement data which comprises: first movement data which is indicative of a safe condition, and/or second movement data which is indicative of an unsafe condition; wherein the system further comprises: at least one movement sensor coupled to the control unit, the at least one movement sensor being configured to sense the movement of a person and provide a movement sensor output signal to the control unit, wherein the control unit is configured to process the movement sensor output signal and generate sensed movement data using the movement sensor output signal, the control unit being configured to compare the sensed movement data with the predetermined movement data and generate an alert signal to indicate an unsafe condition if the sensed movement data does not match at least part of the first movement data and/or the sensed movement data matches at least part of the second movement data.
  • the system further comprises: an alert system which is configured to receive the alert signal and, upon receipt of the alert signal, to output at least one of an alert light, an alert sound or an alert message.
  • an alert system which is configured to receive the alert signal and, upon receipt of the alert signal, to output at least one of an alert light, an alert sound or an alert message.
  • the alert message is at least one of a short message service (SMS) message, an email message or a microblog message.
  • SMS short message service
  • the at least one movement sensor comprises a camera which is configured to capture an image and the provide movement sensor output signal in the form of image data to the control unit, the control unit being configured to process the image data to derive sensed movement data from the image data which is indicative of the movement of a person.
  • the at least one movement sensor comprises an infrared sensor which is configured to sense the movement of a person.
  • the at least one movement sensor comprises a pressure pad sensor which is configured to sense the weight of a person acting on the pressure pad sensor.
  • the at least one movement sensor comprises a light beam sensor which is configured to sense the movement of a person by sensing when a person at least partly interrupts a light beam being detected by the light beam sensor.
  • the light beam sensor is a light curtain sensor which is configured to output a plurality of light beams and to sense an interruption of at feast one of the light beams.
  • the at least one movement sensor comprises an ultrasonic sensor.
  • the system comprises a plurality of movement sensors which are each configured to be positioned at a different location within a building to sense the movement of a person within the building.
  • the at least one sensor is configured to communicate wirelessly with the control unit.
  • the system comprises a plurality of sensors that are configured to communicate wirelessly with each other.
  • the at least one sensor is configured to communicate wirelessly using a wireless communication protocol selected from a group comprising ZigBee, Bluetooth or WiFi.
  • the at least one sensor is physically integrated with the control unit.
  • the at least one sensor is embedded with part of the control unit.
  • the system further comprises: at least one physiological sensor which is configured to sense a physiological property of a person and provide physiological data indicative of the physiological property to the control unit.
  • the system is configured to operate in a recording mode in which the at least one movement sensor senses the movement of a person and provides a movement sensor output signal to the control unit, the control unit being configured to process the movement sensor output signal and generate sensed movement data using the movement sensor output signal, wherein the control unit is configured to store the sensed movement data in the memory for use as predetermined movement data when the system is not operating in the recording mode.
  • the system further comprises: a machine learning module which is configured to receive and process the sensed movement data over a period of time, identify patterns in the movement of a person over the period of time and store pattern data indicative of the movement patterns in the memory for subsequent use by the system.
  • a machine learning module which is configured to receive and process the sensed movement data over a period of time, identify patterns in the movement of a person over the period of time and store pattern data indicative of the movement patterns in the memory for subsequent use by the system.
  • control unit is configured to receive an input from a user which comprises data that is indicative of an unsafe condition and store the input data as second movement data in the memory.
  • the safe condition indicated by the first data is a safe location for a person relative to the at least one sensor.
  • the unsafe condition indicated by the second data unsafe location for a person relative to the at least one sensor is configured to communicate with a remote server via a computer network and to transmit data for storage at the remote server.
  • the control unit is configured to communicate with a mobile device or a smart device via a computer network and to receive commands from and send data to the mobile device or smart device.
  • a patient monitoring network comprising a plurality of patient monitoring systems according to any one of the claims as defined hereinafter, wherein each patient monitoring system is configured to monitor a different patient at a different location and each patient monitoring system is configured to provide monitoring data to a remote device.
  • a method of monitoring a patient comprising: sensing, using at least one movement sensor, the movement of a person and providing a movement sensor output signal from the at least one movement sensor to the control unit; processing, at the control unit, the movement sensor output signal and generating sensed movement data using the movement sensor output signal; comparing, at the control unit, the sensed movement data with predetermined movement data which comprises: first movement data which is indicative of a safe condition, and/or second movement data which is indicative of an unsafe condition; and generating an alert signal to indicate an unsafe condition if the sensed movement data does not match at least part of the first movement data and/or the sensed movement data matches at least part of the second movement data.
  • the method further comprises: receiving the alert signal at an alert system and, upon receipt of the alert signal, to outputting from the alert system at least one of an alert light, an alert sound or an alert message.
  • method comprises sensing, using a plurality of movement sensors each positioned at a different location within a building, the movement of a person within the building.
  • method comprises communicating data wireiessly between the at least one movement sensor and the control unit.
  • method comprises communicating data wireiessly between a plurality of movement sensors.
  • method comprises communicating data wireiessly using a wireless communication protocol selected from a group comprising ZigBee, Bluetooth or WiFi.
  • method further comprises: sensing, using at least one physiological sensor, a physiological property of a person; and providing physiological data indicative of the physiological property to the control unit.
  • method further comprises: sensing, using the at least one movement sensor, the movement of a person and providing a movement sensor output signal to the control unit; processing, at the control unit, the movement sensor output signal and generating sensed movement data using the movement sensor output signal; and storing the sensed movement data in the memory for subsequent use as predetermined movement data.
  • method further comprises: receiving and processing, at a machine learning module, the sensed movement data over a period of time; identifying, at the machine learning module, patterns in the movement of a person over the period of time; and storing pattern data indicative of the movement patterns in the memory.
  • the method further comprises: interacting with at least one of a user, a nurse and/or a technician to cross-validate a previous identification.
  • the method further comprises: analysing an input from at least one of the user, nurse and/or technician to cross-validate a previous identification.
  • method further comprises: receive an input from a user which comprises data that is indicative of an unsafe condition; and storing the input data as second movement data in the memory.
  • the safe condition indicated by the first data is a safe location for a person relative to the at least one sensor.
  • the unsafe condition indicated by the second data is an unsafe location for a person relative to the at least one sensor.
  • the method further comprises: transmitting data from the control unit to a remote server for storage at the remote server.
  • the method further comprises: receiving, at the control unit, commands from a mobile device or a smart device; and sending data from the control unit to the mobile device or smart device.
  • a method of calibrating a sensor comprising: providing a sensor having a field of view over which the sensor senses; positioning a calibration element to occupy the entire field of view of the sensor; adjusting at least one parameter of the sensor by a calibration level so that the output from the sensor is uniform across the field of view of the sensor; removing the calibration element from the field of view of the sensor; and adjusting the at least one parameter of the sensor by the calibration level such that the sensor is calibrated to provide a uniform output across the entire field of view of the sensor.
  • the senor is an infrared sensor.
  • Figure 1 is a schematic diagram showing an overview of a patient monitoring system of some embodiments
  • Figure 2 is a flow diagram showing components of a patient monitoring system of some embodiments
  • Figure 3 is a schematic diagram of part of a patient monitoring system of some embodiments.
  • Figure 4 is a schematic diagram of part of a patient monitoring system of some embodiments.
  • Figure 5A is a schematic diagram of a patient monitoring system installed in a building with a patient in a normal position
  • Figure 5B is a schematic diagram corresponding to figure 5A with the patient in a fall condition
  • Figure 6A is a schematic diagram of a patient monitoring system installed in a building
  • Figure 6B is a schematic diagram corresponding to figure 6A with a high risk fall patient being monitored
  • Figure 7 is a schematic diagram showing data login and report generation details output from a system of some embodiments.
  • Figure 8 is a schematic diagram of a patient monitoring system of some embodiments with the system coupled to a cloud based storage arrangement
  • Figure 9 is a schematic diagram indicating the collaboration of a sensor of some embodiments.
  • Figure 10 is a sample report output from a patient monitoring system of some embodiments
  • Figure 11 is a schematic diagram showing an overview of an embedded patient monitoring system.
  • a patient monitoring system of some embodiments comprises eight subsystems 1-8.
  • the subsystems 1-8 will be described in detail below. It is to be appreciated that, in some embodiments, one or more of the subsystems 1-8 may be omitted.
  • a patient monitoring system of some embodiments comprises a central station in the form of a control unit 9 which incorporates a processor 10.
  • a memory 11 is coupled to the control unit 9 such that the processor 10 can access data stored in the memory 1 and write data to the memory 11.
  • the system further comprises at least one movement sensor 12.
  • the system comprises a plurality of movement sensors which are each coupled to the control unit 9.
  • the at least one sensor 12 is physically integrated with the control unit 9.
  • Each movement sensor 12 is configured to sense the movement of a person/patient 13 and provide a movement sensor output signal to the control unit 9.
  • the control unit 9 is configured to process the movement sensor output signal from the at least one sensor 12 and to generate sensed movement data.
  • the sensed movement data is data which indicates the position or location of the person 13.
  • the sensed movement data is data indicative of a property of the person 13, such as if the person 13 is lying, sitting or standing.
  • the memory 11 stores predetermined movement data.
  • the predetermined movement data comprises first movement data which is indicative of a safe condition and/or second movement data which is indicative of an unsafe condition. In some embodiments, the memory 11 stores only one of the first and second movement data.
  • the first movement data which is indicative of a safe condition, is a predetermined data representation of a safe condition for the person 13. For instance, in some embodiments, the first movement data is indicative of a safe position or location for the person 13 within a building.
  • the second movement data which is indicative of an unsafe condition, is a predetermined data representation of an unsafe condition for the person 13.
  • the unsafe condition of the person 13 is an unsafe position or location for the person 13 within a building.
  • the system is configured, when functioning in an operating mode, to monitor the patient 13.
  • the at least one movement sensor 12 senses the position or movement of the person 3.
  • the control unit 9 is configured to generate an alert signal 14 to indicate an unsafe condition if the sensed movement data does not match at least part of the first movement data and/or the sensed movement data matches at least part of the second movement data.
  • the control unit generates the alert signal 14 if the sensed movement data derived from the at least one sensor 12 is indicative of a position or movement of the person 13 which is not a position or movement which corresponds to a position or movement represented by the first movement data.
  • control unit 9 compares the sensed movement data to the second movement data which is indicative of an unsafe condition. If the control unit 9 establishes that the sensed movement data matches at least part of the second movement data, the control unit 9 determines that the sensed movement data represents corresponds to an unsafe position or movement represented by the second movement data. In this case, the control unit 9 outputs the alert signal 14 to alert a caregiver to the unsafe condition.
  • the control unit 9 is configured to apply an algorithm 15 during the comparison of the sensed movement data with the predetermined movement data to determine whether or not to output the alert signal 14.
  • the system comprises an alert system 16 which is coupled to the control unit 9 and configured to receive the alert signal 14 and output an alert to a user.
  • the alert includes, but is not limited to, an alert light, an alert sound or an alert message.
  • the alert system 16 is configured to output an alert message
  • the alert messages can be in the form of any electronically transmitted message using any electronic device or medium.
  • the alert message can comprise, but is not limited to, a short message service (SMS) message, an email message or a microblog message.
  • SMS short message service
  • the alert system 16 is configured to alert a user, such as a caregiver, to the unsafe condition of the person 13 which was detected by the system. The user can then intervene to minimise or prevent the unsafe condition.
  • the at least one movement sensor 12 comprises a camera which is configured to capture an image and provide the movement sensor output signal in the form of image data to the control unit 9.
  • the control unit 9 is configured to process the image data to derive sensed movement data from the image data which is indicative of the movement of the person 13.
  • the sensed movement data derived from the camera preferably indicates the presence and/or position of the person 13.
  • the sensed movement data derived from the camera provides more detailed information about the position and condition of the person 13, such as the angle at which the person is standing, if the person is sitting or lying and where the person is located. The camera can therefore provide information about whether a person has undergone a fall or predict whether a person will have a fall in a certain period of time.
  • the system comprises at least one movement sensor 12 in the form of an infrared sensor which is configured to sense the presence or movement of the person 3.
  • the sensed movement data derived from the infrared sensor preferably indicates the presence and/or position of the person 13.
  • the sensed movement data derived from the sensor provides more detailed information about the position and condition of the person 13, such as the angle at which the person is standing, if the person is sitting or lying and where the person is located. The sensor can therefore provide information about whether a person has undergone a fall or predict whether a person will have a fall in a certain period of time.
  • the system comprises at least one movement sensor 12 in the form of a pressure pad sensor which is configured to sense the weight of a person acting on the pressure pad sensor.
  • the at least one movement sensor 12 comprises a light beam sensor which is configured to sense the movement of a person 13 by sensing when the person 13 at least partly interrupts a light beam being detected by the light beam sensor.
  • the system comprises a light beam sensor in the form of a light curtain sensor which is configured to output a plurality of light beams and to sense an interruption of at least one of the light beams by a person 3.
  • the at least one movement sensor 12 comprises an ultrasonic sensor which is configured to sense the position or presence of a person 13.
  • the system comprises a plurality of different types of movement sensors, such as the different movement sensors described above. The system pulls together the different types of movement sensor 12 and takes advantage of the benefits offered by each of the different types of movement sensor.
  • the system further comprises a user input module 17 which is coupled to the control unit 9. The user input module 17 is configured to receive an input from a user and to communicate the input to the processor 10 in the control unit 9. The user input module 17 is configured to enable a user to input boundary conditions to the system which are stored as the first or second movement data in the memory 11.
  • the system further comprises a machine learning module 18 which is coupled to the control unit 9.
  • the machine learning module 18 is preferably a computer-implemented module which is configured to receive data gathered and stored by a data logging module 19 over time which is indicative of the sensed movement of the person 13 over time.
  • the control unit 9 is configured to output some or all of the sensed movement data from the processor 10 to the data logging module 19 so that the data logging module 19 records some or ail of the data indicating the position and/or movement of the person 13 over a period of time.
  • the data logging module 19 is configured to provide a data output to users 20 and/or technicians 21.
  • the machine learning module 18 is preferably configured to use a form of artificial intelligence, such as a neural network, to identify patterns in the sensed movement data over a period of time and to store pattern data indicative of the movement patterns in the memory 11.
  • the pattern data can then be used subsequently by the system to detect and/or predict safe and/or unsafe patient movement in advance when the system is monitoring the person 13. For instance, the pattern data can be used by the system to enable the system to determine how long the person 13 would ordinarily take to move from a first position to a second position or a particular time of day at which the person 13 moves in a particular way.
  • the machine learning module 18 is configured to interact with users, nurses and technicians or use inputs from them to cross-validate its identification directly or indirectly.
  • the at least one movement sensor 12 is configured to communicate wirelessly with the control unit 9.
  • the system comprises first and second infrared sensors 22, 23, a camera 24, a light curtain 25 and a pressure pad sensor 26.
  • the wireless communication protocol between the at least one movement sensor 12 and the control unit 9 preferably uses a wireless communication protocol selected from a group comprising ZigBee, Bluetooth or WiFi. In other embodiments, the system can use a different wireless communication method for communication between the at least one movement sensor 12 and the control unit 9.
  • the system comprises a plurality of movement sensors 12 and the movement sensors 12 are configured to communicate with one another in addition to communicating with the control unit 9.
  • the system comprises movement sensors in the form of a camera 27, a light curtain 28, a pressure pad 29 and an infrared sensor 30.
  • the system further comprises a smart watch 31 which is configured to communicate with the central station 9 and with the movement sensors.
  • Each of the arrows shown in figure 4 indicates communication between the components of the system.
  • the communication between the components of the system is preferably communication using technology that would be familiar to those skilled in the art which would typically be used for smart home applications, such as to integrate appliances within a home with the Internet of Things ⁇ referred to hereinafter as loT).
  • the system is configured to operate in a record mode in which the system stores sensed movement data in the memory 11 which is indicative of the movement of the person 13.
  • the record mode enables the system to record the sensed movement data which is subsequently used as predetermined movement data when the system is monitoring a person.
  • the monitoring subsystem 1 is configured to permit multiple different sensor types and/or methods to be fused together to form a more comprehensive patient monitoring system than conventional systems.
  • the patient monitoring system of some embodiments is reliable and highly accurate with a potentially tamper resistant design.
  • the sensor(s) 12 are used to detect patient(s) 13 and their outputs are fed into the processing unit(s) 10.
  • the system allows user(s) to assign predetermined conditions/inputs for the alert.
  • the processing unit(s) compares the sensor outputs and the processing outputs against the predetermined conditions/inputs and produce the alert signal 14 whenever specific conditions are met.
  • the system gathers monitoring data from the sensors 12, logs the data/activities, and reports to user(s) 20 and/or technician(s) 21 any abnormalities after comparing the sensed movement data with the predefined conditions.
  • the system is equipped with machine learning and/or an adaptation algorithm to improve the features and performance of the system over time.
  • the wireless communication subsystem 3 enables the different kinds of sensors 12 to be integrated and communication with the control unit 9, which acts as a control base for the sensor network.
  • the control unit 9 analyses the received data from the different sensors 12 and generates alert messages accordingly.
  • the wireless communication can be realised through different methods.
  • One choice in a smaller area would be ZigBee due to its low power consumption.
  • ZigBee is a reliable and an easily scalable wireless communication standard that can support multiple connected devices.
  • Bluetooth is well suited for use in a confined area. However, with Bluetooth the number of devices connected at one time maybe limited ⁇ typically 6 at a time). Bluetooth is therefore a viable option in a home setting where the number of monitoring devices is usually limited.
  • WiFi is another option which has advantages in terms of the distance range as well as the number of devices that can be connected to the control unit 9. Furthermore, WiFi supports high bandwidth communication between the connected devices. The downside to WiFi is that it generally consumes more power than the ZigBee standard. An appropriate wireless standard can be selected for the intended usage and the system can be configured accordingly so that the optimal performance is achieved from the monitoring system. This wireless communication provides remote configuration and access of sensor(s) and device ⁇ s) from a few location(s). Among many, some of these configurations are:
  • Sensitivity of the sensor(s) 12 is adjusted from the control unit 9
  • the alert system is acknowledged/disabled from specific sensor(s) without having to go to the control unit to deactivate it, and
  • the data/information from device(s) is logged at the control unit or dedicated location(s). While joining the existing wireless network, device(s) have built-in predetermined configuration(s) which may be used to discover or establish initial communication. During the initial communication, the device(s) configuration is preferably updated to integrate the device(s) into the monitoring system and for establishing subsequent communication.
  • the data processing that is performed by the control unit 9 includes motion pattern detection, fall prediction, fall identification etc. among many other parameters.
  • the control unit 9 receives the data frames from the sensor and/or the camera and performs image processing to extract out the human body from the surrounding environment. The data frame is then processed to identify the movement pattern of the body so that the control unit identifies when an abnormal condition occurs.
  • the system is configured to identify when the patient displays an erratic movement pattern or detect the fall pattern of the body so that the caregiver can be notified immediately.
  • FIG 5A This is depicted in figure 5A in which, an elderly person 13 is being monitored using a plurality of sensors 12 mounted in his two-room apartment.
  • Figure 5B depicts the system detecting that the elderly person 13 has fallen and the system outputting an alert message to a mobile telephone to notify a caregiver about the fall.
  • Figures 6A and 6B depict the system monitoring a high fall risk patient.
  • the system is configured to monitor the movement pattern of the person 13 when the person 13 is in bed.
  • an infrared sensor mounted on the wall monitors the person 13 in bed and sends a movement sensor signal to the control unit 9.
  • the control unit 9 is configured to alert a caregiver whenever the system detects or predicts that the person 13 tries to get out of bed and leave a predetermined area 32, as indicated in figure 6A.
  • the system enables a user to easily define boundary conditions which, when breached by a person moving out of a boundary condition cause the system to generate an alert signal.
  • the system is designed so that each movement sensor can be individually controlled form a remote location to enable a user to set personalised boundary conditions.
  • a motion detection algorithm implemented in the control unit 9 is configured to distinguish the conditions of multiple persons present from those when the person is alone in the bed by using pattern recognition.
  • the system is configured to temporarily disable the alarm automatically when multiple persons are detected. This prevents the system from burdening the caregiver and nurses from sounding an alarm even when they are positioned beside the patient.
  • the system is configured to re-activate the alert system when the system detects that the patient is alone again.
  • the image processing is made faster by using specialised devices such as infrared sensors in which most of the background information already filtered out.
  • the infrared sensor provides a heat map of the scenario in front of it so that the shape of the body of the person can be filtered out.
  • loT the Internet of Things
  • the loT is, for example used for turning off the lights or other electric appliances automatically when there is no human present or alerting a homeowner to the main door being unlocked when no one is at home etc.
  • the loT is sure to play a crucial part in the world in the coming decades in terms of enhancing security, making optimal use of resources and energy etc., among many other things.
  • the loT plays an important role in some embodiments of the present patient monitoring system.
  • the system uses loT technology to enable the individual movement sensors 12 to communicate with each other as well as the central station and coordinate their functions, as shown in figure 4.
  • the control unit 9 can instruct some of the movement sensors 12 to enter a sleep mode when a human presence is not detected in the area for a specified amount of time and instruct the movement sensors 12 to be active if otherwise. This helps to maximise the energy efficiency of the system, as well as the load and productivity of the detection algorithms. These embodiments therefore provide a smarter, more responsive and more accurate patient monitoring system.
  • other devices such as smartwatches
  • the other devices are integrated into the patient monitoring system to make the system more comprehensive, this enables the system to monitor patients who are more susceptible to drastic changes in the aforementioned physiological parameters.
  • the communication between the sensors and the control unit can be over a wired connection or by a wireless means. Wireless communication is, however, preferred since wireless communication is more convenient in terms of installation as well as the overall aesthetics of the monitoring system. In embodiments which are configured to use the loT for patient monitoring, remote monitoring is realisable when the control unit 9 is connected to the Internet.
  • control unit 9 is coupled to a cloud based storage that stores monitoring data output from the control unit 9 for recording purposes.
  • a caregiver can access the recorded data from the cloud storage or receive live monitoring data using his/her smartphone or tablet from a remote location.
  • the system is configured to enable a caregiver to view live monitoring data such as video and/or an infrared mapping at the patient's surroundings through this facility.
  • the embodiments described above are configured to use the loT technology to enable individual components of the system to function independently within the system and at the same time as a member device that is a part of a bigger patient monitoring system.
  • Another innovation is in the ability of the control unit to integrate with and receive data from third party physiological sensors to make the system more comprehensive with the ability to measure physiological properties of a person, such as heart rate, body temperature etc., and sound the alarm when any abnormality is detected.
  • the patient monitoring system has the capability to connect to any smart device such as smart phones or tablets and the system can be configured to send the alert to any such devices.
  • the system may also be configured such that some of these smart devices can act as master control devices that can send configuration commands to enable, disable, or acknowledge different alerts remotely.
  • the system can also have an automated mechanism to alert the authorities such as the civil defence department so that the patient is ensured immediate and proper care without any delay. Alert subsystem
  • the alert mechanism subsystem 6 is an integral part of the patient monitoring system. Once the sensor data is collected from the movement sensors, the data is processed by the control unit and a conclusion is reached by the control unit that the situation warrants informing a caregiver, the system activates the alert mechanism.
  • Embodiments are configured to use one or more of many methods to output the alert, for instance the alert can be based on an alarm sound, light indicator or SMS that is communicated to the caregiver. Those of skill in the art will appreciate that the system can use a combination of different types of alerts.
  • control unit comprises a loudspeaker module to generate an alarm sound.
  • This type of alert is preferable in a home or hospital setting with a high-fall risk patient.
  • the caregiver or nurse In the case of a high-fall risk patient, the caregiver or nurse must be notified immediately when the patient gets out of bed.
  • An alarm sound is one of the simplest and best ways to provide an immediate alert that so that the caregiver or nurse can attend to the patient quickly and prevent a potential fall.
  • a light indicator module is carried by the control unit or at one of the movement sensors to acts as an alert mechanism, for instance when the caregiver at a distance from the patient.
  • a light indicator module is especially useful in a hospital setting where there might be multiple monitoring sensors mounted to monitor the patients.
  • an alarm sound is effective in alerting a caregiver to a patient situation
  • an alarm sound can be limited in terms of pin-pointing the location of the source.
  • a light indicator module is provided in some embodiments to act as a complementary mechanism to guide the caregiver to the correct bed so that the assistance can be provided to the patient without any further delay.
  • an SMS alert may be necessary.
  • the caregiver may not be the patient's home at all times. Consequently, whenever an abnormality is detected in the sensor outputs, it is critical to inform the caregiver at the earliest opportunity so that the patient is attended to in the shortest time possible.
  • the control unit is equipped with a mobile network data communication module, such as a GSM module, which is configured to send an alert SMS to multiple predefined phone numbers at frequent intervals to alert the caregiver and, if necessary, even the emergency services.
  • a combination of different alert mechanisms may also be necessary in some cases if the patient is not attended to within a set amount of time.
  • the alert mechanism is highly customizable to provide an alert any number of smart devices and each alert can be individually configured according to the user preference. For example, to provide an alert to close relatives that may require a different set of information/alarm tone than an alert provided to a doctor/nurse. Similarly, some embodiments are configured to provide a different alert message to the emergency services that contain a different set of information from alert messages sent to close relatives or to a doctor/nurse.
  • the system is configured to enable a user to be designated as a master user. In this case, he/she is able to control the alert frequency and/or other parameters such that subsequent alerts can be disabled/acknowledged remotely using SMS/text based commands to the control unit or to a smart phone app.
  • individual movement sensors have the capability to generate their own alerts when necessary; for example, when the sensor does not receive a response from the control unit. This alert can be in the form of sound and/or light alarms to get the attention of persons near to the patient, or even neighbours in the case of a patient in a home monitoring setting.
  • the alert mechanism is configured to make use of multiple means for delivering the alert message. If there is no Internet connectivity, the system's built-in intelligence would use the GSM network and send SMS texts as a backup and vice versa. In some embodiments, the alert system also has the built-in capability to notify a technical team and provide the necessary data to the technical team when something goes wrong internally in the monitoring system so that they can solve the issue within the shortest time.
  • the system comprises data logging subsystem to record and store the data from the sensor outputs as well as the processed data for referencing and report generation.
  • a database becomes another important part of the patient monitoring system. There are multiple user groups in the patient monitoring system; customers, providers and the technical team. The database inputs for each of these customer segments are preferably customised accordingly so that the data is useful for them.
  • the data to be logged for this user group is the time and date of each alert, the type of alert, which sensor generated the alert etc.
  • the report generated for this use group includes the frequency of alert, analysis on which sensor generated the most number of alert, and any pattern in terms of the occurrence of alert (for e.g., whether any particular time of the day involves more alerts than others so that they can adjust to the patient's behaviour pattern so as to prevent any potential fall).
  • the user group of providers are those in hospital settings such as nurses and physicians who are in charge of the patients under their care. Typically, there would be a large number of patients, including those under high fall risk category.
  • the data that is logged includes the alert timestamp and their alert type for each patient individually. This makes it easier for the data analysis and report generation part at the later stage.
  • the report again includes the alert frequency for individual patients so that it would be easier for them to identify which patients to focus more so that a potential fall can be prevented.
  • the report includes the behaviour pattern of patients so that the hospital staff can adjust their workflow so that their resources are optimally used in order to provide the best quality of care to the patients.
  • the technical team user group includes those in charge of the maintenance of the patient monitoring system. On top of the aforementioned data, this user group needs a different set of data in order to understand the system performance and identify the cause of the breakdown when such things occur.
  • the data to be logged includes the alert timestamp as well as any other abnormal data generated from each individual sensor. This log will also include any error signal generated by the system as well.
  • the report generated for this use group will include more details on the different individual sensor readings, abnormal readings, errors generated, together with the timestamps of each entry.
  • Figure 7 shows an example of the data logging and report generation functionality of the system described above for individual user groups in the patient monitoring system.
  • the database is uploaded to a cloud based server so that users can have access to the data from wherever they are, preferably using password authentication.
  • the user can also query the data with a text based instructions from their smart devices, as long as the user passes the authentication test from the server.
  • the server is configured to provide real-time data to the users whenever requested, in case they have difficulty connecting to the monitoring system directly.
  • the cloud based server which contains information from data from multiple patient monitoring system, is able to provide a compiled report to a technical team on a scheduled basis.
  • the report preferably indicates the performance of the components of the patient monitoring system, including any issues faced by any of the member systems and how frequently the issues were reported.
  • the report preferably also indicates whether any component of the monitoring system is behaving abnormally and whether the control unit or any of the member devices need replacing in the near future.
  • An overview of the access differences between different user groups is shown in figure 8. In this example, there are a plurality of patient monitoring systems which each has its own local database storage capacity. In parallel, the data is also sent to the cloud based server. This highly secured cloud based server is only accessible by the technical support user group for maintenance and other purposes.
  • the home based or hospital based caregiver is allowed access to the local system and its database through any locally connected computers or remotely configured smart devices such as smartphones or tablets to acknowledge the alarm as well as to make queries to the database to learn about the real time monitoring as well as physiological data, in case a third party sensor is connected.
  • Calibration subsystem
  • a sensor typically requires proper calibration to ensure that it detects/measures a signal reliably and accurately.
  • a novel method is now proposed for calibrating an infrared sensor, such as the infrared sensor of the embodiments described above.
  • the calibration method involves placing a calibration element or object 33 with a uniform body temperature being placed over the sensor aperture 34 of a sensor 35.
  • the object 33 with a uniform body temperature is, for example, a sheet of paper or card board with uniform colour.
  • the required calibration adjustment value(s) are calculated automatically such that the sensor output is uniform throughout the frame.
  • the calibration value(s) are stored and applied in the subsequence processing step.
  • the calibration value(s) are also used to determine the sensor conditions in terms of their functional performance and reliability.
  • the calibration value(s) also indicate the condition of the sensor and can be used to provide recommendations on changing or replacing the sensor whenever necessary.
  • the sensor calibration method ensures that the temperature difference of a human body relative to a background scene is captured accurately. This in turn ensures that the algorithm applied by the control unit is reliable while monitoring the patient(s)/ subject(s).
  • the entire calibration process is extremely quick and it can be done within a very short period of time (in terms of a few seconds). Furthermore the result of the calibration is immediately visible on the data output with a more clearly defined temperature gradient for different objects in the screen. This simplifies the entire process in identifying the desired patterns and in processing the rendered thermal image so as to reach the necessary conclusions on the patient's posture, thereby increasing the reliability and accuracy of the processing.
  • a sample report for a home based caregiver is shown in figure 10.
  • a user is able to select the dates for the query and the results will be displayed in the report together with a chart.
  • the chart is customisable to show different patterns of alarm activation and the patient's behaviour based on day, time, and a particular sensor.
  • the overall system is built into an integrated embedded platform which enables the components of the system to be compact in size and faster at processing data. This enables the system to be cheaper to manufacture and also enhances its overall reliability. As an embedded system, it will require much less power compared to normal, non-embedded systems.
  • one further advantage that embedded system presents is the compactness of the hardware.
  • the compact size of components of the embedded system appeals to different user groups because it becomes easier to mount different kinds of sensors to the ceilings, walls or bedframes.
  • the control unit also occupies minimal space.
  • An overview of an embedded system of some embodiments of the patient monitoring system is shown in figure 11.
  • the control unit is housed within a small enclosure which is comparable to the size of a regular matchbox but which has all the necessary processing and communication capability built into it as an embedded system.
  • the control unit is configured to run on battery power for a long time, based on the user pattern.
  • the control unit is also easily replaced in case of emergency by simply changing the memory and/or processing platform of the control unit.
  • a technician can also move the monitoring system to a remote location, work on the monitoring system and bring it back to the location where it is being used to monitor a patient.
  • the movement sensors or member devices can also be replaced easily by exchanging the processing unit in each device.
  • the at least one sensor is embedded in part of the control unit. In other embodiments, the at least one sensor is embedded with functions, parts, and/or modules of the control unit.

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Abstract

La présente invention concerne un système, un réseau et un procédé associés de surveillance de patient comprenant : une unité de commande (9); une mémoire, ladite mémoire mémorisant des données de mouvement prédéfinies comprenant : des premières données de mouvement qui indiquent un état sans danger et/ou des secondes données de mouvement qui indiquent un état dangereux; au moins un capteur (12) de mouvement qui fournit un signal de sortie à l'unité de commande (9), ladite unité de commande (9) traitant le signal de sortie et générant des données de mouvement détectées et comparant les données de mouvement détectées aux données de mouvement prédéfinies et générant un signal d'alerte (14) pour indiquer un état dangereux si les données de mouvement détectées ne correspondent pas à au moins une partie des premières données de mouvement et/ou si les données de mouvement détectées correspondent à au moins une partie des secondes données de mouvement. Dans un autre aspect de l'invention, celle-ci concerne un procédé d'étalonnage d'un capteur.
PCT/SG2017/000004 2016-02-23 2017-02-20 Système de surveillance de patient WO2017146643A1 (fr)

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