Detection and identification of a human from characteristic signals

Patent metadata

Field	Value
Publication number	US-11092685-B2
Application number	US-202015930893-A
Country	US
Kind code	B2
Filing date	May 13, 2020
Priority date	Apr 20, 2015
Publication date	Aug 17, 2021
Grant date	Aug 17, 2021

Abstract

One or more sensors are configured for detection of characteristics of moving objects and living subjects for human identification or authentication. One or more processors, such as in a system of sensors or that control a sensor, may be configured to process signals from the one or more sensors to identify a person. The processing may include evaluating features from the signals such as breathing rate, respiration depth, degree of movement and heart rate etc. The sensors may be radio frequency non-contact sensors with automated detection control to change detection control parameters based on the identification of living beings, such as to avoid sensor interference.

First claim

The invention claimed is:

1. A physiological parameter monitoring system adapted to identify a person for monitoring of the identified person's physiological parameters, the system including:
one or more sensors for monitoring one or more persons' physiological parameters comprising a cardiac parameter, and
one or more processors, the one or more processors configured to process signals from the one or more sensors to identify a person according to an evaluation of a biometric signature, the processing comprising an evaluation of parameters comprising the cardiac parameter, wherein the one or more processors are further configured to determine one or more settings for a respiratory therapy device based on the evaluation of the biometric signature.

2. The system of claim 1 wherein the one or more persons' physiological parameters further comprise one or both of respiratory parameters and movement parameters.

3. The system of claim 1 , wherein the monitoring comprises detection of physiological characteristics of the person during sleep, wherein the processing comprises one or more of (a) detection of sleep stages of the person, (b) detection of deep sleep of the person, and (c) detection of REM sleep of the person.

4. The system of claim 1 wherein the monitoring comprises detection of physiological characteristics during awake time of the person.

5. The system of claim 1 wherein the one or more sensors comprises any one or more of:
a radio frequency non-contact sensor;
a biomotion sensor
a sensor of the respiratory therapy device; and
a wearable sensor.

6. The system of claim 1 wherein the respiratory therapy device comprises apparatus configured to supply pressurised air to airways of the person, wherein the apparatus comprises a motor-driven blower or a compressed gas reservoir.

7. The system of claim 6 wherein the respiratory therapy device is positive airway pressure device.

8. The system of claim 7 wherein the respiratory therapy device is an adaptive servo ventilation device.

9. The system of claim 1 wherein the one or more processors is configured to evaluate the cardiac parameter to adjust a respiratory therapy provided by the respiratory therapy device.

10. The system of claim 9 wherein the one or more processors is configured to adjust the respiratory therapy upon detecting an elevated heart rate.

11. The system of claim 10 wherein the one or more processors is configured to re-train for identification of the person if biometric characteristics evaluated in the identification are treated by the respiratory therapy device.

12. The system of claim 10 wherein the one or more processors is configured to track heart rate, variation in heart rate, and/or trends in heart rate dynamics and breathing rate dynamics.

13. The system of claim 11 , wherein the one or more sensors are configured to gather heart rate data from the person when therapy is being provided to the person by the respiratory therapy device and when therapy is not being provided to the person by the respiratory therapy device.

14. The system of claim 1 wherein the one or more processors further comprises a control processor in communication with the one or more sensors, the control processor configured to communicate with the one or more sensors to adjust one or more detection control parameters of the one or more sensors based on an identification of the person.

15. The system of claim 1 wherein the evaluation comprises classification of parameters determined from the signals, the parameters comprising a plurality of:
a spectral peak ratio;
a set up Optimiser flag vector;
a peak trough ratio;
a filtered respiration rate;
a breathing variability measure;
an in-band power of a sensor signal;
a range of a sensor signal;
a final respiration rate;
a ratio of maximum to minimum amplitude of a breathing cycle;
a high band power for a sensor signal;
a mean respiration rate;
a periodic leg movement activity detection;
a detection of turnover; and
a post-processed movement.

16. The system of claim 1 wherein the evaluation comprises classification of parameters determined from the signals, the determined parameters including the cardiac parameter and one or more of: a galvanic skin response parameter, an exercise intensity parameter, a respiration parameter, a blood pressure parameter, a coughing parameter, a snoring parameter, and a sleep parameter.

17. The system of claim 16 wherein the evaluation comprises a comparison of the determined parameters with historic parameters.

18. The system of claim 17 wherein the evaluation further comprises calculating mean and/or standard deviation values for a period of time from the determined parameters.

19. The system of claim 1 wherein the one or more processors is further configured to permit or deny a therapy operation by the respiratory therapy device based on the evaluation of the biometric signature.

20. The system of claim 1 wherein the one or more processors is configured to classify a user's identity from parameters determined in a classification process.

21. The system of claim 20 wherein the classification process comprises any one or more of a neural network, a hidden layer Markov model, logistic regression processing, linear kernel support vector machine, radial kernel support vector machine and Principal Component Analysis on the parameters prior to classification.

22. A method of one or more processors of a physiological parameter monitoring system adapted to identify a person for monitoring of the identified person's physiological parameters, the method comprising:
receiving from one or more sensors one or more monitored physiological parameters of a person, the monitored physiological parameters comprising a cardiac parameter;
processing signals from the one or more sensors to identify a person according to an evaluation of a biometric signature, the processing comprising evaluating monitored parameters comprising the cardiac parameter; and
determining one or more settings for a respiratory therapy device based on the evaluation of the biometric signature.

23. A non-transitory processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to identify a person for monitoring physiological parameters of one or more persons, the processor-executable instructions comprising:
instructions to access from one or more sensors one or more monitored physiological parameters of a person, the monitored physiological parameters comprising a cardiac parameter;
instructions to process signals from the one or more sensors to identify a person according to an evaluation of a biometric signature, the processing comprising evaluating monitored parameters comprising the cardiac parameter; and
instructions to determine one or more settings for a respiratory therapy device based on the evaluation of the biometric signature.

Assignees

• Resmed Sensor Tech Ltd

Inventors

• Shouldice Redmond
• Doheny Emer
• Zaffaroni Alberto

Classifications

• G06V40/00

  Recognition of biometric, human-related or animal-related patterns in image or video data · CPC title

• A61B5/117

  Identification of persons (methods or arrangements for recognising patterns, e.g. fingerprints, G06F18/00, G06V40/00; identification of persons by analysing their voice or speech G10L17/00) · CPC title

• G01S13/88

  Radar or analogous systems specially adapted for specific applications (electromagnetic prospecting or detecting of objects, e.g. near-field detection, G01V3/00) · CPC title

• G01S13/87

  Combinations of radar systems, e.g. primary radar and secondary radar · CPC title

• G01S13/56 Primary

  for presence detection {(presence detection using near field arrangements G01V3/00, e.g. G01V3/08, G01V3/12; burglar, theft or intruder alarms with electrical actuation G08B13/22 - G08B13/26)} · CPC title