APPARATUS, SYSTEM, AND METHOD FOR MONITORING PHYSIOLOGICAL SIGNS

• US 20140163343A1
• Filed: 09/17/2013
• Published: 06/12/2014
• Est. Priority Date: 06/01/2006
• Status: Active Grant

• Current Assignee: ResMed Sensor Technologies Limited (ResMed Incorporated)
• Original Assignee: ResMed Sensor Technologies Limited (ResMed Incorporated)
• Inventors: Heneghan, Conor, Hanley, Conor, Fox, Niall, De Chazal, Philip
• Granted Patent: US 10,729,332 B2
• Time in Patent Office: Days
• US Class Current: 600/324
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0507 using microwaves or terahertz waves
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

An apparatus, system, and method monitors the motion, breathing, heart rate and sleep state of subjects, e.g., humans, in a convenient, non-invasive/non-contact, and low-cost fashion. More particularly, the motion, breathing, and heart rate signals are obtained through processing applied to a raw signal obtained in a non-contact fashion, typically using a radio-frequency sensor. Periods of sleep disturbed respiration, or central apnea can be detected through analysis of the respiratory signal. The mean heart rate, and derived information, such as the presence of cardiac arrhythmias can be determined from the cardiac signal. Motion estimates can be used to recognize disturbed sleep and periodic limb movements. The sleep state may be determined by applying a classifier model to the resulting streams of respiratory, cardiac and motion data. A means for display of the sleep state, respiratory, cardiac, and movement status may also be provided.

Claims

1. A system for monitoring a subject, the system comprising:

at least one sensor configured to output a first output signal comprising a respiratory signal, a cardiac signal, and a motion signal, and

a processor configured to analyze the first output signal to derive a plurality of physiological features,

wherein the processor is configured to selectively combine the plurality of physiological features to monitor the subject'"'"'s health.

2. The system of claim 1 further comprising an output configured to output at least one of the plurality of physiological features.

3. The system of claim 2, wherein the physiological features are selected from the group consisting of:

breathing rate, periodic breathing, an amplitude of breathing, an apnea-hypopnea index, an absence of respiration, dominant respiratory frequency, respiratory power, heart rate, blood pressure, a variability of heart rate, a blood oxygen level, a motion profile, sleep state, and sleep efficiency.

4. The system of claim 1, wherein the at least one sensor comprises a radio frequency (RF) sensor configured to receive reflected RF signals off the subject.

5. The system of claim 1, wherein the first output signal is derived by mixing at least two quadrature signals.

6. The system of claim 1, wherein the processor calculates an amplitude of the respiratory signal.

7. The system of claim 6, wherein the processor determines periodic respiratory patterns by analyzing at least one of the plurality of physiological features.

8. The system of claim 1, wherein the processor is configured to determine a characteristic time period of periodic breathing using at least one of the plurality of physiological features.

9. The system of claim 1, further comprising at least one additional sensor configured to output additional signals indicating environmental parameters.

10. The system of claim 1, wherein the processor is configured to determine sleep state of the subject by analyzing the motion signal.

11. The system of claim 1, wherein the processor is configured to recognize a distress condition of the subject by comparing the derived physiological features with an existing set of physiological features.

12. The system of claim 1, wherein the subject'"'"'s health is monitored over an extended period of time.

14. The method of claim 12, further comprising obtaining at least one environmental parameter using at least one additional sensor.

15. The method of claim 12, further comprising outputting at least one of the plurality of the plurality of respiratory features, the plurality of cardiac features, or bodily motion.

13. A computer-implemented method for monitoring a subject, the method comprising:

obtaining a signal reflected from the subject using at least one sensor;

generating, with a processor, a plurality of respiratory features, a plurality of cardiac features, and bodily motion derived from the signal;

selectively combining the plurality of respiratory features, the plurality of cardiac features, and the bodily motion to monitor the subject'"'"'s health.

16. A computer-implemented method for monitoring for a distress condition of a monitored subject, the method comprising:

calculating for a first time period, one or more parameters selected from the group consisting of a respiratory rate of a subject, incidence of apneas and hypopneas, an amplitude of the respiratory signal, and a period of periodic breathing selected from the group consisting of a respiratory rate of a subject, incidence of apneas and hypopneas, an amplitude of the respiratory signal, and a period of periodic breathing;

calculating for a second time period after the first time period, said one or more parameters selected from said group;

comparing said calculated one or more parameters from the first time period with said calculated one or more parameters from the second time period to obtain a comparison result; and

determining the monitored subject'"'"'s health based on the comparison result.

17. A system for monitoring a subject, comprising:

a processor coupled to a memory,

the memory having instructions that, when executed by the processor, perform the steps of;

receiving a first signal comprising a respiratory signal, a cardiac signal, and a motion signal, and

analyzing the first signal to derive a plurality of physiological features, and

selectively combining the plurality of physiological features to monitor the subject'"'"'s health.

18. The system of claim 17, further comprising an output configured to output at least one of the plurality of physiological features.

19. The system of claim 18, wherein the physiological features are selected from the group consisting of:

breathing rate, periodic breathing, an amplitude of breathing, an apnea-hypopnea index, an absence of respiration, dominant respiratory frequency, respiratory power, heart rate, blood pressure, a variability of heart rate, a blood oxygen level, a motion profile, sleep state, and sleep efficiency.

20. The system of claim 17, wherein the first signal is derived by mixing at least two quadrature signals.

21. The system of claim 17, wherein the memory further comprises instructions for calculating an amplitude of the respiratory signal.

22. The system of claim 21, wherein the memory further comprises instructions for determining periodic respiratory patterns by analyzing at least one of the plurality of physiological features.

23. The system of claim 17, wherein the memory further comprises instructions for determining a characteristic time period of periodic breathing using at least one of the plurality of physiological features.

24. The system of claim 17, wherein the memory further comprises instructions for receiving at least one additional sensor signal indicating environmental parameters.

25. The system of claim 17, wherein the memory further comprises instructions for determining sleep state of the subject by analyzing the motion signal.

26. The system of claim 17, wherein the memory further comprises instructions for recognizing a distress condition of the subject by comparing the derived physiological features with an existing set of physiological features.

27. The system of claim 17, wherein the subject'"'"'s health is monitored over an extended period of time.