HEALTH MONITORING, SURVEILLANCE AND ANOMALY DETECTION

• US 20140276167A1
• Filed: 03/14/2014
• Published: 09/18/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Zansors LLC
• Original Assignee: Zansors LLC
• Inventors: Dasgupta, Abhijit, Das, Ranjit
• Granted Patent: US 10,219,753 B2
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 2503/04 Babies, e.g. for SIDS detection
• CPC Class Codes: A61B 2505/09 Rehabilitation or training
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• 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 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4806 Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/6822 Neck
• CPC Class Codes: A61B 5/6833 Adhesive patches
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A wearable patch and method for automatically monitoring, screening, and/or reporting events related to one or more health conditions (e.g., sleeping or breathing disorders, physical activity, arrhythmias) of a subject.

Claims

1. A method of wirelessly monitoring a condition of a subject, said method comprising:

wirelessly capturing, at a processor, a first signal indicative of the condition over a first period of time;

removing, at the processor, noise from the captured first signal to create a second signal indicative of the condition;

computing, at the processor, a plurality of moving averages of the second signal using a temporal window defining a second period of time; and

determining if there has been an event associated with the condition within any of the temporal windows as determined by moving averages.

2. The method of claim 1, wherein the first signal is captured at a first frequency and said method further comprises the act of down-sampling the captured first signal to a second lower frequency.

3. The method of claim 1, wherein said step of removing noise from the captured first signal comprises:

estimating the noise over a period of time; and

subtracting the estimated noise from the captured first signal.

4. The method of claim 3, wherein the noise is estimated by filtering out portions of the first signal having an intensity less than twice a standard deviation of a distribution of signal intensity captured over a period of time.

5. The method of claim 1, wherein said condition comprises a breathing condition and said first signal is a breathing signal.

6. The method of claim 5, wherein said event comprises an apneic event.

7. The method of claim 5, wherein said event comprises an apneic event and said determining step comprises detecting a moving average indicative of no breathing during the window that the moving average was computed.

8. The method of claim 1, further comprising the act of counting a number of events to determine a severity of the condition.

9. The method of claim 8, wherein said condition comprises a breathing condition, the event comprises and apneic event and the severity of the condition comprises one of mild, moderate or severe sleep apnea.

12. The method of claim 1, wherein said step of removing noise from the captured first breathing signal comprises:

estimating the noise over a period of time; and

subtracting the estimated noise from the captured first breathing signal.

13. The method of claim 12, wherein the noise is estimated by filtering out portions of the first breathing signal having an intensity less than twice a standard deviation of a distribution of signal intensity captured over a period of time.

14. The method of claim 12, wherein the estimated noise comprises one of ambient or background noise.

10. A method of wirelessly monitoring a breathing condition of a subject, said method comprising:

providing a wireless device on the subject, said wireless device comprising a processor;

wirelessly capturing, at the processor, a first breathing signal of the subject continuously over a first period of time;

removing, at the processor, noise from the captured first breathing signal to create a second breathing signal;

computing, at the processor, a plurality of moving averages of the second breathing signal using a temporal window defining a second period of time; and

determining if there has been an event associated with the breathing condition within any of the temporal windows as determined by computed moving averages.

11. The method of claim 10, wherein the first breathing signal is captured at a first frequency and said method further comprises the act of down-sampling the captured first breathing signal to a second lower frequency.

15. The method of claim 10, wherein said event comprises an apneic event.

16. The method of claim 15, wherein said event comprises an apneic event and said determining step comprises computing a moving average indicative of no breathing during the window that the moving average was computed.

17. The method of claim 10, further comprising the act of counting a number of events to determine a severity of the condition.

18. The method of claim 17, wherein the event comprises and apneic event and the severity of the condition comprises one of mild, moderate or severe sleep apnea.