Non-contact diagnosis and monitoring of sleep disorders

Patent metadata

Field	Value
Publication number	US-2018353138-A1
Application number	US-201615778511-A
Country	US
Kind code	A1
Filing date	Dec 8, 2016
Priority date	Dec 8, 2015
Publication date	Dec 13, 2018
Grant date	—

Abstract

A sensor may be configured to detect periodic limb movement in a sleeping person. The sensor may be a non-contact sensor, such as a radar motion sensor. The sensor may include a radio frequency transmitter for emitting radio frequency signals toward the person. The sensor may include a receiver for receiving reflected ones of the emitted radio frequency signals and processing the reflected ones of the emitted radio frequency signals to produce motion signal(s). A processor, such as one integrated with or coupled to the sensor, may evaluate the motion signals, such as in-phase and quadrature motion signals, and generate an indicator to identify occurrence of periodic limb movement in the motion signals based on the evaluation of the motion signals.

First claim

1 . A radio frequency motion sensing apparatus for detection of periodic limb movement in a sleeping person, the apparatus comprising:
a radio frequency transmitter configured to emit radio frequency signals; a receiver configured to:
receive reflected ones of the emitted radio frequency signals, and
process the received reflected ones of the emitted radio frequency signals to produce motion signals; and
a processor configured to:
evaluate the motion signals; and
generate an indicator to identify occurrence of periodic limb movement in the motion signals based on the evaluation of the motion signals.

2 . The apparatus of claim 1 wherein the receiver is configured to mix the received radio frequency signals with the emitted signals to produce the motion signals.

3 . The apparatus of any one of claims 1 to 2 wherein the processor is configured to measure a phase difference between the received radio frequency signals and the emitted signals.

4 . The apparatus of any one of claims 1 to 3 wherein the motion signals comprise in-phase and quadrature motion signals.

5 . The apparatus of any one of claims 1 to 4 wherein the emitted radio frequency signals comprise pulsed radio frequency oscillating signals.

6 . The apparatus of any one of claims 1 to 5 wherein the evaluation comprises comparing the motion signals to a noise threshold.

7 . The apparatus of claim 4 wherein portions of the in-phase and quadrature motion signals are compared to a noise threshold.

8 . The apparatus of any one of claims 6 to 7 further comprising updating an action counter based on the comparing.

9 . The apparatus of claim 8 further comprising increasing the action counter when a portion of the motion signal is greater than the noise threshold.

10 . The apparatus of any one of claims 8 to 9 further comprising decreasing the action counter when a portion of the motion signal is less than the noise threshold.

11 . The apparatus of any one of claims 6 to 10 wherein the noise threshold is defined as a frequency range in-band power of noise of the motion signal.

12 . The apparatus of claim 11 wherein the frequency range comprises a range of four Hertz to eight Hertz.

13 . The apparatus of any one of claims 6 to 12 further comprising updating the noise threshold based on determined average noise of the motion signals.

14 . The apparatus of any one of claims 1 to 13 wherein the processor is configured to detect a movement incident based on a comparison of a determined action count and a count threshold.

15 . The apparatus of claim 14 wherein the processor is configured to determine a velocity of the movement incident.

16 . The apparatus of claim 15 wherein the processor determines the velocity based on a difference between the phase of the motion signals at adjacent samples.

17 . The apparatus of claim 16 wherein the processor determines displacement based on the determined velocity.

18 . The apparatus of claim 17 wherein the processor determines mean displacement from absolute values of determined velocities.

19 . The apparatus of any one of claims 14 to 18 wherein the processor characterizes the movement incident based on a determined mean displacement of the movement incident.

20 . The apparatus of claim 19 wherein the processor generates a mapped activity value from the mean displacement.

21 . The apparatus of any one of claims 1 to 20 wherein the evaluation comprises calculating and assessing a plurality of features derived from the motion signals.

22 . The apparatus of claim 21 wherein the plurality of features comprises at least one of the following:
a duration of a movement incident; a total activity of a detected movement incident; a mapped total activity of a detected movement incident; a cross-correlation of in-phase and quadrature motion signals of the motion signals during a detected movement incident; and a mean of a four quadrant inverse tangent function of real parts of in-phase and quadrature motion signals of the motion signals during a detected movement incident.

23 . The apparatus of any one of claims 21 to 22 wherein the assessing comprises logistic regression and the indicator comprises a probability value representing a likelihood of periodic limb movement during sleep.

24 . The apparatus of any one of claims 1 to 23 , wherein to evaluate the motion signals, the processor is configured to:
partition the motion signals into breath sections;
classify each breath section of the motion signals as containing a limb movement or not containing a limb movement; and
generate the indicator based on the classified breath sections.

25 . The apparatus of claim 24 , wherein the processor is further configured to pre-process the motion signals before the partitioning to de-trend and smooth the motion signals.

26 . The apparatus of any of claims 24 to 25 , wherein the processor is further configured to combine the motion signals to form a combined signal.

27 . The apparatus of claim 26 , wherein the processor is configured to perform principal component analysis to combine the motion signals.

28 . The apparatus of any of claims 26 to 27 , wherein the processor is further configured to discard periods of absence from the combined signal before the partitioning.

29 . The apparatus of any one of claims 26 to 28 , wherein the processor is configured to detect zero-crossings of the combined signal to perform the partitioning.

30 . The apparatus of any one of claims 24 to 29 , wherein the processor is configured to extract a waveform length feature from each breath section to perform the classifying.

31 . The apparatus of any one of claims 24 to 30 , wherein to generate the indicator, the processor is configured to score the breath sections containing limb movements as part of a periodic limb movement (PLM) series according to scoring criteria.

32 . The apparatus of claim 31 , wherein to generate the indicator, the processor is configured to count limb movements forming part of a PLM series from a night's sleep session.

33 . A method for detecting periodic limb movement by a sleeping person comprising:
emitting, by a radio frequency transmitter, radio frequency signals toward the person; receiving, by a receiver, reflected ones of the emitted radio frequency signals, processing, by the receiver, the reflected ones of the emitted radio frequency signals to produce motion signals; and evaluating, by a processor, the motion signals and generating an indicator to identify occurrence of periodic limb movement present in the motion signals based on the evaluation of the motion signals.

34 . The method of claim 33 wherein the received radio frequency signals are mixed with emitted signals to produce the motion signals.

35 . The method of any one of claims 33 to 34 wherein the processor measures a phase difference between the received radio frequency signals and the emitted signals.

36 . The method of any one of claims 33 to 35 wherein the motion signals comprise in-phase and quadrature motion signals.

37 . The method of any one of claims 33 to 36 wherein the emitted radio frequen

Assignees

• Resmed Ltd
• Resmed Sensor Tech Ltd

Inventors

• Doheny Emer
• Gahan Luke
• Khushaba Rami
• O'Hare Emer
• Zaffaroni Alberto

Classifications

• A61B5/113

  occurring during breathing · CPC title

• A61B5/05

  Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves (measuring movement of the entire body or parts thereof A61B5/11; detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof A61B5/24) · CPC title

• A61B5/4818

  Sleep apnoea · CPC title

• A61B5/1113

  Local tracking of patients, e.g. in a hospital or private home · CPC title

• A61B5/7264

  Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems · CPC title