Actigraphy methods and apparatuses

Patent metadata

Field	Value
Publication number	US-9820698-B2
Application number	US-201514934255-A
Country	US
Kind code	B2
Filing date	Nov 6, 2015
Priority date	Nov 7, 2014
Publication date	Nov 21, 2017
Grant date	Nov 21, 2017

Abstract

An actigraphy method includes receiving a physiological parameter signal as a function of time for a physiological parameter other than body motion (such as electrocardiography or a respiration monitor), computing a body motion artifact (BMA) signal as a function of time from the physiological parameter signal (for example, using a local signal power signal, a local variance signal, a short-time Fourier transform, or a wavelet transform over epochs of duration on order a few minutes or less), and computing an actigraphy signal as a function of time from the BMA signal, for example by applying a linear transform to the BMA signal and optionally applying filtering such as median removal and/or high-pass filtering.

First claim

The invention claimed is:

1. A physiological monitoring device comprising:
a sensor configured to generate a non-body motion physiological parameter signal as a function of time for a physiological parameter other than velocity, displacement, and acceleration; and
an electronic digital signal processing (DSP) device configured to perform operations including:
computing a body motion artifact (BMA) signal as a function of time from the non-body motion physiological parameter signal, and
computing an actigraphy signal as a function of time from the BMA signal.

2. The physiological monitoring device of claim 1 wherein the sensor includes an electrocardiography (ECG) sensor and the physiological parameter includes one or more of (i) at least one ECG trace and (ii) a heart rate.

3. The physiological monitoring device of claim 1 wherein the sensor includes a respiratory sensor and the physiological parameter includes a respiration rate.

4. The physiological monitoring device of claim 1 wherein the sensor includes a Respiratory Inductive Plethysmography (RIP) sensor.

5. The physiological monitoring device of claim 1 wherein computing a BMA signal as a function of time from the non-body motion physiological parameter signal comprises computing a local signal power signal from the non-body motion physiological parameter signal.

6. The physiological monitoring device of claim 1 wherein computing a BMA signal as a function of time from the non-body motion physiological parameter signal comprises computing a local signal variance signal from the non-body motion physiological parameter signal.

7. The physiological monitoring device of claim 1 wherein computing a BMA signal as a function of time from the non-body motion physiological parameter signal comprises computing a Short-Time Fourier Transform (STFT) signal from the non-body motion physiological parameter signal.

8. The physiological monitoring device of claim 1 wherein computing a BMA signal as a function of time from the non-body motion physiological parameter signal comprises computing a wavelet transform signal from the non-body motion physiological parameter signal.

9. The physiological monitoring device of claim 1 wherein computing a BMA signal as a function of time from the non-body motion physiological parameter signal comprises computing a BMA signal sample for each time window of a succession of time windows of the non-body motion physiological parameter signal.

10. The physiological monitoring device of claim 9 wherein the succession of time windows is a succession of overlapping Hamming time windows.

11. The physiological monitoring device of claim 1 wherein computing an actigraphy signal as a function of time from the BMA signal comprises applying a linear transform to the BMA signal.

12. The physiological monitoring device of claim 1 wherein the DSP device is configured to perform further operations including:
filtering the actigraphy signal using a median removal filter.

13. The physiological monitoring device of claim 1 wherein the DSP device is configured to perform further operations including:
filtering the actigraphy signal using a high pass filter.

14. A non-transitory storage medium storing instructions readable and executable by an electronic data processing device to perform a physiological monitoring method comprising:
computing a body motion artifact (BMA) signal comprising one of a local signal power signal, a local signal variance signal, a Short-Time Fourier Transform (STFT) signal, and a wavelet transform signal as a function of time from a non-body motion physiological parameter signal as a function of time for a physiological parameter other than displacement, acceleration, and velocity wherein a BMA signal sample is computed for each time window of a succession of time windows; and
computing an actigraphy signal as a function of time from the BMA signal.

15. The non-transitory storage medium of claim 14 , wherein the operation of computing a BMA signal as a function of time from the non-body motion physiological parameter signal comprises one of:
computing a local signal variance signal from the non-body motion physiological parameter signal;
computing a Short-Time Fourier Transform (STFT) signal from the non-body motion physiological parameter signal; and
computing a wavelet transform signal from the non-body motion physiological parameter signal.

16. The non-transitory storage medium of claim 14 , wherein the operation of computing a BMA signal as a function of time from the non-body motion physiological parameter signal comprises computing a BMA signal sample for each time window of a succession of time windows of the non-body motion physiological parameter signal.

17. The non-transitory storage medium of claim 14 , wherein the instructions further include:
filtering the actigraphy signal using a median removal filter or a high pass filter, wherein the filtering operation is performed by the electronic data processing device.

18. A physiological monitoring device comprising:
at least one of an electrocardiography (ECG) sensor and a respiratory sensor configured generate a non-body motion physiological parameter signal as a function of time, the physiological parameter signal including at least one of a heart rate signal, at least one ECG trace signal, and a respiration rate signal; and
at least one processor programmed to:
compute a body motion artifact (BMA) signal as a function of time from the non-body motion physiological parameter signal;
applying a linear transform to the BMA signal;
compute an actigraphy signal as a function of time from the applied linear transform BMA signal.

19. The device of claim 18 , wherein the at least one processor is programmed to compute the BMA signal as a function of time from the non-body motion physiological parameter signal by one of:
computing a local signal variance signal from the non-body motion physiological parameter signal;
computing a Short-Time Fourier Transform (STFT) signal from the non-body motion physiological parameter signal; and
computing a wavelet transform signal from the non-body motion physiological parameter signal.

20. The device of claim 18 , wherein the at least one processor is programmed to compute the BMA signal as a function of time from the non-body motion physiological parameter signal by:
computing a BMA signal sample for each time window of a succession of time windows of the non-body motion physiological parameter signal.

Assignees

• Koninklijke Philips Nv

Inventors

• Fonseca Pedro Miguel
• Haakma Reinder
• Aarts Ronaldus Maria
• Long Xi

Classifications

• A61B5/7203

  for noise prevention, reduction or removal · CPC title

• A61B5/0402

  Human Necessities · mapped topic

• A61B5/0809

  Human Necessities · mapped topic

• A61B5/4812

  Detecting sleep stages or cycles · CPC title

• A61B5/0816

  Measuring devices for examining respiratory frequency (measuring frequency of electric signals G01R23/00) · CPC title