Calibration of a chest-mounted wireless sensor device for posture and activity detection

Patent metadata

Field	Value
Publication number	US-9632981-B2
Application number	US-201313900438-A
Country	US
Kind code	B2
Filing date	May 22, 2013
Priority date	Jul 12, 2012
Publication date	Apr 25, 2017
Grant date	Apr 25, 2017

Abstract

A method and system for calibrating a wireless sensor device are disclosed. In a first aspect, the method comprises determining a vertical calibration vector and determining a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes. In a second aspect, a wireless sensor device comprises a processor and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to determine a vertical calibration vector and to determine a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes.

First claim

What is claimed is:

1. A method for calibrating a wireless sensor device, the method comprising:
detecting accelerometer data in 3 axes within a predetermined time period by the wireless sensor device;
determining an acceleration vector corresponding to a footstep number;
determining a vertical calibration vector using the acceleration vector and a walking detection algorithm, wherein the walking detection algorithm:
calculates a signal magnitude area (SMA) for the predetermined time period using the accelerometer data,
calculates a magnitude of acceleration in a horizontal plane and an overall magnitude of acceleration, and
compares the SMA to a first threshold and the overall magnitude of acceleration to both a second threshold and a third threshold for a result of the walking detection algorithm; and

determining a rotation matrix using the determined vertical calibration vector to line up native axes of the wireless sensor device with body axes.

2. The method of claim 1 , wherein the determining the vertical calibration vector, when executed by a processor via the application, further comprises:
determining the vertical calibration vector using at least one of: automatic calibration, adaptive calibration, or manual calibration.

3. The method of claim 2 , wherein the determining the vertical calibration vector using the automatic calibration comprises:
determining the acceleration vector corresponding to the footstep number of a user of the wireless sensor device; and
determining whether the footstep number meets a minimum footstep number threshold within the predetermined time period.

4. The method of claim 2 , wherein the determining the vertical calibration vector using the adaptive calibration comprises:
detecting an inaccuracy with the automatic calibration; and
adjusting the vertical calibration vector slowly over time.

5. The method of claim 4 , wherein the adjusting the vertical calibration vector slowly over time comprises:
adding current acceleration samples during a detected walking period; and
normalizing the vertical calibration vector to provide an adjusted calibration vector.

6. The method of claim 2 , wherein the determining the vertical calibration vector using the manual calibration, when executed by the processor via the application, comprises:
determining the vertical calibration vector using at least one of: upright manual calibration, manual calibration based on walking, or bedridden manual calibration.

7. The method of claim 6 , wherein the determining the vertical calibration vector using the upright manual calibration comprises:
receiving an upright manual calibration request from a user in a standing upright position via a relay;
detecting a MEMS based vertical calibration vector;
filtering the MEMS based vertical calibration vector using a lowpass filter;
replacing a current upright vertical calibration vector with the filtered MEMS based vertical calibration vector; and
transmitting a status message to the relay.

8. The method of claim 6 , wherein the determining the vertical calibration vector using the manual calibration based on walking comprises:
receiving a manual calibration request from a user during a walking period via a relay;
calculating a MEMS based vertical calibration vector during the walking period;
determining whether the walking period meets another minimum footstep number threshold; and
transmitting a status message to the relay.

9. The method of claim 6 , wherein the determining the vertical calibration vector using the bedridden manual calibration comprises:
receiving a manual calibration request from a bedridden user via a relay;
determining both a supine calibration vector and a leaning calibration vector;
calculating a MEMS based vertical calibration vector based on the supine calibration vector and the leaning calibration vector; and
transmitting a status message to the relay.

10. The method of claim 6 , wherein the manual calibration based on walking, when executed by the processor via the application, further causes the processor to:
receive a manual calibration request from a user during a walking period via a relay;
calculate a MEMS based vertical calibration vector during the walking period;
determine whether the walking period meets another minimum footstep number threshold; and
transmit a status message to the relay.

11. A wireless sensor device, comprising:
a processor; and
a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to:
detect accelerometer data in 3 axes within a predetermined time period by the wireless sensor device;
determine an acceleration vector corresponding to a footstep number;
determine a vertical calibration vector using the acceleration vector and a walking detection algorithm, wherein the walking detection algorithm:
calculates a signal magnitude area (SMA) for the predetermined time period using the accelerometer data,
calculates a magnitude of acceleration in a horizontal plane and an overall magnitude of acceleration, and
compares the SMA to a first threshold and the overall magnitude of acceleration to both a second threshold and a third threshold for a result of the walking detection algorithm; and

determine a rotation matrix using the determined vertical calibration vector to line up native axes of the wireless sensor device with body axes.

12. The device of claim 11 , wherein the determine the vertical calibration vector comprises:
determine the vertical calibration vector using at least one of: automatic calibration, adaptive calibration, or manual calibration.

13. The device of claim 12 , wherein the determine the vertical calibration vector using the automatic calibration comprises:
determine the acceleration vector corresponding to the footstep number of a user of the wireless sensor device; and
determine whether the footstep number meets a minimum footstep number threshold within the predetermined time period.

14. The device of claim 12 , wherein the determine the vertical calibration vector using the adaptive calibration comprises:
detect an inaccuracy with the automatic calibration; and
adjust the vertical calibration vector slowly over time.

15. The device of claim 14 , wherein the adjust the vertical calibration vector slowly over time comprises:
add current acceleration samples during a detected walking period; and
normalize the vertical calibration vector to provide an adjusted calibration vector.

16. The device of claim 12 , wherein the determine the vertical calibration vector using the manual calibration comprises:
determine the vertical calibration vector using at least one of: upright manual calibration, manual calibration based on walking, or bedridden manual calibration.

17. The device of claim 16 , wherein the upright manual calibration, when executed by the processor via the application, further causes the processor to:
receive an upright manual calibration request from a user in a standing upright position via a relay;
detect a MEMS based vertical calibration vector;
filter the MEMS based vertical calibration vector using a lowpass filter;
replace a current upright vertical calibration vector with the filtered MEMS based vertical calibration vector; and
transmit a status message to the relay.

18. The device of claim 16 , wherein the bedridden manual calibration, when executed by the processor via the application, further causes the processor to:
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Assignees

• Vital Connect Inc

Inventors

• Chan Alexander
• Ferdosi Nima
• Narasimhan Ravi

Classifications

• A61B5/00

  Measuring for diagnostic purposes (radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00); Identification of persons · CPC title

• A61B5/11

  Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb {(A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721)} · CPC title

• G06F17/00 Primary

  Digital computing or data processing equipment or methods, specially adapted for specific functions (information retrieval, database structures or file system structures therefor G06F16/00) · CPC title

• G01P21/00 Primary

  Testing or calibrating of apparatus or devices covered by the preceding groups · CPC title

• G06F17/40

  Data acquisition and logging (for input to computer G06F3/00) · CPC title