Granted Patent B2

US 9,632,981 · App. 13/900,438 · Granted Apr 25, 2017

Inventors: Alexander Chan (Campbell, CA); Nima Ferdosi (San Jose, CA); Ravi Narasimhan (Sunnyvale, CA)

Assignee: VITAL CONNECT, INC.

G06F17/00G01P21/00G04F13/04G07C1/00A61B5/00A61B5/11G01D21/00G01P15/00G06F17/40G06F19/00

Abstract

Claims (76)

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:

receive a manual calibration request from a bedridden user via a relay;

determine both a supine calibration vector and a leaning calibration vector;

calculate a MEMS based vertical calibration vector based on the supine calibration vector and the leaning calibration vector; and

transmit a status message to the relay.

Assignments (8)

Continuity (2)