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

• US 10,317,427 B2
• Filed: 03/15/2017
• Issued: 06/11/2019
• Est. Priority Date: 07/12/2012
• Status: Active Grant

• Current Assignee: Vital Connect, Inc.
• Original Assignee: Vital Connect, Inc.
• Inventors: Chan, Alexander, Ferdosi, Nima, Narasimhan, Ravi
• Primary Examiner(s): Bui, Bryan
• Application Number:
  US15/459,017
• Publication Number:
  US 20170184630A1
• Time in Patent Office: 818 Days
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/0247 Pressure sensors
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1115 Monitoring leaving of a patient support, e.g. a bed or a wheelchair
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1121 Determining geometric values, e.g. centre of rotation or angular range of movement
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: G01D 21/00 Measuring or testing not otherwise provided for
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G01P 15/18 in two or more dimensions
• CPC Class Codes: G01P 21/00 Testing or calibrating of apparatus or devices covered by the preceding groups
• CPC Class Codes: G04F 13/04 using electrochemical means
• CPC Class Codes: G06F 17/00 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 Class Codes: G06F 17/40 Data acquisition and logging for input to computer G06F3/00
• CPC Class Codes: G07C 1/00 Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people registering or indicating the working of machines or vehicles G07C3/00, G07C5/00
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

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.

Claims

1. A method to calibrate a wireless sensor device, comprising:

determining a first section and a second section of a rotation matrix algorithm to line up native axes of the wireless sensor device with body axes,

wherein the first section of the rotation matrix algorithm includes;

determining a first vertical calibration vector in a first frame of reference,

calculating, by the wireless sensor device, a new horizontal axis using the first vertical calibration vector,

calculating, by the wireless sensor device, a first cross product of a native horizontal X-axis and the new horizontal axis,

calculating a first rotation angle using the first cross product, and

calculating a first rotation matrix using the first rotation angle,

wherein the second section of the rotation matrix algorithm includes;

calculating a second vertical calibration vector in a second frame of reference,

calculating a new vertical axis using the second vertical calibration vector,

calculating a second cross product of the second calibration vector and the new vertical axis,

calculating a second rotation angle using the second cross product, and

calculating a second rotation matrix using the second rotation angle;

rotating, in accordance with the first rotation matrix of the first section of a rotation matrix algorithm, a native accelerometer X-axis of the wireless sensor device to align horizontally with a medial-lateral (ML) axis of a body; and

rotating, in accordance with the second rotation matrix of the second section of the rotation matrix algorithm, a native accelerometer Y-axis of the wireless sensor device to align vertically with a vertical (VT) axis of the body.

2. The method of claim 1, wherein the first calibration vector is measured on at least one of:

a vertical, supine, reclined, or leaning body position.

3. The method of claim 1, further comprising determining whether a leaning or supine calibration vector is available.

4. The method of claim 3, wherein in response to no available leaning or supine calibration vector, computing a final rotation matrix.

5. The method of claim 4, wherein the computing the final rotation matrix includes using the first and second rotation matrix.

6. The method of claim 4, wherein in response to an available supine calibration vector, a third section of the rotation matrix algorithm involves an orientation angle of a wireless sensor with respect to a vertical (VT) axis of the body.

7. The method of claim 3, wherein in response to an available leaning or supine calibration vector, initiating a third section of the rotation matrix algorithm.

8. The method of claim 7, further comprising:

rotating, in accordance with the third section of the rotation matrix algorithm, the accelerometer axes of the native wireless sensor device to align horizontally with the ML axis of the body and an anterior-posterior (AP) axis of the body, in response to an additional leaning calibration vector being provided.

9. The method of claim 8, wherein the third section of the rotation matrix algorithm includes:

calculating a second cross product of the leaning calibration vector and the VT axis;

calculating a rotation angle;

calculating a third rotation matrix; and

calculating a final rotation matrix using the first, second, and third rotation matrix.

10. A method to calibrate a wireless sensor device, comprising:

determining a vertical calibration vector using a manual calibration vector;

determining a first section of a rotation matrix algorithm that enables rotation of an X-axis of an accelerometer of the wireless sensor device to line up with a horizontal plane of a body by using the vertical calibration vector;

rotating, in accordance with the first section of a rotation matrix algorithm, the X-axis of the accelerometer of the wireless sensor device to align horizontally with the horizontal plane of the body for calibration that constitutes a first rotation matrix;

determining a second section of the rotation matrix algorithm that enables rotation of a Y-axis of the accelerometer of the wireless sensor device to line up a vertical (VT) axis of the body; and

rotating, in accordance with the second section of rotation matrix algorithm, the Y-axis of the accelerometer of the wireless sensor device to align vertically with the VT axis of the body for calibration that constitutes a second rotation matrix.

11. The method of claim 10, wherein the vertical calibration vector is further determined using an automatic calibration, the automatic calibration includes:

determining an acceleration vector corresponding to a footstep number;

determining the vertical calibration vector using the determined acceleration vector; and

determining a rotation matrix to line up native axes of the wireless sensor device with body axes.

12. The method of claim 10, wherein a rotation matrix is generated using a combination of the vertical calibration vector and a leaning calibration vector.

13. The method of claim 12, wherein the leaning calibration vector includes a forward or a backward calibration vector.

14. The method of claim 10, wherein the vertical calibration vector is further determined using an automatic calibration including:

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.

15. The method of claim 10, wherein the vertical calibration vector is further determined using an adaptive calibration including:

detecting an inaccuracy with the automatic calibration; and

adjusting the vertical calibration vector slowly over time by;

adding current acceleration samples during a detected walking period, and

normalizing the vertical calibration vector to provide an adjusted calibration vector.

16. The method of claim 10, wherein the determining the calibration vector using the manual calibration includes determining the vertical calibration vector using at least one of:

a manual calibration based on the user'"'"'s upright position, a manual calibration based on walking/taking steps and a manual calibration based on a bedridden user.

17. The method of claim 16, wherein the upright manual calibration includes:

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.

18. The method of claim 16, wherein the manual calibration based on the bedridden user includes two steps of calibration based on leaning-back and lying down flat in supine postures.