Pedometer with Accelerometer and Foot Motion Distinguishing Method

• US 20170241797A1
• Filed: 10/31/2016
• Published: 08/24/2017
• Est. Priority Date: 02/01/2016
• Status: Active Grant

• Current Assignee: One Two Free Incorporated
• Original Assignee: One Two Free Incorporated
• Inventors: KONG, Deming, CHEN, Guanxing
• Granted Patent: US 11,047,706 B2
• Time in Patent Office: Days
• CPC Class Codes: A43B 17/00 Insoles for insertion, e.g. footbeds or inlays, for attachment to the shoe after the upper has been joined
• CPC Class Codes: A43B 3/34 with electrical or electronic arrangements
• CPC Class Codes: A43B 3/35 with electric heating arrangements
• CPC Class Codes: A43B 3/36 with light sources
• CPC Class Codes: A43B 3/38 with power sources
• CPC Class Codes: A43B 7/02 with heating arrangements with electric heating arrangements A43B3/35
• CPC Class Codes: A61B 2560/029 adapted for auto-initiation
• 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 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/6807 Footwear
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61F 2007/0045 Foot
• CPC Class Codes: A63B 2220/40 Acceleration
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Abstract

A method for distinguishing a foot motion of a user by placing a pedometer at a foot of a user includes the steps of collecting an accelerating data from an accelerometer in a real time manner; filtering the accelerating data via a smoothing filter and a Kalman filter; generating a step data that represents number of steps taken by the user in response to the accelerating data through the smoothing filter; generating an activity data that represents a foot motion of the user in response to the accelerating data through the Kalman filter; and combining the step data and the activity data to form a resulted data that distinguishes the foot motion with step count of the user.

Claims

1. A method for distinguishing a foot motion of a user by placing a pedometer at a foot of a user, which comprises the steps executed by a computerize device of:

(a) collecting an accelerating data from an accelerometer of said pedometer in a real time manner;

(b) filtering said accelerating data via a smoothing filter and a Kalman filter;

(c) generating a step data that represents number of steps taken by the user in response to said accelerating data through said smoothing filter;

(d) generating an activity data that represents a foot motion of the user in response to said accelerating data through said Kalman filter; and

(e) combining said step data and said activity data to form a resulted data that distinguishes the foot motion with step count of the user.

2. The method as recited in claim 1 wherein, in the step (b), said accelerating data from said accelerometer is duplicated to form two sets of identical accelerating data that a first set of accelerating data is processed via said smoothing filter and a second set of accelerating data is processed via said Kalman filter.

3. The method as recited in claim 1 wherein, in the step (c), said step data generated by averaging two consequent accelerating data via said smoothing filter to smooth said accelerating data.

4. The method as recited in claim 2 wherein, in the step (c), said step data generated by averaging two consequent accelerating data via said smoothing filter to smooth said accelerating data.

5. The method, as recited in claim 1, wherein the step (a) further comprises the steps of:

(a.1) extracting said accelerating data from X axis, Y axis, and Z axis to obtain X value, Y value, and Z value of said accelerating data respectively, wherein said X axis refers to a foot motion in a forward direction, said Y axis refers to a foot motion in a left-and-right direction, and said Z axis refers to a foot motion in an elevated direction;

(a.2) comparing each of said X values of said accelerating data with a predetermined X threshold; and

(a.3) determining a one step motion user when the previous X value is smaller than said X threshold and the following X value is larger than said X threshold.

6. The method, as recited in claim 4, wherein the step (a) further comprises the steps of:

(a.1) extracting said accelerating data from X axis, Y axis, and Z axis to obtain X value, Y value, and Z value of said accelerating data respectively;

(a.2) comparing each of said X values of said accelerating data with a predetermined X threshold; and

(a.3) determining a one step motion user when the previous X value is smaller than said X threshold and the following X value is larger than said X threshold.

7. The method, as recited in claim 5, wherein said accelerometer is set at 25 Hz that said accelerometer is set at 25 Hz that no more than 5 steps are counted within 25 consequent X values, such that 8 or more consequent X values are collected for counting one step motion.

8. The method, as recited in claim 6, wherein said accelerometer is set at 25 Hz that said accelerometer is set at 25 Hz that no more than 5 steps are counted within 25 consequent X values, such that 8 or more consequent X values are collected for counting one step motion.

9. The method, as recited in claim 5, wherein the step (d) further comprises the steps of:

(d.1) determining a resultant acceleration in response to said X value, Y value, and Z value of said accelerating data; and

(d.2) determining an activity of walking, jogging, and running of the user by said activity data related to a value of said resultant acceleration, wherein the activity of walking has smaller value of said resultant acceleration, and the activity of running has bigger value of said resultant acceleration.

10. The method, as recited in claim 8, wherein the step (d) further comprises the steps of:

(d.1) determining a resultant acceleration in response to said X value, Y value, and Z value of said accelerating data; and

(d.2) determining an activity of walking, jogging, and running of the user by said activity data related to a value of said resultant acceleration, wherein the activity of walking has smaller value of said resultant acceleration, and the activity of running has bigger value of said resultant acceleration.

11. The method, as recited in claim 9, wherein the step (d) further comprises the steps of:

(d.3) forming a wave form in response to said resultant acceleration; and

(d.4) comparing said wave form with a plurality of wave form configurations to distinguish a motion posture of the user.

12. The method, as recited in claim 10, wherein the step (d) further comprises the steps of:

(d.3) forming a wave form in response to said resultant acceleration; and

(d.4) comparing said wave form with a plurality of wave form configurations to distinguish a motion posture of the user.

13. The method, as recited in claim 5, wherein said accelerometer is initiated to automatically define said X axis, Y axis, and Z axis to obtain X value, Y value, and Z value of said accelerating data.

14. The method, as recited in claim 1, wherein said pedometer is automatically activated by a sensor selected from a group consisting of pressure sensor and motion sensor.

15. The method, as recited in claim 1, wherein said pedometer is embedded in a shoe sole of a shoe worn by the user at a mid portion thereof between toe and heel portions.

16. The method, as recited in claim 1, wherein said pedometer is held on a shoe vamp of a shoe worn by the user.

22. The pedometer, as recited in claim 1, wherein said pedometer is automatically activated by a sensor selected from a group consisting of pressure sensor and motion sensor.

17. A pedometer, comprising:

a casing adapted for being placing at a foot of a user;

an accelerometer, which is received in said casing, that collects an accelerating data in a real time manner;

a smoothing filter filtering said accelerating data to generate a step data that represents number of steps taken by the user;

a Kalman filter filtering said accelerating data to generate an activity data that represents a foot motion of the user; and

a processor combining said step data and said activity data to form a resulted data that distinguishes the foot motion with step count of the user.

18. The pedometer, as recited in claim 17, wherein said accelerating data from said accelerometer is duplicated to form two sets of identical accelerating data that a first set of accelerating data is processed via said smoothing filter and a second set of accelerating data is processed via said Kalman filter.

19. The pedometer, as recited in claim 18, further comprising a comparison module operatively linked to said processor, wherein said accelerating data is extracted to obtain X value, Y value, and Z value of said accelerating data along from X axis, Y axis, and Z axis respectively, wherein each of said X values of said accelerating data is compared with a predetermined X threshold via said comparison module for determining a one step motion user when the previous X value is smaller than said X threshold and the following X value is larger than said X threshold.

20. The pedometer, as recited in claim 19, wherein said processor further generates a resultant acceleration in response to said X value, Y value, and Z value of said accelerating data for determining an activity of walking, jogging, and running of the user by said activity data related to a value of said resultant acceleration, wherein the activity of walking has smaller value of said resultant acceleration, and the activity of running has bigger value of said resultant acceleration.

21. The pedometer, as recited in claim 20, wherein said comparison module further compares a wave form formed in response to said resultant acceleration with a plurality of wave form configurations for distinguishing a motion posture of the user.

23. A shoe, comprising:

a shoe body adapted to be worn on a foot of a user; and

a pedometer, which is carried by said shoe body and positioned with respect to a center of gravity of the user, comprising;

a casing adapted to be carried by said shoe body;

an accelerometer, which is received in said casing, that collects an accelerating data in a real time manner during movement of said shoe body by the user;

a smoothing filter filtering said accelerating data to generate a step data that represents number of steps taken by said shoe body by the user;

a Kalman filter filtering said accelerating data to generate an activity data that represents a foot motion of said shoe body by the user; and

a processor combining said step data and said activity data to form a resulted data that distinguishes the foot motion with step count of said shoe body of the user.

24. The shoe, as recited in claim 23, wherein said accelerating data from said accelerometer is duplicated to form two sets of identical accelerating data that a first set of accelerating data is processed via said smoothing filter and a second set of accelerating data is processed via said Kalman filter.

25. The shoe, as recited in claim 24, further comprising a comparison module operatively linked to said processor, wherein said accelerating data is extracted to obtain X value, Y value, and Z value of said accelerating data along from X axis, Y axis, and Z axis respectively, wherein each of said X values of said accelerating data is compared with a predetermined X threshold via said comparison module for determining a one step motion user when the previous X value is smaller than said X threshold and the following X value is larger than said X threshold.

26. The shoe, as recited in claim 25, wherein said processor further generates a resultant acceleration in response to said X value, Y value, and Z value of said accelerating data for determining an activity of walking, jogging, and running of the user by said activity data related to a value of said resultant acceleration, wherein the activity of walking has smaller value of said resultant acceleration, and the activity of running has bigger value of said resultant acceleration.

27. The shoe, as recited in claim 26, wherein said comparison module further compares a wave form formed in response to said resultant acceleration with a plurality of wave form configurations for distinguishing a motion posture of the user.

28. The shoe, as recited in claim 23, wherein said pedometer is automatically activated by a sensor selected from a group consisting of pressure sensor and motion sensor.