Method and apparatus for estimating a motion parameter

• US 7,467,060 B2
• Filed: 03/01/2007
• Issued: 12/16/2008
• Est. Priority Date: 03/03/2006
• Status: Active Grant

• Current Assignee: Garmin Switzerland GmbH (Garmin Limited)
• Original Assignee: Garmin Limited
• Inventors: MacDonald, Paul R., Rooney, James K., Kulach, Christopher J.
• Primary Examiner(s): Bui; Bryan
• Assistant Examiner(s): Kundu; Sujoy K
• Application Number:
  US11/681,032
• Publication Number:
  US 20070208544A1
• Time in Patent Office: 656 Days
• Field of Search: 702/176, 702/141, 702/160, 702/182, 364/410, 364/561, 364/564, 734/90, 735/140.1
• US Class Current: 702/141
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• 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 5/681 Wristwatch-type devices
• CPC Class Codes: A63B 2071/068 Input by voice recognition
• CPC Class Codes: A63B 2102/32 Golf
• CPC Class Codes: A63B 2220/12 Absolute positions, e.g. by using GPS
• CPC Class Codes: A63B 2220/18 Inclination, slope or curvature
• CPC Class Codes: A63B 2220/20 Distances or displacements
• CPC Class Codes: A63B 2220/30 Speed
• CPC Class Codes: A63B 2220/34 Angular speed
• CPC Class Codes: A63B 2220/40 Acceleration
• CPC Class Codes: A63B 2220/70 Measuring or simulating ambient conditions, e.g. weather, terrain or surface conditions
• CPC Class Codes: A63B 2220/72 Temperature
• CPC Class Codes: A63B 2220/836 Sensors arranged on the body of the user
• CPC Class Codes: A63B 2225/20 with means for remote communication, e.g. internet or the like
• CPC Class Codes: A63B 2225/50 Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2230/06 : heartbeat rate only
• CPC Class Codes: A63B 2230/75 : calorie expenditure
• CPC Class Codes: A63B 2243/0025 : Football American football A63B2243/007
• CPC Class Codes: A63B 2243/0037 : Basketball
• 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: A63B 69/0028 : for running, jogging or speed-walking movable endless bands A63B22/02
• CPC Class Codes: G01C 21/185 : for gravity
• 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 and apparatus for estimating a motion parameter corresponding to a subject element employs one or more accelerometers operable to measure accelerations and a processing system operable to generate a motion parameter metric utilizing the acceleration measurements and estimate the motion parameter using the motion parameter metric.

Claims

1. A method of estimating a motion parameter corresponding to a subject element in cyclical motion, the method comprising:

acquiring an acceleration measurement corresponding to at least one motion cycle;

determining a stride duration using the acceleration measurement;

low-pass filtering the acceleration measurement utilizing a cut-off frequency between about 0.5 Hz and 10 Hz;

calculating an acceleration magnitude using the filtered acceleration measurement;

for each motion cycle, generating a motion parameter metric utilizing the stride duration and acceleration magnitude; and

estimating the motion parameter using the motion parameter metric.

2. The method as claimed in claim 1, wherein the motion parameter is estimated utilizing the motion parameter metric and a statistical model.

3. The method as claimed in claim 2, wherein the statistical model is a regression model selected from the group consisting of a linear regression model, a polynomial regression model, a multiple-regression model, a piecewise-linear regression model, and combinations thereof.

4. The method as claimed in claim 1, further including acquiring a plurality of acceleration measurements and generating the motion parameter metric utilizing the acceleration measurements.

5. The method as claimed in claim 1, wherein the cut-off frequency is generated using a stride frequency calculated from the acceleration measurements.

6. The method as claimed in claim 1, wherein the estimated motion parameter is selected from the group consisting of stride speed, acceleration, velocity, stride distance, total distance, gait efficiency, power, energy, maximum impact, average calories consumed, maximum speed change, speed variability, and combinations thereof.

7. The method as claimed in claim 1, wherein the motion parameter corresponds to a stride speed and the motion parameter metric is at least partially generated by performing an integration of a function of the acceleration magnitude.

8. An apparatus operable to estimate a motion parameter corresponding to a subject element, the apparatus comprising:

a plurality of accelerometers each operable to provide a signal corresponding to an acceleration measurement, at least two of the accelerometers being adapted to measure accelerations in two directions separated by an angle greater than zero degrees; and

a processing system coupled with one or more of the accelerometers, the processing system operable to;

calculate a stride duration using at least one of the acceleration measurements,

low-pass filter the signals corresponding to the acceleration measurements utilizing a cut-off frequency between about 0.5 Hz and 10 Hz,

calculate an acceleration magnitude using the acceleration measurements corresponding to the filtered signals,

generate a motion parameter metric utilizing the stride duration and acceleration magnitude, and

estimate the motion parameter using the motion parameter metric and a statistical regression model.

9. The apparatus as claimed in claim 8, wherein the motion parameter corresponds to a stride speed and the motion parameter metric is at least partially generated by performing an integration of a function of the acceleration magnitude.

10. The apparatus as claimed in claim 8, wherein the apparatus includes at least three accelerometers adapted to measure accelerations in three directions each separated by an angle greater than zero degrees.

11. The apparatus as claimed in claim 8, wherein the processing system is further operable to limit acceleration measurements to within a specific dynamic range.