Joint angle tracking with inertial sensors

Patent metadata

Field	Value
Publication number	US-9597015-B2
Application number	US-37848609-A
Country	US
Kind code	B2
Filing date	Feb 12, 2009
Priority date	Feb 12, 2008
Publication date	Mar 21, 2017
Grant date	Mar 21, 2017

Abstract

A method for estimating joint angles of a multi-segment limb from inertial sensor data accurately estimates and tracks the orientations of multiple segments of the limb as a function of time using data from a single inertial measurement unit worn at the distal end of the limb. Estimated joint angles are computed from measured inertial data as a function of time in a single step using a nonlinear state space estimator. The estimator preferably includes a tracking filter such as an unscented Kalman filter or particle filter. The nonlinear state space estimator incorporates state space evolution equations based on a kinematic model of the multi-segment limb.

First claim

What is claimed is:

1. A method for estimating and tracking joint angles of a human multi-segment linkage, the method comprising:
a) measuring inertial data as a function of time using an inertial measurement unit positioned at a distal end of the human multi-segment linkage; and
b) computing from the measured inertial data estimated joint angles of the human multi-segment linkage as a function of time using a nonlinear state space estimator including an observation model incorporating an acceleration measurement vector comprising both translational accelerations and gravitational effects.

2. The method of claim 1 wherein said measurement unit includes multiple sensors, wherein each of the multiple sensors is selected from the group consisting of a gyroscope, an accelerometer, and a magnetometer.

3. The method of claim 1 wherein said inertial measurement unit includes a triaxial gyroscope and triaxial accelerometer.

4. The method of claim 1 wherein the nonlinear state space estimator comprises a tracking filter selected from the group consisting of an unscented Kalman filter and a particle filter.

5. The method of claim 1 wherein the nonlinear state space estimator comprises state space evolution equations based on a kinematic model of the multi-segment linkage.

6. The method of claim 1 wherein the nonlinear state space estimator comprises state space evolution equations that incorporate physical limitations of the joint angles.

7. The method of claim 1 wherein the nonlinear state space estimator comprises observation equations that incorporate sensor measurement noise.

8. The method of claim 1 wherein the nonlinear state space estimator computes an estimate of uncertainty of the estimated joint angles.

9. The method of claim 1 wherein the nonlinear state space estimator computes predicted estimates of the joint angles.

10. The method of claim 1 wherein the nonlinear state space estimator computes smoothed estimates of the joint angles.

11. The method of claim 1 wherein the multi-segment linkage is a human limb.

12. A system for estimating joint angles of a human multi-segment linkage, the system comprising:
a) an inertial measurement unit for measuring inertial data as a function of time from a distal segment of the human multi-segment linkage;
b) a memory for storing the measured inertial data; and
c) a nonlinear state-space estimator including an observation model incorporating an acceleration measurement vector comprising both translational accelerations and gravitational effects implemented in a computer for estimating from the measured inertial data the joint angles of the human multi-segment linkage as a function of time.

13. The system of claim 12 , wherein said single measurement unit includes multiple sensors, wherein each of the multiple sensors is selected from the group consisting of a gyroscope, an accelerometer, and a magnetometer.

14. The system of claim 12 wherein said single inertial measurement unit includes a triaxial gyroscope and triaxial accelerometer.

15. The system of claim 12 wherein the nonlinear state space estimator comprises a tracking filter selected from the group consisting of an unscented Kalman filter and a particle filter.

16. The system of claim 12 wherein the nonlinear state space estimator comprises state space evolution equations based on a kinematic model of the multi-segment linkage.

17. The system of claim 12 wherein the multi-segment linkage is a human limb.

Assignees

• Mcnames James Nathan
• El-Gohary Mahmoud
• Pearson Sean Christopher
• Univ Portland State

Inventors

• Mcnames James Nathan
• El-Gohary Mahmoud
• Pearson Sean Christopher

Classifications

• A61B5/4528

  Joints (A61B5/4533, A61B5/4538 take precedence) · CPC title

• A61B5/1126

  using a particular sensing technique · CPC title

• A61B2562/0219

  Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches · CPC title

• A61B5/1071

  measuring angles, e.g. using goniometers (A61B5/1123 takes precedence) · CPC title

• A61B5/1121 Primary

  Determining geometric values, e.g. centre of rotation or angular range of movement · CPC title