Motion Tracking System

• US 20080285805A1
• Filed: 05/15/2007
• Published: 11/20/2008
• Est. Priority Date: 03/15/2007
• Status: Active Grant

• Current Assignee: Movella Technologies BV
• Original Assignee: Xsens Technologies BV (Movella Holdings, Inc.)
• Inventors: Roetenberg, Daniel, Luinge, Henk J., Slycke, Per J.
• Granted Patent: US 8,165,844 B2
• Time in Patent Office: Days
• US Class Current: 382/107
• 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 2562/046 in a matrix array
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1121 Determining geometric values, e.g. centre of rotation or angular range of movement
• CPC Class Codes: A61B 5/1122 of movement trajectories
• CPC Class Codes: A61B 5/1126 using a particular sensing technique
• CPC Class Codes: A61B 5/4528 Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61B 5/6804 Garments; Clothes
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: B25J 9/1694 characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
• CPC Class Codes: G05B 2219/37388 Acceleration or deceleration, inertial measurement
• CPC Class Codes: G05B 2219/42337 Tracking control
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00

Abstract

A system is provided for capturing motion of a moving object via a plurality of motion sensor modules placed on various body segments. The sensor modules capture both 3D position and 3D orientation data relating to their respective body segments, thereby gathering motion data having six degrees of freedom with respect to a coordinate system not fixed to the body. Each body sensor collects 3D inertial sensor data and, optionally, magnetic field data. In embodiments, either DSP circuitry within the sensor modules or an external computing device, processes the sensor data to arrive at orientation and position estimates by using an estimation algorithm, such as a Kalman filter or a particle filter. The processing includes biomechanical model constraints that allow flexibility in the joints and provide characteristics for various joint types. To improve estimation accuracy, the system may be integrated with various types of aiding sensors.

Claims

1. A method for capturing motion of an object having a plurality of segments via a plurality of motion sensor modules located on the segments, each of two or more of the segments of the object having thereon at least one motion sensor, each sensor module being adapted to capture 3D position data and 3D orientation data associated with its respective segment, the method comprising:

collecting 3D inertial sensor data at each sensor module via at least one 3D accelerometer sensor and at least one 3D angular velocity sensor; and

calculating a 3D orientation and 3D position of each segment having a sensor by integrating the 3D angular velocity data and doubly integrating the 3D accelerometer data in time and updating the calculation via constraints based on predetermined characteristics of the segments.

2. The method according to claim 1, wherein the constraints comprise a biomechanical model which includes an assumption that the segments are linked by joints.

3. The method according to claim 2, wherein the biomechanical model allows a predetermined degree of laxity in one or more joints and provides for two or more distinct biomechanical characteristics corresponding to two or more respective distinct joint types.

4. The method according to claim 1, further comprising updating the 3D orientation and 3D position calculation with one or more aiding sensors selected from the group consisting of a magnetic sensor, a GPS receiver, an RF-based local positioning sensor, a barometer, a pressure sensor, and a camera.

5. The method according to claim 4, wherein the camera is adapted to improve the object'"'"'s 3D position and 3D orientation calculation by providing at least 2D positional data of the object.

6. The method according to claim 1, further comprising updating the 3D orientation and 3D position calculation by detecting an external contact of the object with predetermined surroundings of the object based on at least one of position, velocity, and acceleration of one or more segments.

7. The method according to claim 1 wherein the object'"'"'s surroundings are characterized by one or more predetermined assumptions, the method further comprising updating the one or more predetermined assumptions via a simultaneous localization and mapping technique.

8. A system for capturing motion of an object having a plurality of segments, the system comprising:

a plurality of motion sensor modules including at least one sensor module located on each of two or more segments, each sensor module being adapted to capture 3D inertial sensor data; and

at least one sensor fusion circuit for estimating 3D position and 3D orientation of the plurality of segments based on the 3D inertial sensor data captured by the motion sensor modules, wherein the at least one sensor fusion circuit updates the 3D position and 3D orientation estimates based on predetermined constraints associated with the segments.

9. The system of claim 8 wherein the at least one sensor fusion circuit estimates the 3D position and 3D orientation data via one of a Kalman filter and a particle filter.

10. The system of claim 8 wherein the segment constraints comprise a biomechanical model of the object having a plurality of segment joints and allowing a predetermined degree of laxity in one or more joints to accommodate distinct biomechanical characteristics corresponding to distinct joint types.

11. The system of claim 8 further comprising one or more aiding sensors for updating the 3D orientation and 3D position estimates for the plurality of segments, the aiding sensors selected from the group consisting of a magnetic sensor, a GPS receiver, an RF-based local positioning sensor, a barometer, a pressure sensor, and a camera.

12. The system of claim 11 wherein the camera is adapted to improve the body'"'"'s position estimate by providing positional information associated with the body'"'"'s environment.

13. The system of claim 8 further comprising a logging device adapted to provide synchronization of information between the sensor modules and to provide further processing of sensor data via the at least one sensor fusion circuit.

14. A motion sensor module for capturing motion of at least one of a plurality of object segments, wherein the motion sensor module is located on the at least one of the segments, the motion sensor module comprising:

at least one of a 3D accelerometer sensor and a 3D angular velocity sensor for collecting 3D inertial sensor data associated with the at least one segment; and

a sensor fusion circuit for estimating 3D position and 3D orientation data based on the 3D inertial sensor data, wherein the sensor fusion circuit updates the 3D position and 3D orientation estimates via a plurality of constraints based on predetermined characteristics of the object segments.

15. The motion sensor module of claim 14, wherein the constraints comprise a biomechanical model which includes an assumption that the plurality of object segments are directly or indirectly linked by joints.

16. The motion sensor module of claim 15, wherein the biomechanical model allows a predetermined degree of laxity in one or more joints and provides for distinct biomechanical characteristics corresponding to distinct joint types.

17. The motion sensor module of claim 14 wherein the sensor fusion circuit estimates the 3D position and 3D orientation data via one of a Kalman filter and a particle filter.