Full metadata
Title
Multimodal movement sensing using motion capture and inertial sensors for mixed-reality rehabilitation
Description
This thesis presents a multi-modal motion tracking system for stroke patient rehabilitation. This system deploys two sensor modules: marker-based motion capture system and inertial measurement unit (IMU). The integrated system provides real-time measurement of the right arm and trunk movement, even in the presence of marker occlusion. The information from the two sensors is fused through quaternion-based recursive filters to promise robust detection of torso compensation (undesired body motion). Since this algorithm allows flexible sensor configurations, it presents a framework for fusing the IMU data and vision data that can adapt to various sensor selection scenarios. The proposed system consequently has the potential to improve both the robustness and flexibility of the sensing process. Through comparison between the complementary filter, the extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the particle filter (PF), the experimental part evaluated the performance of the quaternion-based complementary filter for 10 sensor combination scenarios. Experimental results demonstrate the favorable performance of the proposed system in case of occlusion. Such investigation also provides valuable information for filtering algorithm and strategy selection in specific sensor applications.
Date Created
2010
Contributors
- Liu, Yangzi (Author)
- Qian, Gang (Thesis advisor)
- Olson, Loren (Committee member)
- Si, Jennie (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
vii, 76 p. : ill. (some col.)
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.8665
Statement of Responsibility
by Yangzi Liu
Description Source
Viewed on Apr. 13, 2012
Level of coding
full
Note
Partial requirement for: M.S., Arizona State University, 2010
Note type
thesis
Includes bibliographical references (p. 65-67)
Note type
bibliography
Field of study: Electrical engineering
System Created
- 2011-08-12 01:05:18
System Modified
- 2021-08-30 01:56:52
- 2 years 8 months ago
Additional Formats