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Human arm motion tracking by orientation-based fusion of inertial sensors and kinect using unscented kalman filter

Atrsaei, A ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1115/1.4034170
  3. Publisher: American Society of Mechanical Engineers (ASME) , 2016
  4. Abstract:
  5. Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in nonlaboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g., home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the inertial sensors drift problem in high dynamic motions and also joints occlusion in Kinect. The efficiency of the proposed algorithm was evaluated by an optical motion tracker system. The errors were reduced by almost 50% compared to cases when either inertial sensor or Kinect measurements were utilized
  6. Keywords:
  7. Bandpass filters ; Kalman filters ; Motion analysis ; Nonlinear filtering ; Complementary property ; Fusion algorithms ; Human body movement ; Human motion capture ; Measurement model ; MEMS inertial sensors ; Motion capture system ; Unscented kalman filter ; Inertial navigation systems
  8. Source: Journal of Biomechanical Engineering ; Volume 138, Issue 9 , 2016 ; 01480731 (ISSN)
  9. URL: http://biomechanical.asmedigitalcollection.asme.org/article.aspx?articleid=2536526