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Design and Implementation of a Motion Analysis Algorithm based on Inertia-kinect Sensors for Step Length Estimation

Abbasi, Javad | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52340 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Salarieh, Hassan; Alasty, Aria
  7. Abstract:
  8. Motion capture is a process that movements of living organisms like human or objects are captured and the results are processed for the desired applications. This applications are in rehabilation, sports, film industry and etc. There are many techniques and instruments for motion capture that optical cameras are the most accurate ones. But this cameras are high cost and limited to labs. Some sensors like IMUs and recently, Kinect cameras have been considered by many researchers because these are low cost and easy to use. But problems like bias, accumulated error and occlusion make them to looking for improvments. Fusion algorithms are one of the best methods that help to use from each sensor's strengths. The purpose of this work is design and implementation of an efficient algorithm for estimation of lower limbs joints 3D positions and step length. Orientation quaternions are considered as estimation states. An algorithm was developed with gradient descent and unscented Kalman filter approach based on IMUs and Kinect's measurements. In this algorithm bias and magnetic distortions have been compensated in parallel algorithms. The results errors have been reported with respect to optical cameras. the results show up to 62 percent improvement on Kinect in joints 3D positions estimation and the algorithm improves step length estimation error of Kinect from 7.8 cm to 0.03 cm.

  9. Keywords:
  10. Motion Capture ; Kinect Sensor ; Inertial Measurement Unite (IMU) ; Step Length ; Gait Analysis

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