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      • HARVEST
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      Body Motion Capture Using Multiple Inertial Sensors

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      XIA-THESIS.pdf (1.882Mb)
      Date
      2013-02-25
      Author
      Xia, Xiaoye
      Type
      Thesis
      Degree Level
      Masters
      Metadata
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      Abstract
      Near-fall detection is important for medical research since it can help doctors diagnose fall-related diseases and also help alert both doctors and patients of possible falls. However, in people’s daily life, there are lots of similarities between near-falls and other Activities of Daily Living (ADLs), which makes near-falls particularly difficult to detect. In order to find the subtle difference between ADLs and near-fall and accurately identify the latter, the movement of whole human body needs to be captured and displayed by a computer generated avatar. In this thesis, a wireless inertial motion capture system consisting of a central control host and ten sensor nodes is used to capture human body movements. Each of the ten sensor nodes in the system has a tri-axis accelerometer and a tri-axis gyroscope. They are attached to separate locations of a human body to record both angular and acceleration data with which body movements can be captured by applying Euler angle based algorithms, specifically, single rotation order algorithm and the optimal rotation order algorithm. According to the experiment results of capturing ten ADLs, both the single rotation order algorithm and the optimal rotation order algorithm can track normal human body movements without significantly distortion and the latter shows higher accuracy and lower data shifting. Compared to previous inertial systems with magnetometers, this system reduces hardware complexity and software computation while ensures a reasonable accuracy in capturing human body movements.
      Degree
      Master of Science (M.Sc.)
      Department
      Electrical and Computer Engineering
      Program
      Electrical Engineering
      Supervisor
      Teng, Daniel; Dinh, Anh; Basran, Jenny
      Committee
      Ko, Seokbum; Deters, Ralph; Wahid, Khan A.
      Copyright Date
      January 2012
      URI
      http://hdl.handle.net/10388/ETD-2012-01-311
      Subject
      Motion capture
      Activities of Daily Living (ADLs)
      Inertial sensors
      Euler angles
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