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Human Arm Motion Tracking by Inertial/Magnetic Sensors Using Unscented Kalman Filter and Relative Motion Constraint

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Abstract

Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the measurement covariance matrix in such a way that the filter implements gyroscopes when large accelerations are involved. The proposed algorithm was evaluated experimentally by an optical tracking system as the ground truth reference. The results showed the effectiveness and good performance of the proposed algorithm.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11155-9567, Azadi Ave, Tehran, Iran

    Arash Atrsaei, Hassan Salarieh, Aria Alasty & Mohammad Abediny

Authors
  1. Arash Atrsaei
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  2. Hassan Salarieh
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  3. Aria Alasty
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  4. Mohammad Abediny
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Correspondence to Hassan Salarieh.

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Atrsaei, A., Salarieh, H., Alasty, A. et al. Human Arm Motion Tracking by Inertial/Magnetic Sensors Using Unscented Kalman Filter and Relative Motion Constraint. J Intell Robot Syst 90, 161–170 (2018). https://doi.org/10.1007/s10846-017-0645-z

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  • DOI: https://doi.org/10.1007/s10846-017-0645-z

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