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Hand Motion Measurement using Inertial Sensor System and Accurate Improvement by Extended Kalman Filter.

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    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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    This study introduces a new inertial sensor system for accurate hand motion analysis, overcoming limitations of optical systems. The novel approach corrects posture errors, enabling precise measurement of intricate finger movements.

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    Area of Science:

    • Biomechanics
    • Robotics
    • Human-Computer Interaction

    Background:

    • Accurate analysis of hand motions is vital for daily activities and occupational tasks.
    • Inertial sensor systems offer advantages over optical motion capture by avoiding spatial constraints.
    • Traditional sensor fusion methods struggle with the complex, multi-jointed nature of finger movements.

    Purpose of the Study:

    • To develop a high-accuracy measurement system for hand and forearm motions using inertial sensors.
    • To address and overcome the critical posture error issue inherent in inertial sensor integration.
    • To enable precise tracking of intricate and rapid finger movements, which are challenging for conventional methods.

    Main Methods:

    • Development of a novel observation equation incorporating dynamic acceleration and compass error correction.
    • Utilizing inertial sensors for motion data acquisition, avoiding the spatial limitations of optical systems.
    • Validation of the system's accuracy by comparing measurements with optical motion capture data for hand and forearm movements.

    Main Results:

    • The proposed observation equation effectively reduced posture and position errors in hand and forearm motion analysis.
    • The system demonstrated high accuracy in measuring complex hand movements, validated against optical motion capture.
    • Successful analysis of intricate hand actions like writing and spinning a top using the developed system.

    Conclusions:

    • The novel inertial sensor system provides accurate and reliable measurement of hand and forearm motions.
    • The developed observation equation is effective in mitigating integration errors, crucial for dynamic joint analysis.
    • This technology has significant potential for applications in fields requiring precise hand motion tracking.