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Estimation of the Operating Force From the Human Motion.

Ming Ding, Ryuzo Baba, Kristada Masanthia

    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 novel, sensor-free method to estimate hand operating forces during object manipulation by analyzing human motion. The technique accurately predicts forces for pushing, pulling, and lifting tasks using biomechanical models.

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    Area of Science:

    • Biomechanics
    • Human-Computer Interaction
    • Robotics

    Background:

    • Estimating forces in human object interaction is crucial for robotics and ergonomics.
    • Current methods often require intrusive sensors on humans or objects.

    Purpose of the Study:

    • To develop and validate a non-invasive method for estimating hand operating forces.
    • To enable accurate force estimation solely from observable human motion.

    Main Methods:

    • Utilized measured joint angles to compute center of mass and hand position via a human biomechanical model.
    • Applied principles of force and moment balance using a dynamic model to estimate operating forces.
    • Experimentally validated the method with human subjects performing box pushing, pulling, and lifting tasks.

    Main Results:

    • The proposed method successfully estimated hand operating forces for various object manipulation tasks.
    • Experimental results demonstrated a high degree of accuracy when comparing estimated and measured forces.
    • The effectiveness of the non-invasive, motion-based force estimation was verified.

    Conclusions:

    • The developed method offers a viable, sensor-free approach for estimating human operating forces.
    • This technique has potential applications in human-robot collaboration, ergonomic analysis, and virtual reality.
    • Future work could extend the method to more complex manipulation scenarios and object types.