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    This study estimates human arm energy absorption using Excess of Passivity (EOP) derived from Forcemyography. This enhances robotic safety by regulating energy delivery in human-robot interactions, crucial for rehabilitation therapy.

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    Area of Science:

    • Robotics
    • Biomechanics
    • Human-Computer Interaction

    Background:

    • Human-robot interactions (HRIs) are increasingly used across industries, improving user experience.
    • Safety is paramount in HRIs, especially in high-risk environments like rehabilitation, space exploration, and mining.
    • Integrating biological user information into control systems can enhance HRI safety and performance.

    Purpose of the Study:

    • To estimate the energy-absorbing capabilities of the human arm.
    • To utilize the metric Excess of Passivity (EOP) for quantifying these capabilities.
    • To improve human-robot interaction safety by informing control system energy regulation.

    Main Methods:

    • Collected Excess of Passivity (EOP) data from healthy subjects.
    • Employed Forcemyography of the human arm to gather biological information.
    • Developed a protocol to estimate energy absorption based on Forcemyography and EOP.

    Main Results:

    • Successfully estimated the energy-absorbing capabilities of the human arm using EOP.
    • Demonstrated the feasibility of using Forcemyography for enhanced biological information acquisition.
    • Established a method to quantify human arm's passive energy dissipation.

    Conclusions:

    • The developed protocol provides a method for assessing human arm energy absorption.
    • This estimation technique can improve the safety of human-robot interactions by regulating energy delivery.
    • Clinical relevance: The protocol can assess rehabilitation patients' tolerance to robotic stimulation, aiding in assistive therapy design.