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    This study shows that robotic exoskeleton sensors can detect user gait intentions without direct human sensing. This advance could improve exoskeleton usability for rehabilitation and mobility assistance.

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    Area of Science:

    • Robotics
    • Biomechanics
    • Rehabilitation Engineering

    Background:

    • Robotic exoskeletons offer potential for rehabilitation and locomotion support.
    • Current methods for detecting user gait intentions are often complex or invasive.
    • Wider adoption of exoskeletons is hindered by challenges in intent detection.

    Purpose of the Study:

    • To investigate the feasibility of using only onboard exoskeleton sensors for user intent detection.
    • To assess if joint positions and motor currents can indicate changes in intended gait speed.
    • To evaluate the effectiveness of this approach for both able-bodied and non-able-bodied users.

    Main Methods:

    • A pilot study was conducted using onboard sensors within a robotic exoskeleton.
    • Joint position and commanded motor current data were collected.
    • Data were analyzed before and after users intended to change their gait speed.

    Main Results:

    • Significant differences in joint positions and motor currents were observed after gait intention changes.
    • These differences were evident in both able-bodied and non-able-bodied participants.
    • Intent detection signals were influenced by control settings, user ability, and timing.

    Conclusions:

    • Onboard sensors alone can potentially identify user gait intentions in robotic exoskeletons.
    • This approach avoids the complexities of direct human sensing methods.
    • Further research is needed to optimize intent detection based on various factors.