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Real-Time Continuous Calibration of an EMG-Informed Neuromusculoskeletal Model for Assistive Exoskeleton Control.

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    IEEE ... International Conference on Rehabilitation Robotics : [Proceedings]
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    Summary

    This study introduces real-time neuromusculoskeletal (NMS) modeling with continuous calibration for controlling upper limb exoskeletons in neurorehabilitation. It enables personalized, adaptive control without pre-session calibration, improving usability.

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    Area of Science:

    • Biomedical Engineering
    • Rehabilitation Robotics
    • Computational Neuroscience

    Background:

    • Accurate real-time neuromusculoskeletal (NMS) modeling is essential for effective closed-loop neurorehabilitation systems.
    • Existing NMS models often require time-consuming pre-session calibration, limiting their clinical applicability.
    • Controlling upper limb exoskeletons demands precise and adaptive NMS models.

    Purpose of the Study:

    • To develop and validate a novel electromyography (EMG)-informed NMS modeling framework with continuous real-time calibration.
    • To assess the framework's performance in controlling an upper limb exoskeleton during functional tasks.
    • To compare the accuracy and control performance of continuously calibrated models against uncalibrated and offline calibrated models.

    Main Methods:

    • Developed an autodifferentiable NMS model incorporating a sliding window online calibration technique.
    • Validated the framework using an ArmeoPower exoskeleton during a functional reaching task.
    • Compared model accuracy and exoskeleton control performance across uncalibrated, offline calibrated, and continuously calibrated NMS models.

    Main Results:

    • The continuously calibrated model achieved accuracy comparable to offline calibration within 15 movement cycles (110 seconds).
    • Continuous calibration eliminated the need for pre-session model calibration.
    • Physiologically plausible joint moment predictions enabled exoskeleton control performance on par with offline calibrated models.

    Conclusions:

    • The proposed EMG-informed NMS modeling framework with continuous real-time calibration significantly enhances the usability of NMS models in real-time neurorehabilitation applications.
    • This adaptive approach offers personalized control for exoskeletons, dynamically adjusting to physiological changes like fatigue.
    • The framework represents a significant advancement for personalized and adaptive neurorehabilitation solutions.