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Related Experiment Video

Updated: Mar 11, 2026

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
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An Intuitive, Bidirectional, and Adaptive Functional Electrical Stimulation System for Hand Rehabilitation.

Marshall A Trout, Clay T Stanley, Kristen M Saad

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |March 9, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an adaptive functional electrical stimulation (FES) system for hand rehabilitation. The FES system offers faster setup and more accurate, fatigue-adapting grip force control for stroke and spinal cord injury patients.

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    Area of Science:

    • Neuroscience
    • Rehabilitation Engineering
    • Biomedical Engineering

    Background:

    • Neuromotor injuries like stroke and spinal cord injury (SCI) significantly impair hand function, reducing patient independence and quality of life.
    • Functional electrical stimulation (FES) therapy shows promise for recovery, but its clinical use is limited by complex setup and lack of specialized systems.
    • Existing FES systems require lengthy setup times, hindering widespread adoption in hand therapy settings.

    Purpose of the Study:

    • To develop and validate a closed-loop, bidirectional FES system tailored for grasping rehabilitation.
    • To utilize an adaptive local model of muscle activation dynamics for precise grip force control.
    • To assess the system's performance, ease of use, and adaptability to muscle fatigue and patient-specific conditions.

    Main Methods:

    • A novel closed-loop, bidirectional FES system was designed, employing a first-order adaptive local model to control FES amplitude for grip force modulation.
    • The system's control accuracy was compared against an autotuned PID controller using 12 healthy participants.
    • System validation included testing with a C5 spinal cord injury participant and assessing performance during fatiguing contractions and setup time by untrained users.

    Main Results:

    • The adaptive controller demonstrated superior accuracy in grip force control compared to the autotuned PID controller in healthy participants.
    • The FES system effectively controlled grasping in a participant with C5 spinal cord injury exhibiting upper motor neuron spasticity.
    • The controller successfully adapted to muscle fatigue during prolonged use, with model parameters correlating strongly with fatigue, enabling real-time fatigue measurement.
    • An untrained user could set up the FES system in under 5 minutes.

    Conclusions:

    • Adaptive models offer significant benefits for FES control, leading to more accurate and responsive grasping rehabilitation.
    • The developed FES system is user-friendly, adaptable to fatigue, and effective for patients with neuromotor injuries, including SCI.
    • This work provides a foundation for designing more effective and clinically translatable FES systems for hand therapy.