MyoGestic: EMG interfacing framework for decoding multiple spared motor dimensions in individuals with neural lesions

Science Advances, 2025 · DOI: 10.1126/sciadv.ads9150 · Published: April 9, 2025

Assistive Technology Neurology Biomedical

Simple Explanation

The study introduces MyoGestic, a wireless, high-density EMG bracelet and software framework, designed to decode motor intent in individuals with neural lesions such as spinal cord injuries, strokes, or amputations. The system allows for rapid adaptation of machine learning models to individual users, enabling real-time decoding of spared motor dimensions, which can then be used to control various devices. MyoGestic promotes a collaborative and iterative development of myocontrol algorithms, fostering a partnership between researchers and participants to advance intuitive EMG interfaces.

Study Duration

Not specified

Participants

Two participants with traumatic SCI, two with spinal stroke, and three with amputations

Evidence Level

Not specified

Key Findings

1
The study successfully decoded motor intent in real time from participants with SCI, spinal stroke, and amputations, achieving multiple controllable motor dimensions within minutes.
2
Decoded neural signals were used to control a digitally rendered hand, an orthosis, a prosthesis, and a two-dimensional cursor, showcasing the versatility of the system.
3
The lightweight EMG bracelet and software framework facilitate rapid adaptability to the needs of impaired participants, enabling immediate validation of new hand movements.

Research Summary

The study introduces MyoGestic, a neural interface system that includes a 32-channel monopolar EMG bracelet and an open-source software framework designed for rapid experimentation and adaptation to participant-specific needs. MyoGestic enables the real-time decoding of multiple distinctive gestures from participants with SCI and amputations, allowing them to control a virtual hand, orthosis, prosthesis, or a 2D cursor. The framework supports a collaborative approach to decoding preserved motor intent, where participant feedback is integrated immediately, potentially serving as a generalized tool for both researchers and clinicians.

Practical Implications

Enhanced Motor Recovery

MyoGestic can maximize motor recovery by enabling real-time decoding of motor intentions in individuals with neural lesions.

Improved Assistive Device Control

The system can be used to intuitively control various assistive devices, such as orthoses and prostheses, improving the quality of life for individuals with motor impairments.

Accelerated Research

The open-source framework facilitates rapid experimentation and adaptation, enabling researchers to iterate on myocontrol algorithms more quickly.

Study Limitations

1
The hardware was not tailored to the shape and size of the patient anatomy.
2
The bracelets cannot perfectly conform to the preserved anatomy, resulting in noisy channels due to suboptimal skin-electrode contact.
3
Limited data recorded in this study may not be sufficient for achieving reliable longitudinal control.

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