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Robotic leg control with EMG decoding in an amputee with nerve transfers
Levi J Hargrove1, Ann M Simon, Aaron J Young
1Center for Bionic Medicine, Rehabilitation Institute of Chicago, and the Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois 60611, USA. l-hargrove@northwestern.edu
The New England Journal of Medicine
|September 27, 2013
Summary
Researchers improved robotic leg prosthesis control using electromyographic (EMG) signals from residual thigh muscles. This allows intuitive control for amputees, enabling seamless transitions between different terrains and seated repositioning.
Area of Science:
- Biomedical Engineering
- Neuroprosthetics
- Robotics
Background:
- Clinical use of robotic prosthetics is hindered by inadequate control strategies.
- Powered prosthetic knees and ankles require advanced control for effective patient use.
Observation:
- Electromyographic (EMG) signals from residual thigh muscles, both natively innervated and surgically reinnervated, were utilized.
- A pattern-recognition algorithm was employed to decode these EMG signals.
Findings:
- Decoding EMG signals and integrating prosthesis sensor data enabled intuitive interpretation of patient's intended movements.
- This approach resulted in robust control of ambulation, including seamless transitions across level ground, stairs, and ramps.
- The system also facilitated effortless repositioning of the prosthetic leg while the patient was seated.
Implications:
- This advancement offers a more intuitive and robust control strategy for robotic leg prostheses.
- It has the potential to significantly enhance the quality of life and mobility for individuals with lower-limb amputations.
- Further development could lead to more natural and adaptable prosthetic limb functionality.
