Robotic leg control with EMG decoding in an amputee with nerve transfers.
The clinical application of robotic technology to powered prosthetic knees and ankles is limited by the lack of a robust control strategy. We found that the use of electromyographic (EMG) signals from natively innervated and surgically reinnervated residual thigh muscles in a patient who had undergone knee amputation improved control of a robotic leg prosthesis. EMG signals were decoded with a pattern-recognition algorithm and combined with data from sensors on the prosthesis to interpret the patient's intended movements. This provided robust and intuitive control of ambulation--with seamless transitions between walking on level ground, stairs, and ramps--and of the ability to reposition the leg while the patient was seated.
Center 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
Levi J
LJ
Hargrove
Ann M
AM
Simon
Aaron J
AJ
Young
Robert D
RD
Lipschutz
Suzanne B
SB
Finucane
Douglas G
DG
Smith
Todd A
TA
Kuiken
D000063:Accidents, Traffic; D000328:Adult; D000671:Amputation, Surgical / Q000379:methods; D000674:Amputees / Q000534:rehabilitation; D001186:Artificial Limbs; D004576:Electromyography; D006801:Humans; D007866:Leg / Q000294:innervation* / Q000502:physiology / Q000601:surgery; D009049:Motorcycles; D018482:Muscle, Skeletal / Q000294:innervation* / Q000502:physiology / Q000601:surgery; D016067:Nerve Transfer; D011187:Posture; D012371:Robotics; D016138:Walking / Q000502:physiology*