articleJAMAFeb 10, 2009GREEN OA

Targeted Muscle Reinnervation for Real-time Myoelectric Control of Multifunction Artificial Arms

Shirley Ryan AbilityLab

PubMed
Indexed incrossrefpubmed

Abstract

Objective

To assess the performance of patients with upper-limb amputation who had undergone TMR surgery, using a pattern-recognition algorithm to decode EMG signals and control prosthetic-arm motions. DESIGN, SETTING, AND PARTICIPANTS: Study conducted between January 2007 and January 2008 at the Rehabilitation Institute of Chicago among 5 patients with shoulder-disarticulation or transhumeral amputations who underwent TMR surgery between February 2002 and October 2006 and 5 control participants without amputation. Surface EMG signals were recorded from all participants and decoded using a pattern-recognition algorithm. The decoding program controlled the movement of a virtual prosthetic arm. All participants were instructed to perform various arm movements, and their abilities to control the virtual prosthetic arm were measured. In addition, TMR patients used the same control system to operate advanced arm prosthesis prototypes. MAIN OUTCOME MEASURE: Performance metrics measured during virtual arm movements included motion selection time, motion completion time, and motion completion ("success") rate.

Results

The TMR patients were able to repeatedly perform 10 different elbow, wrist, and hand motions with the virtual prosthetic arm. For these patients, the mean motion selection and motion completion times for elbow and wrist movements were 0.22 seconds (SD, 0.06) and 1.29 seconds (SD, 0.15), respectively. These times were 0.06 seconds and 0.21 seconds longer than the mean times for control participants. For TMR patients, the mean motion selection and motion completion times for hand-grasp patterns were 0.38 seconds (SD, 0.12) and 1.54 seconds (SD, 0.27), respectively. These patients successfully completed a mean of 96.3% (SD, 3.8) of elbow and wrist movements and 86.9% (SD, 13.9) of hand movements within 5 seconds, compared with 100% (SD, 0) and 96.7% (SD, 4.7) completed by controls. Three of the patients were able to demonstrate the use of this control system in advanced prostheses, including motorized shoulders, elbows, wrists, and hands.

Citation impact

1,100
total citations
FWCI
34.66
Percentile
100%
References
24
Citations per year

Authors

1

Topics & keywords

Keywords
  • Medicine
  • Reinnervation
  • Wrist
  • Physical medicine and rehabilitation
  • Amputation
  • Elbow
  • Prosthesis
  • Electromyography
UN Sustainable Development Goals
  • Good health and well-being
No related works found for this paper.