Targeted Muscle Reinnervation for Real-time Myoelectric Control of Multifunction Artificial Arms
Open accessAbstract
CONTEXT: Improving the function of prosthetic arms remains a challenge, because access to the neural-control information for the arm is lost during amputation. A surgical technique called targeted muscle reinnervation (TMR) transfers residual arm nerves to alternative muscle sites. After reinnervation, these target muscles produce electromyogram (EMG) signals on the surface of the skin that can be measured and used to control prosthetic arms. 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. CONCLUSION: These results suggest that reinnervated muscles can produce sufficient EMG information for real-time control of advanced artificial arms.
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TMR necessarily cuts nerve branches to residual muscles and denervates existing muscle.
“as is necessary in TMR (29).”
From A regenerative peripheral nerve interface allows real-time control of an artificial hand in upper limb amputees (2020) · cites this paper as [29]
The Introduction (page unavailable) says TMR transfers remaining arm nerves to residual muscles, and the Methods (page unavailable) identify muscles that received those transfers. Our copy does not say that TMR necessarily cuts the target muscles’ existing nerve branches or denervates existing muscle. (LLM, conf=0.83)
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- Authors
- Kuiken, T. A.
- Affiliations
- Shirley Ryan AbilityLab (US)
- Corresponding author
- Kuiken, Todd A.
- ORCID
- Kuiken, Todd A.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2009-02-11
- Volume
- 301
- Issue
- 6
- Pages
- 619
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC3036162
- OpenAlex
- W2122612627
- Cited by
- 1,089
- References
- 24
- Citations by year
- 2026: 42 · 2025: 44 · 2024: 51 · 2023: 68 · 2022: 53 · 2021: 85 · 2020: 74 · 2019: 77 · 2018: 79 · 2017: 77 · 2016: 73 · 2015: 60 · 2014: 80 · 2013: 75 · 2012: 42
- FWCI
- 29.83
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01hd043137-05)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01 HD-043137, R01HD044798)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Keywords
- targeted muscle reinnervation, myoelectric control, upper limb amputation, prosthetic arm, surface electromyography, pattern recognition, transhumeral amputation, real-time control
- MeSH terms
- Adult, Amputation, Surgical, Amputation Stumps, Arm, Artificial Limbs, Electromyography, Female, Humans, Male, Middle Aged, Movement, Pattern Recognition, Automated, Prosthesis Design, Nerve Transfer, Muscle, Skeletal, Young Adult
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