Control Strategies and Performance Assessment of Upper-Limb TMR Prostheses: A Review.

Targeted Muscle Reinnervation (TMR) multi-DoF control pattern recognition prosthesis prosthetic control upper limb amputee

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
10 Mar 2021
Historique:
received: 29 01 2021
revised: 26 02 2021
accepted: 05 03 2021
entrez: 3 4 2021
pubmed: 4 4 2021
medline: 29 4 2021
Statut: epublish

Résumé

The evolution of technological and surgical techniques has made it possible to obtain an even more intuitive control of multiple joints using advanced prosthetic systems. Targeted Muscle Reinnervation (TMR) is considered to be an innovative and relevant surgical technique for improving the prosthetic control for people with different amputation levels of the limb. Indeed, TMR surgery makes it possible to obtain reinnervated areas that act as biological amplifiers of the motor control. On the technological side, a great deal of research has been conducted in order to evaluate various types of myoelectric prosthetic control strategies, whether direct control or pattern recognition-based control. In the literature, different control performance metrics, which have been evaluated on TMR subjects, have been introduced, but no accepted reference standard defines the better strategy for evaluating the prosthetic control. Indeed, the presence of several evaluation tests that are based on different metrics makes it difficult the definition of standard guidelines for comprehending the potentiality of the proposed control systems. Additionally, there is a lack of evidence about the comparison of different evaluation approaches or the presence of guidelines on the most suitable test to proceed for a TMR patients case study. Thus, this review aims at identifying these limitations by examining the several studies in the literature on TMR subjects, with different amputation levels, and proposing a standard method for evaluating the control performance metrics.

Identifiants

pubmed: 33802231
pii: s21061953
doi: 10.3390/s21061953
pmc: PMC8000641
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : European Commission
ID : 899822
Organisme : Istituto Nazionale per l'Assicurazione Contro Gli Infortuni sul Lavoro
ID : E59E19001460005

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Auteurs

Federico Mereu (F)

Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.

Francesca Leone (F)

Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.

Cosimo Gentile (C)

Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.

Francesca Cordella (F)

Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.

Emanuele Gruppioni (E)

INAIL Prosthetic Center, 40054 Vigorso di Budrio, Italy.

Loredana Zollo (L)

Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.

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Classifications MeSH