Affordable Access

Access to the full text

Real-Time Control of a Multi-Degree-of-Freedom Mirror Myoelectric Interface During Functional Task Training

Authors
  • Sarasola-Sanz, Andrea1, 2
  • López-Larraz, Eduardo2, 3
  • Irastorza-Landa, Nerea1, 2
  • Rossi, Giulia2
  • Figueiredo, Thiago2
  • McIntyre, Joseph1
  • Ramos-Murguialday, Ander1, 2
  • 1 Neurotechnology Unit, TECNALIA, Basque Research and Technology Alliance, Donostia-San Sebastian , (Spain)
  • 2 Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen , (Germany)
  • 3 Bitbrain Technologies, Zaragoza , (Spain)
Type
Published Article
Journal
Frontiers in Neuroscience
Publisher
Frontiers Media SA
Publication Date
Mar 11, 2022
Volume
16
Identifiers
DOI: 10.3389/fnins.2022.764936
Source
Frontiers
Keywords
Disciplines
  • Neuroscience
  • Original Research
License
Green

Abstract

Motor learning mediated by motor training has in the past been explored for rehabilitation. Myoelectric interfaces together with exoskeletons allow patients to receive real-time feedback about their muscle activity. However, the number of degrees of freedom that can be simultaneously controlled is limited, which hinders the training of functional tasks and the effectiveness of the rehabilitation therapy. The objective of this study was to develop a myoelectric interface that would allow multi-degree-of-freedom control of an exoskeleton involving arm, wrist and hand joints, with an eye toward rehabilitation. We tested the effectiveness of a myoelectric decoder trained with data from one upper limb and mirrored to control a multi-degree-of-freedom exoskeleton with the opposite upper limb (i.e., mirror myoelectric interface) in 10 healthy participants. We demonstrated successful simultaneous control of multiple upper-limb joints by all participants. We showed evidence that subjects learned the mirror myoelectric model within the span of a five-session experiment, as reflected by a significant decrease in the time to execute trials and in the number of failed trials. These results are the necessary precursor to evaluating if a decoder trained with EMG from the healthy limb could foster learning of natural EMG patterns and lead to motor rehabilitation in stroke patients.

Report this publication

Statistics

Seen <100 times