Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

A database of high-density surface electromyogram signals comprising 65 isometric hand gestures

Malešević, Nebojša LU ; Olsson, Alexander LU ; Sager, Paulina ; Andersson, Elin ; Cipriani, Christian ; Controzzi, Marco ; Björkman, Anders LU and Antfolk, Christian LU (2021) In Scientific Data 8(1).
Abstract

Control of contemporary, multi-joint prosthetic hands is commonly realized by using electromyographic signals from the muscles remaining after amputation at the forearm level. Although this principle is trying to imitate the natural control structure where muscles control the joints of the hand, in practice, myoelectric control provides only basic hand functions to an amputee using a dexterous prosthesis. This study aims to provide an annotated database of high-density surface electromyographic signals to aid the efforts of designing robust and versatile electromyographic control interfaces for prosthetic hands. The electromyographic signals were recorded using 128 channels within two electrode grids positioned on the forearms of 20... (More)

Control of contemporary, multi-joint prosthetic hands is commonly realized by using electromyographic signals from the muscles remaining after amputation at the forearm level. Although this principle is trying to imitate the natural control structure where muscles control the joints of the hand, in practice, myoelectric control provides only basic hand functions to an amputee using a dexterous prosthesis. This study aims to provide an annotated database of high-density surface electromyographic signals to aid the efforts of designing robust and versatile electromyographic control interfaces for prosthetic hands. The electromyographic signals were recorded using 128 channels within two electrode grids positioned on the forearms of 20 able-bodied volunteers. The participants performed 65 different hand gestures in an isometric manner. The hand movements were strictly timed using an automated recording protocol which also synchronously recorded the electromyographic signals and hand joint forces. To assess the quality of the recorded signals several quantitative assessments were performed, such as frequency content analysis, channel crosstalk, and the detection of poor skin-electrode contacts.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Scientific Data
volume
8
issue
1
article number
63
publisher
Nature Publishing Group
external identifiers
  • pmid:33602931
  • scopus:85101199343
ISSN
2052-4463
DOI
10.1038/s41597-021-00843-9
language
English
LU publication?
yes
id
d8c2d60f-334b-4ab7-8c66-7fc174ab3c7e
date added to LUP
2021-03-08 08:56:57
date last changed
2024-03-21 03:11:52
@article{d8c2d60f-334b-4ab7-8c66-7fc174ab3c7e,
  abstract     = {{<p>Control of contemporary, multi-joint prosthetic hands is commonly realized by using electromyographic signals from the muscles remaining after amputation at the forearm level. Although this principle is trying to imitate the natural control structure where muscles control the joints of the hand, in practice, myoelectric control provides only basic hand functions to an amputee using a dexterous prosthesis. This study aims to provide an annotated database of high-density surface electromyographic signals to aid the efforts of designing robust and versatile electromyographic control interfaces for prosthetic hands. The electromyographic signals were recorded using 128 channels within two electrode grids positioned on the forearms of 20 able-bodied volunteers. The participants performed 65 different hand gestures in an isometric manner. The hand movements were strictly timed using an automated recording protocol which also synchronously recorded the electromyographic signals and hand joint forces. To assess the quality of the recorded signals several quantitative assessments were performed, such as frequency content analysis, channel crosstalk, and the detection of poor skin-electrode contacts.</p>}},
  author       = {{Malešević, Nebojša and Olsson, Alexander and Sager, Paulina and Andersson, Elin and Cipriani, Christian and Controzzi, Marco and Björkman, Anders and Antfolk, Christian}},
  issn         = {{2052-4463}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Scientific Data}},
  title        = {{A database of high-density surface electromyogram signals comprising 65 isometric hand gestures}},
  url          = {{http://dx.doi.org/10.1038/s41597-021-00843-9}},
  doi          = {{10.1038/s41597-021-00843-9}},
  volume       = {{8}},
  year         = {{2021}},
}