Improved Multichannel Electromyograph Using Off-the-Shelf Components for Education and Research.
Arduino
EMG
electromyography
signal acquisition
signal conditioning
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
10 May 2022
10 May 2022
Historique:
received:
03
04
2022
revised:
02
05
2022
accepted:
04
05
2022
entrez:
28
5
2022
pubmed:
29
5
2022
medline:
1
6
2022
Statut:
epublish
Résumé
Most students and researchers with limited funding are often looking for simple and low-cost devices for the acquisition of the electromyogram signal (EMG) in an educational or research setting. Thus, off-the-shelf devices are used and they have already been described in the literature, but they are used without considering their real performances, which are, in general, quite poor from the electronic and signal processing points of view. It is the purpose of this communication to present the evidence of these issues, and to describe an improved version of the "classical" duo, composed of the common ECG/EMG Olimex board and the Arduino microprocessor board. In this case, the Arduino-DUE is used. Three main points are highlighted in this paper: (a) the bandpass characteristics of the ECG/EMG Olimex board and how they can be improved to cope with EMG bandwidth requirements; (b) the increase in sampling frequency of the signal; and, finally, (c) the possibility of automatic detection of more ECG/EMG Olimex boards installed at the same time as the shields on the Arduino-DUE board. Very simple and low-cost modifications on the ECG/EMG Olimex board could deliver a much better performing multichannel EMG acquisition system, suitable for educational classroom experiments and early proof-of-concept research.
Identifiants
pubmed: 35632029
pii: s22103616
doi: 10.3390/s22103616
pmc: PMC9143621
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Références
Sensors (Basel). 2019 Jul 20;19(14):
pubmed: 31330807
J Electromyogr Kinesiol. 2019 Dec;49:102363
pubmed: 31665683