Using Low-Power, Low-Cost IoT Processors in Clinical Biosignal Research: an In-depth Feasibility Check.


Journal

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
ISSN: 2694-0604
Titre abrégé: Annu Int Conf IEEE Eng Med Biol Soc
Pays: United States
ID NLM: 101763872

Informations de publication

Date de publication:
07 2020
Historique:
entrez: 6 10 2020
pubmed: 7 10 2020
medline: 23 10 2020
Statut: ppublish

Résumé

Research on biosignal (ExG) analysis is usually performed with expensive systems requiring connection with external computers for data processing. Consumer-grade low-cost wearable systems for bio-potential monitoring and embedded processing have been presented recently, but are not considered suitable for medical-grade analyses. This work presents a detailed quantitative comparative analysis of a recently presented fully-wearable low-power and low-cost platform (BioWolf) for ExG acquisition and embedded processing with two researchgrade acquisition systems, namely, ANTNeuro (EEG) and the Noraxon DTS (EMG). Our preliminary results demonstrate that BioWolf offers competitive performance in terms of electrical properties and classification accuracy. This paper also highlights distinctive features of BioWolf, such as real-time embedded processing, improved wearability, and energy-efficiency, which allows devising new types of experiments and usage scenarios for medical-grade biosignal processing in research and future clinical studies.

Identifiants

pubmed: 33018878
doi: 10.1109/EMBC44109.2020.9176002
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4008-4011

Auteurs

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Classifications MeSH