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Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies
Nowadays, the growing interest in gathering physiological data and human behavior in everyday life scenarios is paralleled by an increase in wireless devices recording brain and body signals. However, the technical issues that characterize these solutions often limit the full brain-related assessmen...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8707223/ https://www.ncbi.nlm.nih.gov/pubmed/34960261 http://dx.doi.org/10.3390/s21248167 |
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author | Ascari, Luca Marchenkova, Anna Bellotti, Andrea Lai, Stefano Moro, Lucia Koshmak, Konstantin Mantoan, Alice Barsotti, Michele Brondi, Raffaello Avveduto, Giovanni Sechi, Davide Compagno, Alberto Avanzini, Pietro Ambeck-Madsen, Jonas Vecchiato, Giovanni |
author_facet | Ascari, Luca Marchenkova, Anna Bellotti, Andrea Lai, Stefano Moro, Lucia Koshmak, Konstantin Mantoan, Alice Barsotti, Michele Brondi, Raffaello Avveduto, Giovanni Sechi, Davide Compagno, Alberto Avanzini, Pietro Ambeck-Madsen, Jonas Vecchiato, Giovanni |
author_sort | Ascari, Luca |
collection | PubMed |
description | Nowadays, the growing interest in gathering physiological data and human behavior in everyday life scenarios is paralleled by an increase in wireless devices recording brain and body signals. However, the technical issues that characterize these solutions often limit the full brain-related assessments in real-life scenarios. Here we introduce the Biohub platform, a hardware/software (HW/SW) integrated wearable system for multistream synchronized acquisitions. This system consists of off-the-shelf hardware and state-of-art open-source software components, which are highly integrated into a high-tech low-cost solution, complete, yet easy to use outside conventional labs. It flexibly cooperates with several devices, regardless of the manufacturer, and overcomes the possibly limited resources of recording devices. The Biohub was validated through the characterization of the quality of (i) multistream synchronization, (ii) in-lab electroencephalographic (EEG) recordings compared with a medical-grade high-density device, and (iii) a Brain-Computer-Interface (BCI) in a real driving condition. Results show that this system can reliably acquire multiple data streams with high time accuracy and record standard quality EEG signals, becoming a valid device to be used for advanced ergonomics studies such as driving, telerehabilitation, and occupational safety. |
format | Online Article Text |
id | pubmed-8707223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87072232021-12-25 Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies Ascari, Luca Marchenkova, Anna Bellotti, Andrea Lai, Stefano Moro, Lucia Koshmak, Konstantin Mantoan, Alice Barsotti, Michele Brondi, Raffaello Avveduto, Giovanni Sechi, Davide Compagno, Alberto Avanzini, Pietro Ambeck-Madsen, Jonas Vecchiato, Giovanni Sensors (Basel) Article Nowadays, the growing interest in gathering physiological data and human behavior in everyday life scenarios is paralleled by an increase in wireless devices recording brain and body signals. However, the technical issues that characterize these solutions often limit the full brain-related assessments in real-life scenarios. Here we introduce the Biohub platform, a hardware/software (HW/SW) integrated wearable system for multistream synchronized acquisitions. This system consists of off-the-shelf hardware and state-of-art open-source software components, which are highly integrated into a high-tech low-cost solution, complete, yet easy to use outside conventional labs. It flexibly cooperates with several devices, regardless of the manufacturer, and overcomes the possibly limited resources of recording devices. The Biohub was validated through the characterization of the quality of (i) multistream synchronization, (ii) in-lab electroencephalographic (EEG) recordings compared with a medical-grade high-density device, and (iii) a Brain-Computer-Interface (BCI) in a real driving condition. Results show that this system can reliably acquire multiple data streams with high time accuracy and record standard quality EEG signals, becoming a valid device to be used for advanced ergonomics studies such as driving, telerehabilitation, and occupational safety. MDPI 2021-12-07 /pmc/articles/PMC8707223/ /pubmed/34960261 http://dx.doi.org/10.3390/s21248167 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ascari, Luca Marchenkova, Anna Bellotti, Andrea Lai, Stefano Moro, Lucia Koshmak, Konstantin Mantoan, Alice Barsotti, Michele Brondi, Raffaello Avveduto, Giovanni Sechi, Davide Compagno, Alberto Avanzini, Pietro Ambeck-Madsen, Jonas Vecchiato, Giovanni Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies |
title | Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies |
title_full | Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies |
title_fullStr | Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies |
title_full_unstemmed | Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies |
title_short | Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies |
title_sort | validation of a novel wearable multistream data acquisition and analysis system for ergonomic studies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8707223/ https://www.ncbi.nlm.nih.gov/pubmed/34960261 http://dx.doi.org/10.3390/s21248167 |
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