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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...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
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
Descripción
Sumario: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.