Abstract
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.
Highlights
The development of mobile devices for the acquisition of brain and body signals [1,2], as well as of Brain Computer Interfaces (BCI) [3,4,5,6] for ecologic applications, such as driving or neuro-rehabilitation, requires HW/SW flexible platforms able to reliably acquire, synchronize and record multiple streams of different signals, compact enough not to limit movements or interactions, easy to be operated and interfaced with off-the-shelf sensors, and cost-effective [7].The growing development of BCI solutions has been paralleled by a flourishing increase of devices allowing to record brain and body signals wirelessly, i.e., in out-of-the-lab conditions
The most informative bio-potential is the electroencephalographic signal (EEG) that continues to be the most difficult to record in a real-life environment, as it reflects an uncontrolled mixture of several neural processes [12] that might be hard to dissociate
Results of the motor task returned no significant variation of the amplitude of power spectrum derived by the time-frequency decomposition of the EEG between the two acquisition systems for the C3 channel
Summary
The development of mobile devices for the acquisition of brain and body signals [1,2], as well as of Brain Computer Interfaces (BCI) [3,4,5,6] for ecologic applications, such as driving or neuro-rehabilitation, requires HW/SW flexible platforms able to reliably acquire, synchronize and record multiple streams of different signals, compact enough not to limit movements or interactions, easy to be operated and interfaced with off-the-shelf sensors, and cost-effective [7].The growing development of BCI solutions has been paralleled by a flourishing increase of devices allowing to record brain and body signals wirelessly, i.e., in out-of-the-lab conditions. BCI-based solutions are gaining attention for developing applications supporting industrial performance by optimizing the cognitive load of working operators, facilitating human-robot interactions, and making operations in critical conditions more secure [4]. These solutions often involve technical issues that limit the full exploitation of BCI and, more generally, brain-related assessments in real-life scenarios. EEG signal is often contaminated by different types of noise whose weight typically increases moving from the lab to real-life settings [13]
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