Author:

Keywords:

Science & Technology, Technology, Engineering, Biomedical, Engineering, Electroencephalography, Electrodes, Decoding, Scalp, Correlation, Wireless sensor networks, Auditory attention detection, brain-computer interface, channel selection, EEG processing, EEG sensor networks, WIRELESS EEG, SPEECH, REGRESSION, Attention, Auditory Perception, Brain-Computer Interfaces, Humans, Miniaturization, Monitoring, Ambulatory, Signal Processing, Computer-Assisted, STADIUS-19-04, C14/16/057#53765161, 0801 Artificial Intelligence and Image Processing, 0903 Biomedical Engineering, 0906 Electrical and Electronic Engineering, Biomedical Engineering, 4003 Biomedical engineering, 4009 Electronics, sensors and digital hardware, 4603 Computer vision and multimedia computation

Abstract:

OBJECTIVE: Concealable, miniaturized electroencephalography (mini-EEG) recording devices are crucial enablers toward long-term ambulatory EEG monitoring. However, the resulting miniaturization limits the inter-electrode distance and the scalp area that can be covered by a single device. The concept of wireless EEG sensor networks (WESNs) attempts to overcome this limitation by placing a multitude of these mini-EEG devices at various scalp locations. We investigate whether optimizing the WESN topology can compensate for miniaturization effects in an auditory attention detection (AAD) paradigm. METHODS: Starting from standard full-cap high-density EEG data, we emulate several candidate mini-EEG sensor nodes that locally collect EEG data with embedded electrodes separated by short distances. We propose a greedy group-utility based channel selection strategy to select a subset of these candidate nodes to form a WESN. We compare the AAD performance of this WESN with the performance obtained using long-distance EEG recordings. RESULTS: The AAD performance using short-distance EEG measurements is comparable to using an equal number of long-distance EEG measurements if, in both cases, the optimal electrode positions are selected. A significant increase in performance was found when using nodes with three electrodes over nodes with two electrodes. CONCLUSION: When the nodes are optimally placed, WESNs do not significantly suffer from EEG miniaturization effects in the case of AAD. SIGNIFICANCE: WESN-like platforms allow us to achieve similar AAD performance as with long-distance EEG recordings while adhering to the stringent miniaturization constraints for ambulatory EEG. Their applicability in an AAD task is important for the design of neuro-steered auditory prostheses.