Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis

Recent studies show that the integrity of core perceptual and cognitive functions may be tested in a short time with Steady-State Visual Evoked Potentials (SSVEP) with low stimulation frequencies, between 1 and 10 Hz. Wearable EEG systems provide unique opportunities to test these brain functions on...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-12, Vol.22 (24), p.9803
Main Authors: Kartsch, Victor Javier, Kumaravel, Velu Prabhakar, Benatti, Simone, Vallortigara, Giorgio, Benini, Luca, Farella, Elisabetta, Buiatti, Marco
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Brain-Computer Interfaces
Canonical Correlation Analysis
CCA
Correlation analysis
delta band
Electrodes
Electroencephalography
Electroencephalography - methods
Energy efficiency
Evoked Potentials, Visual
frequency tagging
Medical research
Medicine, Experimental
NCCA
Newborn babies
Noise levels
Photic Stimulation - methods
Signal processing
SSVEP
Stimulation
wearable EEG
Wearable Electronic Devices
Wearable technology
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Summary:Recent studies show that the integrity of core perceptual and cognitive functions may be tested in a short time with Steady-State Visual Evoked Potentials (SSVEP) with low stimulation frequencies, between 1 and 10 Hz. Wearable EEG systems provide unique opportunities to test these brain functions on diverse populations in out-of-the-lab conditions. However, they also pose significant challenges as the number of EEG channels is typically limited, and the recording conditions might induce high noise levels, particularly for low frequencies. Here we tested the performance of Normalized Canonical Correlation Analysis (NCCA), a frequency-normalized version of CCA, to quantify SSVEP from wearable EEG data with stimulation frequencies ranging from 1 to 10 Hz. We validated NCCA on data collected with an 8-channel wearable wireless EEG system based on BioWolf, a compact, ultra-light, ultra-low-power recording platform. The results show that NCCA correctly and rapidly detects SSVEP at the stimulation frequency within a few cycles of stimulation, even at the lowest frequency (4 s recordings are sufficient for a stimulation frequency of 1 Hz), outperforming a state-of-the-art normalized power spectral measure. Importantly, no preliminary artifact correction or channel selection was required. Potential applications of these results to research and clinical studies are discussed.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22249803