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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| Format: | Article |
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MDPI AG
2022-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/24/9803 |
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| author | Victor Javier Kartsch Velu Prabhakar Kumaravel Simone Benatti Giorgio Vallortigara Luca Benini Elisabetta Farella Marco Buiatti |
| author_facet | Victor Javier Kartsch Velu Prabhakar Kumaravel Simone Benatti Giorgio Vallortigara Luca Benini Elisabetta Farella Marco Buiatti |
| author_sort | Victor Javier Kartsch |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T15:52:10Z |
| format | Article |
| id | doaj.art-050895a8f811459691df92c57fc1f49b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T15:52:10Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-050895a8f811459691df92c57fc1f49b2023-11-24T17:55:35ZengMDPI AGSensors1424-82202022-12-012224980310.3390/s22249803Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation AnalysisVictor Javier Kartsch0Velu Prabhakar Kumaravel1Simone Benatti2Giorgio Vallortigara3Luca Benini4Elisabetta Farella5Marco Buiatti6Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, 40136 Bologna, ItalyDigital Society Center, Fondazione Bruno Kessler, 38123 Trento, ItalyDepartment of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, 40136 Bologna, ItalyCenter for Mind/Brain Sciences (CIMeC), University of Trento, 38068 Rovereto, ItalyDepartment of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, 40136 Bologna, ItalyDigital Society Center, Fondazione Bruno Kessler, 38123 Trento, ItalyCenter for Mind/Brain Sciences (CIMeC), University of Trento, 38068 Rovereto, ItalyRecent 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.https://www.mdpi.com/1424-8220/22/24/9803SSVEPCCANCCAwearable EEGfrequency taggingdelta band |
| spellingShingle | Victor Javier Kartsch Velu Prabhakar Kumaravel Simone Benatti Giorgio Vallortigara Luca Benini Elisabetta Farella Marco Buiatti Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis Sensors SSVEP CCA NCCA wearable EEG frequency tagging delta band |
| title | Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis |
| title_full | Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis |
| title_fullStr | Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis |
| title_full_unstemmed | Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis |
| title_short | Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis |
| title_sort | efficient low frequency ssvep detection with wearable eeg using normalized canonical correlation analysis |
| topic | SSVEP CCA NCCA wearable EEG frequency tagging delta band |
| url | https://www.mdpi.com/1424-8220/22/24/9803 |
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