Abstract
Purpose: The electroencephalography (EEG) signals recorded in clinical settings are usually corrupted by electrooculography (EOG) artifacts. EEMD-ICA is a commonly used method for removing EOG artifacts. This study aims at exploring the performance of different methods of identification of artifactual components under the framework of EEMD-ICA.
Methods: This study is conducted in a semi-simulated way. A EEG dataset covering signal of SNR from -1 to 2 is generated based on the EEG and EOG segments from two public datasets. Characterized by the artifactual components identification method, EEMD-ICA kurt, EEMD-ICA entropy, EEMD-ICA autocor and EEMD-ICA eogcor are proposed and evaluated in terms of Normalized Mean Square Error (NMSE), Cross Correlation (CC) and Structural Similarity Index (SSIM) on this dataset. Results: EEMD-ICA autocor outperforms other three approaches and demonstrates the strongest versatility. Besides successfully eliminating EOAs from EEG signals, it loses the least neuron activities.
Conclusion: Although performance metrics improve as SNR increases, the loss of structure information also improves (SNR > 1). In practice, it is vital to estimate the SNR of data before applying these approaches because when SNR is high, these methods may have a counterproductive.
Original language | English |
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Title of host publication | Internet of Things of Big Data for Healthcare - 5th International Workshop, IoTBDH 2023, Proceedings |
Editors | Jun Qi, Po Yang |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 111-123 |
Number of pages | 13 |
ISBN (Print) | 9783031522154 |
DOIs | |
Publication status | Published - 2024 |
Event | 5th International Workshop on Internet of Things of Big Data for Healthcare, IoTBDH 2023 - Birmingham, United Kingdom Duration: 21 Oct 2023 → 25 Oct 2023 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 2019 CCIS |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference
Conference | 5th International Workshop on Internet of Things of Big Data for Healthcare, IoTBDH 2023 |
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Country/Territory | United Kingdom |
City | Birmingham |
Period | 21/10/23 → 25/10/23 |
Keywords
- Artifact
- EEG
- EEMD
- ICA
- Removal