Performance Analysis and Comparison of Classification Algorithms for EEG-Based BCI System
| Autor: | Mandeep Kaur Ghumman, Balkrishan Jindal, Navtej Singh |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Signal processing
medicine.diagnostic_test Computer science business.industry Interface (computing) Feature extraction ComputerApplications_COMPUTERSINOTHERSYSTEMS Pattern recognition Electroencephalography Signal Statistical classification Motor imagery medicine Artificial intelligence business Brain–computer interface |
| Zdroj: | Proceedings of Sixth International Congress on Information and Communication Technology ISBN: 9789811617805 ICICT (3) |
| DOI: | 10.1007/978-981-16-1781-2_77 |
| Popis: | The signals emanating from the human scalp due to motor imagery activity happening in the brain can be fetched using various techniques. Electroencephalogram (EEG) is a popular signal fetching technique for providing input to the brain-computer interface system. This field of signal processing can be used for the rehabilitation of patients suffering from neurological disorders. It can also be used in a variety of other applications including environmental control, device communication, and mobility devices. Artificial intelligence techniques can be used to implement various phases of brain-computer interface. In this paper, we have discussed, evaluated, and compared the performance of many such popular techniques used for the classification of the EEG signals. |
| Databáze: | OpenAIRE |
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