| Autor: |
Suma KV; Department of Electronics and Communication, MS Ramaiah Institute of Technology, Bangalore, India., Lingaraju GM; Department of Information Science and Engineering, MS Ramaiah Institute of Technology, Bangalore, India., Dinesh PA; Department of Mathematics, M. S. Ramaiah Institute of Technology, Bangalore - 560 054, India., Nivedha R; Department of Electronics and Communication, MS Ramaiah Institute of Technology, Bangalore, India. |
| Jazyk: |
angličtina |
| Zdroj: |
Critical reviews in biomedical engineering [Crit Rev Biomed Eng] 2020; Vol. 48 (1), pp. 17-28. |
| DOI: |
10.1615/CritRevBiomedEng.2020033161 |
| Abstrakt: |
We sort human emotions using Russell's circumplex model of emotion by classifying electroencephalogram (EEG) signals from 25 subjects into four discrete states, namely, happy, sad, angry, and relaxed. After acquiring signals, we use a standard database for emotion analysis using physiological EEG signals. Once raw signals are pre-processed in an EEGLAB, we perform feature extraction using Matrix Laboratory and apply discrete wavelet transform. Before classifying we optimize extracted features with particle swarm optimization. The acquired set of EEG signals are validated after finding average classification accuracy of 75.25%, average sensitivity of 76.8%, and average specificity of 91.06%. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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