會議論文
| 學年 | 109 |
|---|---|
| 學期 | 1 |
| 發表日期 | 2020-11-24 |
| 作品名稱 | Classification of Music-Induced Mental States Using Convolutional Neural Networks for an EEG Study |
| 作品名稱（其他語言） | |
| 著者 | Kit Hwa Cheah; Humaira Nisar; Chi-Yi Tsai |
| 作品所屬單位 | |
| 出版者 | |
| 會議名稱 | Proceedings of the 12th National Technical Seminar on Unmanned System Technology |
| 會議地點 | Malaysia |
| 摘要 | Electroencephalogram (EEG) is the brain signal acquired through multiple channels and is packed with useful information for the mental state recognition. EEG has wide applicability in the field of medicine (e.g. pre-disease risk estimation, disease characterization, prognosis, treatment monitoring), psycho-physiological research (e.g., affective state classification, stress assessment, alertness monitoring, sleep stage identification), human–computer interaction (e.g. thought typing, prosthetic limb control), and many other areas. However, manual EEG feature selection is time-consuming and challenging to fully make use of the relevant information embedded in the EEG signals. Deep learning (DL), while enabling high hierarchical abstract representation of complex data, has been strongly indicated by recent research works to be generally outperforming the manual EEG feature extraction algorithms and classical classifiers. In this study, different neural network architectures have been constructed for binary classification of an EEG using a dataset that showed no significant statistical difference between its two data categories (baseline resting EEG and EEG while listening to music) with traditional EEG feature extraction methods. The two-convolutional-path Convolutional Neural Network (CNN) model examined in this study shows higher validation accuracy (75 ± 1%) than the single-convolutional-path CNN model examined which had achieved accuracy of 71.5 ± 2% using the same EEG dataset. The effects of different architectural components and model training hyperparameters on the models’ validation performance are also studied and presented. |
| 關鍵字 | Electroencephalogram (EEG);Convolutional neural network (CNN);Music and binaural beats |
| 語言 | en_US |
| 收錄於 | |
| 會議性質 | 國際 |
| 校內研討會地點 | 無 |
| 研討會時間 | 20201124~20201125 |
| 通訊作者 | |
| 國別 | MYS |
| 公開徵稿 | |
| 出版型式 | |
| 出處 | Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020, p. 383-401 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/122622 ) |