Sun, Hudun (2021) Multi-feature data fusion based on common space model and recurrent convolutional neural networks for EEG tristimania recognition used in upper limb rehabilitation exercises. EAI Endorsed Transactions on Scalable Information Systems.
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Abstract
Traditional tristimania recognition methods cannot accurately recognize the mood of patients, which cannot provide effective adjuvant therapy for rehabilitation. Therefore, this paper proposes a new multi-feature data fusion method for
Electroencephalography (EEG) tris
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 15:00 |
| Last Modified: | 11 Apr 2026 16:31 |
| URI: | http://eprints.eai.eu/id/eprint/37443 |
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