A Novel Approach to Classify Natural Grasp Actions by Estimating Muscle Activity Patterns from EEG Signals
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/9046668/9061585/09061627.pdf?arnumber=9061627
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Enhancing Classification of Grasping Tasks Using Hybrid EEG-sEMG Features;IFMBE Proceedings;2024
2. Multivariate Fast Iterative Filtering Based Automated System for Grasp Motor Imagery Identification Using EEG Signals;International Journal of Human–Computer Interaction;2023-11-20
3. AI-enabled Hybrid Model for Lower-Limb Movements Recognition using Estimated Muscular Activity from Cortical Brain Signals;IETE Journal of Research;2023-08-17
4. Hierarchical approach for fusion of electroencephalography and electromyography for predicting finger movements and kinematics using deep learning;Neurocomputing;2023-03
5. Decoding Multi-class Motor-related Intentions with User-optimized and Robust BCI System Based on Multimodal Dataset;2023 11th International Winter Conference on Brain-Computer Interface (BCI);2023-02-20
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