Enhancing Motor Imagery based Brain Computer Interfaces for Stroke Rehabilitation

Author:

Soni Saher1ORCID,Chaudhary Shivam1ORCID,Miyapuram Krishna Prasad1ORCID

Affiliation:

1. Indian Institute of Technology, Gandhinagar, India

Publisher

ACM

Reference44 articles.

1. Visual-Electrotactile Stimulation Feedback to Improve Immersive Brain-Computer Interface Based on Hand Motor Imagery

2. Hamdi Altaheri, Ghulam Muhammad, Mansour Alsulaiman, Syed Umar Amin, Ghadir Ali Altuwaijri, Wadood Abdul, Mohamed A Bencherif, and Mohammed Faisal. 2021. Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review. Neural Computing and Applications (2021), 1–42.

3. Mohamed Athif and Hongliang Ren. 2019. WaveCSP: a robust motor imagery classifier for consumer EEG devices. Australasian physical & engineering sciences in medicine 42 (2019), 159–168.

4. Suresh Balakrishnama and Aravind Ganapathiraju. 1998. Linear discriminant analysis-a brief tutorial. Institute for Signal and information Processing 18, 1998 (1998), 1–8.

5. Motor Imagery Hand Movement Direction Decoding Using Brain Computer Interface to Aid Stroke Recovery and Rehabilitation

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