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An Efficient Multi-Class MI Based BCI Scheme Using Statistical Fusion Techniques of Classifiers., , and . TENCON, page 378-382. IEEE, (2019)Automatic quality classification of entire electrocardiographic recordings obtained with a novel patch type recorder., , , , , , and . EMBC, page 5639-5642. IEEE, (2014)An end-to-end deep learning approach to MI-EEG signal classification for BCIs., , , and . Expert Syst. Appl., (2018)A Deep Learning MI - EEG Classification Model for BCIs., , , and . EUSIPCO, page 1676-1679. IEEE, (2018)Adaptive CSP for User Independence in MI-BCI Paradigm for Upper Limb Stroke Rehabilitation., , , and . GlobalSIP, page 420-423. IEEE, (2018)An adaptive CSP filter to investigate user independence in a 3-class MI-BCI paradigm., , , and . Comput. Biol. Medicine, (2018)FBCSP and Adaptive Boosting for Multiclass Motor Imagery BCI Data Classification: A Machine Learning Approach., , , , and . SMC, page 1275-1279. IEEE, (2020)Motor Imagery based Brain Computer Interface Paradigm for Upper Limb Stroke Rehabilitation., and . EMBC, page 1960-1963. IEEE, (2018)Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: From designing to application., , , and . Comput. Biol. Medicine, (2020)