Transactions on Neural Systems and Rehabilitation Engineering

Featured Articles
Classification of Electromyographic Hand Gesture Signals Using Modified Fuzzy C-Means Clustering and Two-Step Machine Learning Approach
Understanding and classifying electromyogram (EMG) signals is of significance for dexterous prosthetic hand control, sign languages, grasp recognition, human-machine interaction, etc.. The existing research of EMG-based hand gesture classification faces the challenges of unsatisfied classification accuracy, insufficient generalization ability, lack... Read more
Featured Articles
Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces
     Neuroprosthesis enables the brain control on the external devices purely using neural activity for paralyzed people. Supervised learning decoders recalibrate or re-fit the discrepancy between the desired target and decoder’s output, where the correction may over-dominate the user’s intention. Reinforcement... Read more
Featured Articles, Special Issue: BRAIN
Learning Recurrent Waveforms within EEGs
Austin J. Brockmeier,  Jose C. Principe, University of Liverpool, UK, University of Florida, USA When experts analyze EEGs they look for landmarks in the traces corresponding to established waveform patterns, such as phasic events of particular frequency or morphology. Lengthy records motivate automated analysis... Read more