Paper

Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions from Limited Data

7 days ago   |   By EMBS

Non-parametric regression has been shown to be useful in extracting relevant features from Local Field Potential signals for decoding motor intentions. Yet, in many instances, brain-computer interfaces rely on simple classification methods, circumventing deep neural networks due to limited training data. This paper leverages the robustness of several important results in non-parametric...
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Decoding Finger Tapping with the Affected Hand in Chronic Stroke Patients During Motor Imagery and Execution

7 days ago   |   By EMBS

In stroke rehabilitation, motor imagery based on a brain-computer interface is an extremely useful method to control an external device and utilize neurofeedback. Many studies have reported on the classification performance of motor imagery to decode individual fingers in stroke patients compared with healthy controls. However, classification performance for a given limb is still low...
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