Recovery of Volitional Motor Control and Overground Walking in Participants With Chronic Clinically Motor Complete Spinal Cord Injury: Restoration of Rehabilitative Function With Epidural Spinal Stimulation (RESTORES) Trial-A Preliminary Study.

Spinal cord injury (SCI) is damage to any part of the spinal cord resulting in paralysis, bowel and/or bladder incontinence, and loss of sensation and other bodily functions. Current treatments for chronic SCI are focused on managing symptoms and preventing further damage to the spinal cord with limited neuro-restorative interventions. Recent research and independent clinical trials of spinal cord stimulation (SCS) or intensive neuro-rehabilitation including neuro-robotics in participants with SCI have suggested potential malleability of the neuronal networks for neurological recovery.

A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson's disease.

Objective: This study seeks to systematically review the selection of features and algorithms for machine learning and automation in deep brain stimulation surgery (DBS) for Parkinson's disease. This will assist in consolidating current knowledge and accuracy levels to allow greater understanding and research to be performed in automating this process, which could lead to improved clinical outcomes.

Methods: A systematic literature review search was conducted for all studies that utilized machine learning and DBS in Parkinson's disease.

EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS.

The EEG of epileptic patients often contains sharp waveforms called "spikes", occurring between seizures. Detecting such spikes is crucial for diagnosing epilepsy. In this paper, we develop a convolutional neural network (CNN) for detecting spikes in EEG of epileptic patients in an automated fashion.