Electroencephalogram Features Reflect Effort Corresponding to Graded Finger Extension: Implications for Hemiparetic Stroke.

Brain-computer interfaces (BCIs) offer disabled individuals the means to interact with devices by decoding the electroencephalogram (EEG). However, decoding intent in fine motor tasks can be challenging, especially in stroke survivors with cortical lesions. Here, we attempt to decode graded finger extension from the EEG in stroke patients with left-hand paresis and healthy controls.

Reconnecting the Hand and Arm to the Brain: Efficacy of Neural Interfaces for Sensorimotor Restoration After Tetraplegia.

Background And Objectives: Paralysis after spinal cord injury involves damage to pathways that connect neurons in the brain to peripheral nerves in the limbs. Re-establishing this communication using neural interfaces has the potential to bridge the gap and restore upper extremity function to people with high tetraplegia. We report a novel approach for restoring upper extremity function using selective peripheral nerve stimulation controlled by intracortical microelectrode recordings from sensorimotor networks, along with restoration of tactile sensation of the hand using intracortical microstimulation.

Prediction of isometric handgrip force from graded event-related desynchronization of the sensorimotor rhythm.

. Brain-computer interfaces (BCIs) show promise as a direct line of communication between the brain and the outside world that could benefit those with impaired motor function. But the commands available for BCI operation are often limited by the ability of the decoder to differentiate between the many distinct motor or cognitive tasks that can be visualized or attempted.

Noninvasive seizure prediction using autonomic measurements in patients with refractory epilepsy.

There is resurgent interest in the role played by autonomic dysfunction in seizure generation. Advances in wearable sensors make it convenient to track many autonomic variables in patient populations. This study assesses peri-ictal changes in surrogate measures of autonomic activity for their predictive value in epilepsy patients.

Upper extremity movement reliability and validity of the Kinect version 2.

Purpose: Studies have shown that marker-less motion detection systems, such as the first generation Kinect (Kinect 1), have good reliability and potential for clinical application. Studies of the second generation Kinect (Kinect 2) have shown a large range of accuracy relative to balance and joint localization; however, few studies have investigated the validity and reliability of the Kinect 2 for upper extremity motion. This investigation compared reliability and validity among the Kinect 1, Kinect 2 and a video motion capture (VMC) system for upper extremity movements.