| Literature DB >> 33414824 |
Yangyang Miao1, Shugeng Chen2, Xinru Zhang1, Jing Jin1, Ren Xu3, Ian Daly4, Jie Jia2, Xingyu Wang1, Andrzej Cichocki5,6,7, Tzyy-Ping Jung8.
Abstract
Background: Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and entered into the sequela stage of chronic stroke. Method: Studies have shown that motor imagery- (MI-) based brain-computer interface (BCI) has a positive effect on poststroke rehabilitation. This study used both virtual limbs and functional electrical stimulation (FES) as feedback to provide patients with a closed-loop sensorimotor integration for motor rehabilitation. An MI-based BCI system acquired, analyzed, and classified motor attempts from electroencephalogram (EEG) signals. The FES system would be activated if the BCI detected that the user was imagining wrist dorsiflexion on the instructed side of the body. Sixteen stroke patients in the sequela stage were randomly assigned to a BCI group and a control group. All of them participated in rehabilitation training for four weeks and were assessed by the Fugl-Meyer Assessment (FMA) of motor function.Entities:
Year: 2020 PMID: 33414824 PMCID: PMC7752268 DOI: 10.1155/2020/8882764
Source DB: PubMed Journal: Neural Plast ISSN: 1687-5443 Impact factor: 3.599