Explainable Deep-Learning Prediction for Brain–Computer Interfaces Supported Lower Extremity Motor Gains Based on Multistate Fusion

Explainable Deep-Learning Prediction for Brain–Computer Interfaces Supported Lower Extremity Motor Gains Based on Multistate Fusion

Predicting the potential for recovery of motor function in stroke patients who undergo specific rehabilitation treatments is an important and major challenge. Recently, electroencephalography (EEG) has shown potential in helping to determine the relationship between cortical neural activity and moto...

Full description

Bibliographic Details
Main Authors: Ping-Ju Lin, Wei Li, Xiaoxue Zhai, Zhibin Li, Jingyao Sun, Quan Xu, Yu Pan, Linhong Ji, Chong Li
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Deep learning
multi-model fusion
explainable AI
electroencephalography
prognosis
Online Access:https://ieeexplore.ieee.org/document/10492982/

Internet

https://ieeexplore.ieee.org/document/10492982/

Similar Items