Abstract
Though Motor Imagery (MI) stroke rehabilitation effectively promotes neural reorganization, current therapeutic methods are immeasurable and their repetitiveness can be demotivating. In this work, a real-time electroencephalogram (EEG) based MI-BCI (Brain Computer Interface) system with a virtual reality (VR) game as a motivational feedback has been developed for stroke rehabilitation. If the subject successfully hits one of the targets, it explodes and thus providing feedback on a successfully imagined and virtually executed movement of hands or feet. Novel classification algorithms with deep learning (DL) and convolutional neural network (CNN) architecture with a unique trial onset detection technique was used. Our classifiers performed better than the previous architectures on datasets from PhysioNet offline database. It provided fine classification in the real-time game setting using a 0.5 second 16 channel input for the CNN architectures. Ten participants reported the training to be interesting, fun and immersive. "It is a bit weird, because it feels like it would be my hands", was one of the comments from a test person. The VR system induced a slight discomfort and a moderate effort for MI activations was reported. We conclude that MI-BCI-VR systems with classifiers based on DL for real-time game applications should be considered for motivating MI stroke rehabilitation.
Original language | English |
---|---|
Title of host publication | Proceedings of the 10th Augmented Human International Conference 2019 |
Number of pages | 8 |
Publisher | Association for Computing Machinery |
Publication date | 2019 |
Article number | Article No. 22 |
ISBN (Print) | 978-1-4503-6547-5 |
DOIs | |
Publication status | Published - 2019 |
Event | 10th Augmented Human International Conference 2019 - University of Reims Champagne-Ardenne, Reims, France Duration: 11 Mar 2019 → 12 Mar 2019 Conference number: 10 |
Conference
Conference | 10th Augmented Human International Conference 2019 |
---|---|
Number | 10 |
Location | University of Reims Champagne-Ardenne |
Country/Territory | France |
City | Reims |
Period | 11/03/2019 → 12/03/2019 |
Keywords
- Motor Imagery
- Brain Computer Interface
- Deep learning
- CNN
- Virtual Reality
- Online EEG classification