Paper Info
Title
Study On Brain Computer Interface Combined Tactile Enhancement And Time-Varying Features
Abstract
Neuroplasticity plays an important role in the recovery of injured nervous system. Both motor imagery (MI) and functional electrical stimulation (FES) can promote plasticity by activating the sensorimotor cortex. Specifically, MI as control strategy to activate FES in a brain computer interface (BCI) is a promising approach for motor functions recovery. This study demonstrated the efficiency of somatosensory input provided by electrical stimulation (ES) on cortical activation during MI. And the performance of classifiers with time-varying electroencephalography (EEG) features also be probed. We inspected the cortical activation by EEG for three experiment conditions, i.e. ES during MI, MI and ES. And the classification accuracy of three conditions were discussed respectively. Results showed that the ES during MI could induce stronger cortical activation than the other two conditions, and the classifier with time-varying EEG features had a higher classification accuracy. The results demonstrated that MI-based BCI combined MI and ES which fulfills two properties of somatosensory input and time-varying features is an available approach for motor neural rehabilitation.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8856609
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Computer vision,Functional electrical stimulation,Neuroscience,Computer science,Brain–computer interface,Nervous system,Somatosensory system,Artificial intelligence,Neuroplasticity,Electroencephalography,Stimulation,Motor imagery
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Lei Zhang1283.95
Long Chen203.04
Zhongpeng Wang302.70
Shuang Liu43622.95
Mengya Wang500.68
Shanguang Chen600.68
Dong Ming710551.47