Title
Sensitivity and specificity of upper extremity movements decoded from electrocorticogram.
Abstract
Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially be used for control of arm prostheses. Restoring independent function to BCI users with such a system will likely require control of many degrees-of-freedom (DOF). However, our ability to decode many-DOF arm movements from ECoG signals has not been thoroughly tested. To this end, we conducted a comprehensive study of the ECoG signals underlying 6 elementary upper extremity movements. Two subjects undergoing ECoG electrode grid implantation for epilepsy surgery evaluation participated in the study. For each task, their data were analyzed to design a decoding model to classify ECoG as idling or movement. The decoding models were found to be highly sensitive in detecting movement, but not specific in distinguishing between different movement types. Since sensitivity and specificity must be traded-off, these results imply that conventional ECoG grids may not provide sufficient resolution for decoding many-DOF upper extremity movements.
Year
DOI
Venue
2013
10.1109/EMBC.2013.6610824
EMBC
Keywords
Field
DocType
biomechanics,bci,biomedical electrodes,artificial limbs,electroencephalography,brain-computer interfaces,epilepsy surgery evaluation,upper extremity movement sensitivity,arm prostheses,ecog-based brain computer interfaces,upper extremity movement specificity,electrocorticogram,ecog electrode grid implantation,surgery,many-dof arm movements,feature extraction,brain computer interfaces,sensitivity,decoding,electrodes,data models
Biomedical engineering,Computer vision,Epilepsy surgery,Computer science,Artificial limbs,Brain–computer interface,Electrode Grid,Artificial intelligence,Biomechanics,Decoding methods,Physical medicine and rehabilitation,Electroencephalography
Conference
Volume
ISSN
Citations 
2013
1557-170X
1
PageRank 
References 
Authors
0.63
4
13