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.
Highlights
AND BACKGROUNDElectrocorticogram (ECoG) has been increasingly used as a signal acquisition modality for brain-computer interface (BCI) applications
This study examines the representation of six elementary finger, hand, and arm movements in ECoG signals, and whether these movements can be distinguished from one another
Subject S1, a 20-year-old female, was implanted with an 8×8 grid located on the left anterior frontal temporal area and a 1×6 posterior frontal strip
Summary
Electrocorticogram (ECoG) has been increasingly used as a signal acquisition modality for brain-computer interface (BCI) applications. Unlike action and local field potentials that rely on intracortical implantation of microelectrodes, ECoG can be acquired using less invasive surgical procedures. This signal acquisition modality may have better long-term stability properties. The majority of ECoG-based BCI studies have focused on decoding the kinematic parameters of upper extremity movements. Examples include decoding and resolving the movement of individual fingers [1], [2], [3], the onset and direction of reaching movements [4], [5], as well as elbow and hand movements [5], [6]. While reaching, grasping and finger movements are important components of most goal-oriented upper extremity tasks, these movements alone are insufficient to regain the upper extremity functions
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