Extracting attempted hand movements from eegs in people with complete hand paralysis following stroke

Abirami Muralidharan, John Chae, Dawn M. Taylor

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


This study examines the feasibility of using electroencephalograms (EEGs) to rapidly detect the intent to open one's hand in individuals with complete hand paralysis following a subcortical ischemic stroke. If detectable, this motor-planning activity could be used in real time to trigger a motorized hand exoskeleton or an electrical stimulation device that opens/closes the hand. While EEG-triggered movement-assist devices could restore function, they may also promote recovery by reinforcing the use of remaining cortical circuits. EEGs were recorded while participants were cued to either relax or attempt to extend their fingers. Linear-discriminant analysis was used to detect onset of finger-extension from the EEGs in a leave-one-trial-out cross-validation process. In each testing trial, the classifier was applied in pseudo-real-time starting from an initial hand-relaxed phase, through movement planning, and into the initial attempted-finger-extension phase (finger-extension phase estimated from typical time-to-movement-onset measured in the unaffected hand). The classifiers detected attempted-finger-extension at a significantly higher rate during both motor-planning and early attempted execution compared to rest. To reduce inappropriate triggering of a movement-assist device during rest, the classification threshold could be adjusted to require more certainty about one's intent to move before triggering a device. Additionally, a device could be set to activate only after multiple time samples in a row were classified as finger-extension events. These options resulted in some sessions with no false triggers while the person was resting, but moderate-to-high true trigger rates during attempted-movements.

Original languageEnglish (US)
Article number39
JournalFrontiers in Neuroscience
Issue numberMAR
StatePublished - 2011
Externally publishedYes


  • Brain-computer interface
  • Brain-machine interface
  • Decoding
  • Electroencephalograph
  • Hand paresis
  • Hebbian plasticity
  • Linear-discriminant analysis
  • Stroke


Dive into the research topics of 'Extracting attempted hand movements from eegs in people with complete hand paralysis following stroke'. Together they form a unique fingerprint.

Cite this