Grasp detection from human ECoG during natural reach-to-grasp movements

PLoS One. 2013;8(1):e54658. doi: 10.1371/journal.pone.0054658. Epub 2013 Jan 24.


Various movement parameters of grasping movements, like velocity or type of the grasp, have been successfully decoded from neural activity. However, the question of movement event detection from brain activity, that is, decoding the time at which an event occurred (e.g. movement onset), has been addressed less often. Yet, this may be a topic of key importance, as a brain-machine interface (BMI) that controls a grasping prosthesis could be realized by detecting the time of grasp, together with an optional decoding of which type of grasp to apply. We, therefore, studied the detection of time of grasps from human ECoG recordings during a sequence of natural and continuous reach-to-grasp movements. Using signals recorded from the motor cortex, a detector based on regularized linear discriminant analysis was able to retrieve the time-point of grasp with high reliability and only few false detections. Best performance was achieved using a combination of signal components from time and frequency domains. Sensitivity, measured by the amount of correct detections, and specificity, represented by the amount of false detections, depended strongly on the imposed restrictions on temporal precision of detection and on the delay between event detection and the time the event occurred. Including neural data from after the event into the decoding analysis, slightly increased accuracy, however, reasonable performance could also be obtained when grasping events were detected 125 ms in advance. In summary, our results provide a good basis for using detection of grasping movements from ECoG to control a grasping prosthesis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Algorithms
  • Cerebral Cortex / physiology
  • Discriminant Analysis
  • Electroencephalography
  • Hand Strength*
  • Humans
  • Movement*
  • Reproducibility of Results

Grant support

This work was funded by the German Federal Ministry of Education and Research: BMBF grant 01GQ0420 to BCCN Freiburg and GoBio grant 0313891. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.