title: Continuous decoding of grasping tasks for a prospective implantable cortical neuroprosthesis.
abstract: BACKGROUND
  In the recent past several invasive cortical neuroprostheses have been developed. Signals recorded from the motor cortex (area MI) have been decoded and used to control computer cursors and robotic devices. Nevertheless, few attempts have been carried out to predict different grips.A Support Vector Machines (SVMs) classifier has been trained for a continuous decoding of four/six grip types using signals recorded in two monkeys from motor neurons of the ventral premotor cortex (area F5) during a reach-to-grasp task.
  
  
  RESULTS
  The results showed that four/six grip types could be extracted with classification accuracy higher than 96% using window width of 75-150 ms.
  
  
  CONCLUSIONS
  These results open new and promising possibilities for the development of invasive cortical neural prostheses for the control of reaching and grasping.
authors.affiliation: Neural Engineering Area, The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy. j.carpaneto@sssup.it
authors.forename: Jacopo
authors.initials: J
authors.lastname: Carpaneto
authors.forename: Vassilis
authors.initials: V
authors.lastname: Raos
authors.forename: Maria A
authors.initials: MA
authors.lastname: Umiltà
authors.forename: Leonardo
authors.initials: L
authors.lastname: Fogassi
authors.forename: Akira
authors.initials: A
authors.lastname: Murata
authors.forename: Vittorio
authors.initials: V
authors.lastname: Gallese
authors.forename: Silvestro
authors.initials: S
authors.lastname: Micera
mesh_terms: D000465:Algorithms; D000818:Animals; D001132:Arm / Q000502:physiology; D002540:Cerebral Cortex / Q000502:physiology*; D018737:Hand Strength / Q000502:physiology*; D008254:Macaca nemestrina; D009044:Motor Cortex / Q000502:physiology; D009068:Movement; D058117:Neural Prostheses; D009474:Neurons / Q000502:physiology; D010363:Pattern Recognition, Automated; D011474:Prosthesis Design; D011597:Psychomotor Performance; D060388:Support Vector Machine