title: Simulation of a Real-Time Brain Computer Interface for Detecting a Self-Paced Hitting Task.
abstract: OBJECTIVE
  An invasive brain-computer interface (BCI) is a promising neurorehabilitation device for severely disabled patients. Although some systems have been shown to work well in restricted laboratory settings, their utility must be tested in less controlled, real-time environments. Our objective was to investigate whether a specific motor task could be reliably detected from multiunit intracortical signals from freely moving animals in a simulated, real-time setting.
  
  
  METHODS
  Intracortical signals were first obtained from electrodes placed in the primary motor cortex of four rats that were trained to hit a retractable paddle (defined as a "Hit"). In the simulated real-time setting, the signal-to-noise-ratio was first increased by wavelet denoising. Action potentials were detected, and features were extracted (spike count, mean absolute values, entropy, and combination of these features) within pre-defined time windows (200 ms, 300 ms, and 400 ms) to classify the occurrence of a "Hit."
  
  
  RESULTS
  We found higher detection accuracy of a "Hit" (73.1%, 73.4%, and 67.9% for the three window sizes, respectively) when the decision was made based on a combination of features rather than on a single feature. However, the duration of the window length was not statistically significant (p = 0.5).
  
  
  CONCLUSIONS
  Our results showed the feasibility of detecting a motor task in real time in a less restricted environment compared to environments commonly applied within invasive BCI research, and they showed the feasibility of using information extracted from multiunit recordings, thereby avoiding the time-consuming and complex task of extracting and sorting single units.
authors: Department of Health Science and Technology, Center for Sensory-Motor Interaction, Aalborg University, Aalborg, Denmark.
authors: Sofyan H
authors: SH
authors: Hammad
authors: Department of Health Science and Technology, Center for Sensory-Motor Interaction, Aalborg University, Aalborg, Denmark.
authors: Ernest N
authors: EN
authors: Kamavuako
authors: Department of Health Science and Technology, Center for Sensory-Motor Interaction, Aalborg University, Aalborg, Denmark.|Department of Neurorehabilitation Engineering, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany.
authors: Dario
authors: D
authors: Farina
authors: Department of Health Science and Technology, Center for Sensory-Motor Interaction, Aalborg University, Aalborg, Denmark.
authors: Winnie
authors: W
authors: Jensen
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D062207:Brain-Computer Interfaces; D003198:Computer Simulation; D004569:Electroencephalography; D008297:Male; D009044:Motor Cortex / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D015999:Multivariate Analysis; D051381:Rats; D017207:Rats, Sprague-Dawley; D000068356:Self-Control; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted
keywords: Invasive brain-computer interface; classification feature; multi-unit; wavelet de-noising