Effect of subject training on a movement-related cortical potential-based brain-computer interface

Mads Jochumsen, Imran Khan Niazi, Rasmus Wiberg Nedergaard, Muhammad Samran Navid, Kim Dremstrup

Research output: Contribution to journalJournal articleResearchpeer-review

8 Citations (Scopus)


Brain-computer interfaces (BCIs) have been developed for several purposes in communication, control, and rehabilitation. To use the BCI efficiently, the system must be technically tuned, and the user must learn to operate it. In this study, we investigated if the user could be trained to improve the performance of online detection of movement-related cortical potentials (MRCPs) associated with fast and slow movements. Seven healthy subjects participated in nine experiments over eight weeks while the ability of the online system to detect the movements was accessed. The movements were detected using template matching. No training effect was observed on the performance or MRCP morphology over the eight weeks. The system correctly detected ∼80% of the movements with ∼1.5 false positive detections/min. The findings suggest that the detection of MRCPs is stable from the first session and that several training sessions are not needed to obtain control of the BCI; this may have implication for the applicability of BCIs for movement detection.

Original languageEnglish
JournalBiomedical Signal Processing and Control
Pages (from-to)63-68
Number of pages6
Publication statusPublished - 2018


  • Brain-computer interface
  • Movement intention
  • Movement kinetics
  • Movement-related cortical potential
  • Training


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