In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code, and the VEPs were recognized and classified using subject-specific algorithms. The system provided the ability of controlling a wheelchair model (LEGO R MINDSTORM R EV3 robot) in 4 different directions based on the elicited c-VEPs. Ten healthy subjects were evaluated in testing the system where an average accuracy of 97% was achieved. The promising results illustrate the potential of this approach when considering a real wheelchair application.
|Title of host publication||Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Publication status||Published - 2015|
|Event||37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Milano, Italy|
Duration: 25 Aug 2015 → 29 Aug 2015
Conference number: 37
|Conference||37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Period||25/08/2015 → 29/08/2015|