A high-performance brain–computer interface for finger decoding and quadcopter game control in an individual with paralysis

This research focuses on creating a brain-computer interface (BCI) that allows a person with paralysis to control individual finger movements. This is achieved by decoding brain activity related to intended finger motions. The decoded finger movements are then used to control a virtual hand on a computer screen, enabling the participant to perform tasks requiring dexterity. The ultimate goal was to use this finger-based BCI to control a virtual quadcopter, providing the participant with a sense of enablement, recreation, and social connectedness.

• 1
  The developed BCI system allowed continuous control of three independent finger groups, with the thumb having two degrees of freedom, resulting in a total of four degrees of freedom.
• 2
  The participant achieved an average acquisition rate of 76 targets per minute in sequential finger tasks, with completion times of 1.58 ± 0.06 seconds.
• 3
  The finger positions were successfully mapped to control a virtual quadcopter, allowing the participant to navigate obstacle courses and fly through randomly appearing rings.