A brain-computer interface for motor assist by the prefrontal cortex

Considerable research has been conducted on the development of brain-computer interfaces (BCIs). Although there have been several reports on BCIs that assist motor functions by measurement of brain activity in the motor cortex, only a few studies have discussed BCIs that assist motor functions by measurement of activity in areas other than the motor cortex. In this study, we experimentally develop a BCI that assists motor functions on the basis of brain activity in the prefrontal cortex. In this BCI system, subjects are presented with the labyrinth problem. Concretely, brain activity is measured using fNIRS and the data are acquired in real time. The signal processing module implements low-pass filtering of these signals. Further, the pattern classification module used in this system currently is a support vector machine. Twenty-two subjects, both male and female, volunteered to participate in this experiment. Eight of these twenty-two subjects were able to solve the labyrinth problem. In this experiment, we could not obtain a high distinction. However, these results show that it is possible to develop BCI systems that assist motor functions using information from the prefrontal cortex.