论文部分内容阅读
A brain-computer interface(BCI)-based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control system makes use of the amplitude enhancement of alpha-wave blocking in electroencephalogram(EEG) when eyes close for more than 1 s to constitute a BCI for the switch control of wheelchair movements. The system was formed by BCI control panel, data acquisition, signal processing unit and interface control circuit. Eight volunteers participated in the wheelchair control experiments according to the preset routes. The experimental results show that the mean success control rate of all the subjects was 81.3%, with the highest reaching 93.7%. When one subject’s triggering time was 2.8 s, i.e., the flashing time of each cycle light was 2.8 s, the average information transfer rate was 8.10 bit/min, with the highest reaching 12.54 bit/min.
A brain-computer interface (BCI) -based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control system makes use of the amplitude enhancement of alpha-wave blocking in electroencephalogram (EEG) when eyes close for more than 1 s to constitute a BCI for the switch control of wheelchair movements. The system was formed by BCI control panel, data acquisition, signal processing unit and interface control circuit. Eight volunteers participated in the wheelchair control experiments according to the preset routes. The experimental results show the mean success control rate of all the subjects was 81.3%, with the highest reaching 93.7%. When one subject’s triggering time was 2.8 s, ie, the flashing time of each cycle light was 2.8 s, the average information transfer rate was 8.10 bit / min, with the highest reaching 12.54 bit / min.