Electro-Acupuncture Stimulation (EAS) Control by Imaginary Movement with Feedback Based on Electroencephalograph (EEG) Sensoring

Abstract

Electro-acupuncture stimulation (EAS) technique applies the electrical nerve stimulation therapy on traditional acupuncture points to restore the muscle tension. The rapid promotion and development of brain-computer interface (BCI) technology makes the thought-control of EAS possible. This paper designed a new BCI-control-EAS (BCICEAS) system by using event-related desynchronization (ERD) of EEG signal evoked by imaginary movement. The change of EEG signal was observed in the training and stimulation experiments with visual feedback. The Fisher parameters were extracted from feature frequency bands of EEG and classified into EAS control commands by Mahalanobis distance (MD) classifier. A feedback training technique was employed to correlate the enhancement of relevant EEG feature through a visual interface with a virtual liquid column, whose height varied along with EEG power spectral feature. According to the statistics analysis of 12 subjects, experimental results revealed the effective improvement of feedback training on signal feature and reliable control of EAS. It is expected that the proposed control method can explore a new way for EAS system design and help people who sufferers with severe movement dysfunction.

Keywords

• Electro-acupuncture stimulation
• Brain-computer interface
• Event-related desynchronization
• Imaginary movement
• Mahalanobis distance classifier.