Pattern recognition of motor imagery EEG signal in noninvasive brain-computer interface

Brain-Computer Interface (BCI) enables people to communicate with the external objects directly only by using electroencephalography (EEG) rather than other central nerves, peripheral nerves or effectors in brain normal pathway. Spontaneous and noninvasive, Brain-Computer Interface based on motor imagery EEG signal can be applied more widely. This paper focuses on pattern recognition of EEG signal in Brain-Computer Interface based on the left-right hand motor imagery. Mental task among 5 subjects was processed to acquire motor imagery EEG signal. In order to improve the signal-to-noise ratio (SNR) of EEG, filters in time domain, frequency domain and special domain are applied in signal preprocess. Additionally, power spectral density (PSD) was extracted with sliding windows from processed signal as features for pattern recognition. Then the discriminate labels of motor imagery are trained by linear discriminate analysis (LDA) and random forest algorithm to decode the imagine pattern. The results show an average recognition accuracy of 0.65 ± 0.07 for LDA and 0.70 ± 0.05 for random forest can be obtained, which has significant difference with random level. From the results, it can be concluded that pattern of motor imagery can be decoded. In addition, a signal trial online pattern recognition task can be further implement to achieve human-computer interaction based on EEG signals.

I. Introduction

In science fiction movies, we can see characters controlling the external articles through minds directly, with special equipments on the body which can decode their intentions. Faster and more flexibility, the new communicating methods that only rely on brain instead of other body organs are expected. With the development of science and technology, Brain-Computer Interface has made a considerable progress for the realization of the new communicating methods. Brain-Computer Interface (BCI) provides a new way for humans to communicate with the external world using electroencephalography (EEG) but not other nerves in the normal neural pathway [1]. Electroencephalography is a kind of potential signal generated by the cerebral cortex, which records the electrical activities of human brain. The current mainstream view stands on the point that EEG is mainly produced by the potential superposition of pyramidal neurons in the cerebral cortex of the cerebral cortex.