Method for determining fatigue state according to electroencephalogram

Abstract

The invention provides a method for determining fatigue state according to electroencephalogram (EEG) which adopts a plurality of electroencephalographs and connecting electrodes for realizing the real time acquisition of electroencephalogram. The method comprises the following steps: running interface programs of a PC and the electroencephalographs; realizing the synchronous acquisition of data by using a VC++ to compile visual interface program of the electroencephalographs under the Windows platform, and displaying EEG waveforms acquired in real-time; pre-processing the acquired data; carrying out the low-pass filtering at 0Hz to 30Hz to the data by an FIR (Finite Impulse Response) filter, so as to eliminate the power frequency noise and external interference; decomposing the filtered EEG waveforms by the blind-source separation method, so as to acquire each component of the mixed signal comprising electro-oculogram (EOG) and left and right brain EEGs; carrying out the fast Fourier transform (FFT) on the left and right brain EEGs, and converting the time-domain signals to the frequency-domain signals; working out the energy of alpha, beta, theta and delta waves in the EEGs and classifying the BP (back propagation) neural network of the multi-layer perceptron. The invention has the characteristics of directness and rapidness.

Description

technical field [0001] The present invention relates to a method for extracting energy of brain wave α, β, θ, δ components in a brain-computer interface (brain-computer interface, BCI) device, in particular to a feature extraction and classification of an independent component analysis method combined with a BP neural network method. Background technique [0002] A brain-computer interface (BCI) is a direct connection pathway established between a human or animal brain (or a culture of brain cells) and an external device. In the case of a one-way BCI, the computer either accepts commands from the brain or sends signals to the brain (such as video reconstruction), but cannot send and receive signals at the same time. The two-way brain-computer interface allows two-way information exchange between the brain and external devices. [0003] Brain-computer interface is divided into invasive brain-computer interface, partially invasive brain-computer interface and non-invasive br...

AI Technical Summary

Problems solved by technology

[0008] (2) Strong non-stationarity and randomness

[0009] (3) Nonlinear

[0019] Therefore, it is urgent to develop a method for judging the fatigue state based on the EEG signal, so as to change the existing methods of judging the fatigue state, such as triggering immune response and callus, low resolution of the recorded signal, unstable signal and The problem of poor anti-interference ability makes it have the characteristics of direct, stable and fast

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