應用腦電波之眼動訊號於疲勞狀態的識別

Identification of drowsiness by detecting eye movement based on mindwave EEG signal

陳竫昊(Ching-Hao Chen)

指導教授 ： 林志哲

國立臺北科技大學/機電學院/自動化科技研究所/碩士(2014年)

https://doi.org/10.6841/NTUT.2014.00137

摘要

本研究的目的是發展應用腦電波量測來分析受測者的眼動訊號，透過時域訊號的特徵來辨識眼動狀態，進而了解受測者的疲勞程度。本研究使用由神念科技(NeuroSky)所研發的非侵入式腦電波量測儀，進行腦電波原始資料的擷取，使用Matlab程式對於腦電波進行小波轉換(Wavelet transform, WT)將訊號分解，再將數據轉化為特徵值之後，使用支持向量機(Support vector machine, SVM)與倒傳遞類神經網路(Back propagation neural network, BPNN)進行辨識開閉眼的狀態；透過模糊邏輯，根據閉開眼頻率與閉眼時間來推論受測者之疲勞狀態，進而用於駕駛之警示。

關鍵字

腦電波圖 ； 小波轉換 ； 支持向量機 ； 類神經網路 ； 模糊邏輯

並列摘要

In this study, a drowsiness identification system using mindwave EEG signal is proposed. With the noninvasive mindwave headset developed by NeuroSky, the time domain signal of the mindwave is used to recognize eye movement and the user's fatigue level. First, the EEG raw signal is transformed by the wavelet transformation. Second, the eigenvalues are computed based on the Daubechies wavelet. Third, the support vector machine and the back propagation neural network are studied to identify the status of eye movement using the eigenvalues. Finally, the fuzzy logic is used to obtain the fatigue level, according to the frequency of the eye movement and the time of closing eyes.

並列關鍵字

Electroencephalogram ； Wavelet transform ； Support vector machine ； Back propagation neural network ； Fuzzy logic

參考文獻

[6] 林怡秀，調適性網路模糊推論於水下聲源訊號辨識系統之研究，碩士論文，私立中原大學資訊工程學系，桃園，2001。

[1] G.D Schott, " Penfield's homunculus: a note on cerebral cartography," Journal of Neurology, Neurosurgery and Psychiatry, 56, 1993, pp. 329-333.

[2] 洪偉哲，以小波轉換鑑別人類情緒腦波，碩士論文，國立臺灣師範大學機電科技學系，臺北，2011。

[5] James W. Cooley and John W. Tukey, " An algorithm for the machine calculation of complex Fourier series," Mathematics of Computation, vol. 19, no. 90, 1965, pp. 297-301.

[9] I. Daubechies, " Orthonormal bases of compactly supported wavelets," Communications on Pure and Applied Mathematics, vol. 41, 1988, pp. 909-996.