運用單通道腦波儀實現情緒壓力判斷

一個情緒壓力判斷系統的建立，將有助於減緩現代人對於工作以及日常生活的壓力，進而減少壓力帶來的衝突、不安與誤會。本研究利用能夠誘發特定情緒的多媒體資訊，紀錄在不同多媒體的誘發情境下的各頻段腦波資訊。原始腦波訊號利用快速傅立葉轉換(Fast Fourier Transform, FFT)進行時頻轉換，依照各頻帶分出各腦波類型。由於每位受試者對於不同多媒體資訊，可能會因為個人的喜好、價值觀而有不同的效果，因此在紀錄完一個片段的腦波資訊後，讓受試者填寫SAM量表(Self-Assessment Manikin)，檢查此次測量的情緒。本實驗使用支持向量機(SVM)達到情緒判別的目的，對於測試影片達到86.4%的精確度，並且發現在使用的腦波特徵中，Highγ同時對正面情緒與負面情緒有最好的判別結果。

關鍵字

腦波；情緒辨認；支持向量機； AM量表

並列摘要

An emotional stress determination system is helpful for the modern people to reduce stress and avoid conflict, anxiety and misunderstanding. In this study, we used different multimedia to induce emotions and obtain EEG data. The raw EEG data was transformed into different EEG types by Fast Fourier Transform (FFT). However, the inducing emotion effect from subjects might be different because of the personal preferences, values and life experiences. Therefore Self-Assessment Manikin (SAM) is used as criterions for examining subjects’ emotion after induced emotion experiment. Experimental results shows that Support Vector Machine (SVM) achieves emotional determination with an average accuracy of 86.4%.The finding of this work is the high-gamma(γ) frequency feature from EEG power has the higher average accuracy rate of both positive emotion and negative emotion.

並列關鍵字

EEG ； emotion recognition ； support vector machine ； Self-Assessment Manikin

參考文獻

[1] J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, “Brain – computer interfaces for communication and control,” Clin. Nerophysiology, Vol. 113, pp. 767–791, 2002

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[2] 圖片取自於http://www.success001.cn/naoboyinyue/th.jpg

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[3] 李欣哲，腦波訊號評測生活美學認知-以室內設計風格為例，國立臺灣科技大學，2015

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[4] Boris Reuderink ,Valence, arousal and dominance in the EEG during game play, International journal of autonomous and adaptive communications systems, Vol.6, pp.45-62, 2013

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[5] 勝宏精密科技股份有限公司，來源http://www.brain-sh.tw/index.php

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運用單通道腦波儀實現情緒壓力判斷

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