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Mervyn V.M. Yeo, Xiaoping Li , Kaiquan Shen , Einar P.V. Wilder-Smith
M.V.M. Yeo et al. / Safety Science 47 (2009) 115–124
Presented by：Bo-Yang Hou
Adviser：Shih-Chung Chen
Chairman：Hung-Chi Yang
Date：2012/12/19
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The objective of this study is to establish an
automatic method of distinguishing between
alert and drowsy states by using a recently
established signal pattern recognition
technology to develop a reliable detection
system of drowsiness for driving safety.
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引用於：支持向量機教學文件(中文版) 李根逸 台灣大學通訊與多媒體實驗室
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1. Support Vector Machines (SVM)

To understand the essence of SVM classification,
one needs only to grasp four basic concepts:
(I) The separating hyperplane
(II) The maximum-margin hyperplane
(III) The soft margin
(IV) The kernel function
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2. Participants

The recruitment of human subjects for this study
was approved by the National University of
Singapore (NUS) ethical committee.

The Epworth Sleepiness Scale was used to
prescreen and determine the level of daytime
sleepiness.
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3. EEG equipment and data collection
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The EEG equipment used was a 32-channel
Medtronic PL-Winsor 2.35 system, with a
sampling frequency of 256 Hz, an integrated
low pass (cut-off frequency of 35 Hz) and a time
constant of 0.30 s.

Full head mapping was done using the standard
10/20 system of electrode placement (Jasper,
1958).
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The SVM program was also able to predict the
transition from alertness to drowsiness reliably
in over 90% of data samples.
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This study shows that automatic analysis and
detection of drowsiness EEG is possible by
SVM and SVM is a good candidate for
developing pre-emptive automatic drowsiness
detection systems for driving safety.
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[1] Mervyn V.M. Yeo, Xiaoping Li , Kaiquan Shen , Einar P.V. WilderSmith , Can SVM be used for automatic EEG detection of drowsiness
during car driving? , M.V.M. Yeo et al. / Safety Science 47 (2009)
115–124
[2] William S Noble , What is a support vector machine? , NATURE
BIOTECHNOLOGY VOLUME 24 NUMBER 12 DECEMBER 2006
1565-1567
[3] Kristin P.Bennett & Colin Campbell ,Support Vector Machines:
Hype or hallelujh? ,SIGKDD Explorations.Copyright ©2000ACM
SIGKDD ,December2000 ,Volune 2 ,Issue – page13
[4]支持向量機教學文件(中文版) 李根逸 台灣大學通訊與多
媒體實驗室
[5] 勞工安全衛生研究所 ,認識睡眠呼吸中止症 ,
http://www.iosh.gov.tw/Print.aspx?cnid=12&P=528
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