Evaluation of EEG features as indicators of physiological conditions
This paper aims to quantify physiological conditions based on two EEG features, composite permutation entropy index (CPEI) and sample entropy (SampEn), to identify healthy (unstressed) and stressed conditions. An experiment with 28 participants (17 healthy, 11 stressed) was designed. It was conduc...
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| Main Authors: | , , |
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| 格式: | Article |
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Springer
2012
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| 主題: | |
| 在線閱讀: | http://eprints.utp.edu.my/8441/1/Abstract-journal_V6.pdf http://www.springer.com/biomed/journal/13246 http://eprints.utp.edu.my/8441/ |
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| 機構: | Universiti Teknologi Petronas |
| 總結: | This paper aims to quantify physiological conditions based on two EEG features, composite permutation entropy index (CPEI) and sample entropy (SampEn), to identify healthy (unstressed) and stressed conditions.
An experiment with 28 participants (17 healthy, 11 stressed) was designed. It was conducted using visual stimulus in the 2D and 3D game environments, respectively. The dataset was recorded in eyes close (EC), eyes open (EO), and game playing in two dimension (2D), three dimension (3D) Active and Passive stages. It was then analysed using CPEI and SampEn.
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