Human stress level computation using multiple physiological signals-based on fusion technique through dynamic bayesian network /
This study investigates to improve the stress levels computation and its reliability using multiple physiological signals. In which, stress inducement, physiological signal acquisition, preprocessing, feature extraction, classification, optimization of features from multiple physiological signals, s...
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| Main Author: | |
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| Format: | Thesis Software eBook |
| Language: | English |
| Published: |
Perlis, Malaysia
School of Mechatronic Engineering, University Malaysia Perlis
2014
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| Subjects: | |
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| Summary: | This study investigates to improve the stress levels computation and its reliability using multiple physiological signals. In which, stress inducement, physiological signal acquisition, preprocessing, feature extraction, classification, optimization of features from multiple physiological signals, significant feature estimation, decision boundary optimization, and fusion are the major process. |
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| Physical Description: | 1 computer disc illustrations 12 cm |
| Bibliography: | Includes bibliographical references. |