Design and implementation of a cascaded adaptive neuro-fuzzy inference system for cognitive and emotional stress level assessment based on electroencephalograms and self-reports
Stress has been considered as one of the culprit in many diseases and other physical disorders. There are several methods on how to determine stress levels which are usually conducted by an experienced clinician. However, computer aided detection systems could be more objective and consistent in del...
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| Main Authors: | , |
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| Format: | text |
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Animo Repository
2014
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1383 |
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| Institution: | De La Salle University |
| Summary: | Stress has been considered as one of the culprit in many diseases and other physical disorders. There are several methods on how to determine stress levels which are usually conducted by an experienced clinician. However, computer aided detection systems could be more objective and consistent in delivering results as basis of diagnosis and suggestions for relieving stress. In this paper, a cascaded adaptive neuro-fuzzy inference system (ANFIS) was proposed to assess the stress level in the cognitive and emotional aspect of an individual using EEG and self-reports. The two-stage ANFIS was able to predict the level of confusion, difficulty and frustration of the respondents with the task given to them. Using these factors, the system was also able to predict the level of stress that they had. Results show close proximity to the expected levels as described by the respondents through a system evaluation using the root mean square error and a parametric statistical test for significant difference. |
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