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Communication Dans Un Congrès Année : 2018

A Multi-feature Fuzzy Index to Assess Stress Level from Bio-signals

Résumé

A mono-feature fuzzy index that evaluates the stress level from one feature extracted from ECG or GSR is presented. It is build using several measures of the feature recorded when the subject is at rest. The mono-feature fuzzy index can be merged in a multi-feature stress index without any tuning. It can be used to select relevant features and to detect stress. The performance of the stress index is analyzed on a data set made of 160 time periods of time when 20 subjects had to perform stressful tasks and corresponding control tasks. The stress was induced by 4 different tasks. The performances reached are 72% of correctly classified time periods in stress and no stress situations. Interesting conclusions could also be made on the tasks ability to induce stress.
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Dates et versions

hal-01977567 , version 1 (10-01-2019)

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Citer

Sylvie Charbonnier, Gael Vila, Christelle Godin, Etienne Labyt, Oumayma Sakri, et al.. A Multi-feature Fuzzy Index to Assess Stress Level from Bio-signals. EMBC 2018 - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Jul 2018, Honolulu, Hawaii, United States. ⟨10.1109/EMBC.2018.8512499⟩. ⟨hal-01977567⟩
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