학술논문
A Multi-feature Fuzzy Index to Assess Stress Level from Bio-signals
Document Type
Conference
Author
Source
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) IEEE Engineering in Medicine and Biology Society (EMBC), 2018 40th Annual International Conference of the. :1086-1089 Jul, 2018
Subject
Language
ISSN
1558-4615
Abstract
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.