Modeling observer stress for typical real environments
作者：
Highlights：
• Proposed a computational model system for observer stress for real-life events.
• System input includes a novel set of multi-sensor physiological & physical signals.
• System is based on a support vector machine and a genetic algorithm.
• Real-world stress data was acquired for interview and meditation settings.
• Signals captured for the stress model were EEG, skin conductivity, thermal videos.
摘要
•Proposed a computational model system for observer stress for real-life events.•System input includes a novel set of multi-sensor physiological & physical signals.•System is based on a support vector machine and a genetic algorithm.•Real-world stress data was acquired for interview and meditation settings.•Signals captured for the stress model were EEG, skin conductivity, thermal videos.
论文关键词：Stress classification,Physiological signals,Physical signals,Support vector machine,Genetic algorithm,Real environments
论文评审过程：Available online 25 September 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.09.021
