A review on stress inducement stimuli for assessing human stress using physiological signals

P. Karthikeyan, M. Murugappan, S. Yaacob
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引用次数: 75

Abstract

Assessing human stress in real-time is more difficult and challenging today. The present review deals about the measurement of stress in laboratory environment using different stress inducement stimuli by the help of physiological signals. Previous researchers have been used different stress inducement stimuli such as stroop colour word test (CWT), mental arithmetic test, public speaking task, cold pressor test, computer games and works used to induce the stress. Most of the researchers have been analyzed stress using questionnaire based approach and physiological signals. The several physiological signals like Electrocardiogram (ECG), Electromyogram (EMG), Galvanic Skin Response (GSR), Blood Pressure (BP), Skin Temperature (ST), Blood Volume Pulse (BVP), respiration rate (RIP) and Electroencephalogram (EEG) were briefly investigated to identify the stress. Different statistical methods like Analysis of variance (ANOVA), two-way ANOVA, Multivariate analysis of variance (MANOVA), t-test, paired t-tests and student t-tests have used to describe the correlation between stress inducement stimuli, subjective parameters (age, gender and etc.,) and physiological signals. This present works aims to find the most appropriate stress inducement stimuli, physiological signals and statistical method to efficiently asses the human stress.
利用生理信号评价人体应激的应激诱导刺激研究进展
在今天,实时评估人类的压力更加困难和具有挑战性。本文综述了利用不同的应激诱导刺激,借助生理信号在实验室环境中测量应激的方法。以往的研究已经使用了不同的压力诱导刺激,如彩色单词测试(CWT)、心算测试、公共演讲任务、冷压力测试、电脑游戏和作品来诱导压力。研究人员大多采用问卷调查法和生理信号法对压力进行分析。通过观察心电图(ECG)、肌电图(EMG)、皮肤电反应(GSR)、血压(BP)、皮肤温度(ST)、血容量脉冲(BVP)、呼吸速率(RIP)和脑电图(EEG)等生理信号来识别应激。不同的统计方法,如方差分析(ANOVA)、双向方差分析(ANOVA)、多元方差分析(MANOVA)、t检验、配对t检验和学生t检验,被用来描述应激诱发刺激、主观参数(年龄、性别等)和生理信号之间的相关性。本研究旨在寻找最合适的应激诱导刺激、生理信号和统计方法来有效地评估人体应激。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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