Setz Cornelia, Arnrich Bert, Schumm Johannes, La Marca Roberto, Tröster Gerhard, Ehlert Ulrike
Wearable Computing Laboratory, Swiss Federal Institute of Technology Zurich, 8092 Zurich, Switzerland.
IEEE Trans Inf Technol Biomed. 2010 Mar;14(2):410-7. doi: 10.1109/TITB.2009.2036164. Epub 2009 Nov 10.
The inferred cost of work-related stress call for prevention strategies that aim at detecting early warning signs at the workplace. This paper goes one step towards the goal of developing a personal health system for detecting stress. We analyze the discriminative power of electrodermal activity (EDA) in distinguishing stress from cognitive load in an office environment. A collective of 33 subjects underwent a laboratory intervention that included mild cognitive load and two stress factors, which are relevant at the workplace: mental stress induced by solving arithmetic problems under time pressure and psychosocial stress induced by social-evaluative threat. During the experiments, a wearable device was used to monitor the EDA as a measure of the individual stress reaction. Analysis of the data showed that the distributions of the EDA peak height and the instantaneous peak rate carry information about the stress level of a person. Six classifiers were investigated regarding their ability to discriminate cognitive load from stress. A maximum accuracy of 82.8% was achieved for discriminating stress from cognitive load. This would allow keeping track of stressful phases during a working day by using a wearable EDA device.
工作相关压力的推断成本需要预防策略，这些策略旨在在工作场所检测早期预警信号。本文朝着开发用于检测压力的个人健康系统这一目标迈进了一步。我们分析了在办公环境中，皮肤电活动（EDA）在区分压力和认知负荷方面的辨别能力。33名受试者参与了一项实验室干预，其中包括轻度认知负荷和两个与工作场所相关的压力因素：在时间压力下解决算术问题所引发的精神压力，以及社会评价威胁所引发的心理社会压力。在实验过程中，使用了可穿戴设备来监测EDA，以此作为个体压力反应的一种度量。数据分析表明，EDA峰值高度和瞬时峰值率的分布携带了有关一个人压力水平的信息。研究了六种分类器区分认知负荷和压力的能力。在区分压力和认知负荷方面，最高准确率达到了82.8%。这将使得通过使用可穿戴EDA设备来追踪工作日中的压力阶段成为可能。
