ABSTRACT

HCI researchers and practitioners are increasingly using physiological data to measure User eXperience (UX) parameters. The dynamic nature of physiological data offers a continuous window for an in-depth understanding of users’ interaction experience. However, in order to be truly informative, physiological signals need to be linked to users’ interaction experience aspects, such as their emotional states, in a systematic and efficient way. Studies have shown that skin conductance is a physiological signal highly associated with stress. The main purpose of this paper is to present the validation study of our proposed stress detection mechanism which is integrated into a software named PhysiOBS. PhysiOBS is an observation analysis tool that can be used in the post-study analysis phase. PhysiOBS uses nonspecific skin conductance responses (NS-SCRs) in order to auto-report time periods that are probably associated with a problematic interaction. PhysiOBS can also combine multiple data sources. Hence, UX evaluators are able to further investigate a recorded session in order to reveal additional interaction flaws. The integrated stress assessment mechanism, which uses four trained classifiers, can be applied in the reported periods (auto/expert-reported) in order to classify them as stress or non-stress. For the purpose of the validation study, 24 users were recruited in order to participate in a lab experiment. Results showed that our stress assessment mechanism supports UX evaluators by accurately identifying stressful regions within an interaction scenario.

摘要

HCI研究人员和从业人员越来越多地使用生理数据来测量用户体验（UX）参数。生理数据的动态性质为深入了解用户的交互体验提供了一个连续的窗口。然而，为了真正地提供信息，生理信号需要以系统和有效的方式链接到用户的交互体验方面，例如他们的情绪状态。研究表明，皮肤电导是与压力高度相关的生理信号。本文的主要目的是对我们提出的压力检测机制进行验证研究，该机制已集成到名为PhysiOBS的软件中。PhysiOBS是一种观察分析工具，可用于研究后分析阶段。PhysiOBS使用非特异性皮肤电导响应（NS-SCR），以便自动报告可能与有问题的相互作用相关的时间段。PhysiOBS也可以合并多个数据源。因此，UX评估人员能够进一步调查记录的会话，以发现其他交互缺陷。可以在报告的期间（自动/专家报告）中应用使用四个受过训练的分类器的综合压力评估机制，以将其分类为压力或非压力。为了进行验证研究，招募了24位用户以参加实验室实验。结果表明，我们的压力评估机制通过准确识别交互场景中的压力区域来支持UX评估人员。