Stimulus–response compatibility and affective computing: a review

Abstract

Affective computing, a human-factors effort to investigate the merits of emotions while people are working with human-computer interfaces, is gaining momentum. Measures to quantify affect (or its influences) range from EEG, to measurements of autonomic nervous system responses (e.g., heart rate, blood pressure), to less objective self-reports. Here we claim that simple response-time measurements may be a viable alternative to measure (indirectly) the effects of affect on performance by providing a review of experimental paradigms and associated models of human information processing. In particular, we focus on stimulus-response compatibility paradigms that have provided important insights for human-factors research, for instance regarding the important role of the spatial layout of interface design on the efficiency of human task performance, to show that these paradigms can also be applied to investigate the role of affect in human-computer interaction.

Monitoring Cognitive and Emotional Processes Through Pupil and Cardiac Response During Dynamic Versus Logical Task

“…In mental workload literature (Brookings et al 1996;Dahlstrom and Nahlinder 2006), as well as in human machine interface studies (Gevins and Smith 2003;Iqbal et al 2005;Lemmens et al 2007), psychophysiological data are commonly used as an index of the level of cognitive demand generated by a task (e.g. increased temporal demand, memory loading etc.).…”

Gender and Personality Trait Measures Impact Degree of Affect Change in a Hedonic Computing Paradigm

“…For example, it is acknowledged that people respond differentially to stressful stimuli. To detect stress and affect, methods that cater to the individual have been used, such as measuring galvanic skin response (Healey, Picard, & Dabek, 1998), blood volume pressure (Ward & Marsden, 2003), electromyograms (Scheirer, Fernandez, Klein, & Picard, 2002), squeeze pressure on a mouse (van Galen, Liesker, & De Haan, 2004), keystrokes (Vizer, Zhou, & Sears, 2009), and response time (Lemmens, De Haan, van Galen, & Meulenbroek, 2007), among others. These physiological measurements are customized to the user and have even been used to alter computer game difficulty in real time based on the user's current affect (Liu, Agrawal, Sarkar, & Chen, 2009).…”