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When we seek to determine the experiences of individuals, their affective state or whether they are cognitively challenged, we commonly interrogate them verbally. Various types of questionnaires exist to probe for individual experiences, allowing us to readily evaluate how subjects are affected by interacting ...

When we seek to determine the experiences of individuals, their affective state or whether they are cognitively challenged, we commonly interrogate them verbally. Various types of questionnaires exist to probe for individual experiences, allowing us to readily evaluate how subjects are affected by interacting with, or being exposed to, certain products, procedures, or situations.

While these ‘explicit’ measures are often relatively easy to acquire and interpret for human adult populations, they can be seriously biased by factors such as memory, cultural background and the act of interrogation itself. These limitations can be met by using measures that convey information implicitly. Such measures can be behavioral (ranging from navigating behavior to facial expression) and physiological (ranging from heart rate responses to EEG).

Implicit measures have a long tradition in the field of psychology, psychophysiology, and neuroscience, and are common in ‘affective computing’, neuroergonomics and brain-computer interfaces. Research on how to probe experience, affective and cognitive states in an implicit way gained interest with the rise of (wearable) sensing systems that enable capturing multiple sources of information in real-life conditions.

Here we will focus on novel, methodological developments of implicit measures. Topics of interest include the design of new methodologies (new tools to measure and quantify behavior and physiology in ecological environments, new ways of combining measures from multiple modalities), methodologies to properly interpret and validate these proxies and derived data, or techniques to facilitate generalization of implicit measures across contexts. These innovative methodologies can be linked to any (real-life) setting, e.g. assessing food experience and food choices, measuring the impact of environmental characteristics on mental state and movement behavior, or monitoring attention of a group in an educational setting.

The Research Topic is connected to the conference ‘Measuring Behavior/Seminars on Behavioral Methods’ (MBSBM) which takes place May 27-29, 2020 in Krakow, Poland: http://www.measuringbehavior.org. MBSBM is the premier interdisciplinary event for scientists and practitioners concerned with the study of human or animal behavior. This unique conference focuses on methods, techniques, and tools in behavioral research in the widest sense and aims to bridge between disciplines by bringing together people who may otherwise be unlikely to meet. Attendees of this conference are invited by the editors to submit manuscript about their presentation to this Research Topic.

Keywords: measuring behavior, human behavior, affective computing, wearable sensors, multimodal measures, implicit measures


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