Emotion recognition – Validation of a measurement environment based on psychophysiological parameters
Authors: Ramona Schmid, Linn Braunmiller, Lena Hansen, Christopher Schonert, Knut Möller, Verena Wagner-Hartl
Abstract: Emotions are an essential part of our daily social interaction. They are highly complex processes and can cause different physiological, behavioral, and cognitive changes in individuals. A person for whom it is difficult or impossible to interpret emotions may face major problems in everyday life, e.g., patients with autism spectrum disorders. Understanding emotions is not only of great importance in private social interactions but also in the working environment, e.g., for managers or collaborative work. Initial research aims to positively influence behavior and outcomes of social interactions at work by emotion training. Additionally, the COVID-19 pandemic limited social interactions drastically. Due to isolation and contact restrictions, it is important to understand the impact on our ability to recognize emotions. Hence, there is a great interest in emotion research, including how emotions can be measured. For this purpose, a measuring environment was implemented that allows to detect a person’s emotional state. The aim of the presented study was to validate the measurement environment by evoking different emotions. As stimulus, affective visual material (EmoPicS) was used to address different emotional poles. To make emotions measurable, a multidimensional approach combining subjective and objective measures according to Boucsein and colleagues was chosen. Therefore, participants rated their emotional state using the Self-Assessment Manikin (SAM) on the three different affective dimensions: valence, arousal, and dominance. Also, facial expression was recorded as subjective measure. The objective psychophysiological measures were electrocardiogram (ECG), electrodermal activity (EDA) and electromyogram on the forearm and neck (EMG). Results prove a successful validation of the measurement environment. Furthermore, first findings show a significant difference regarding the subjective assessment of the affective visual material for the dimension valence. Nevertheless, no significant differences were found in the psychophysiological data for the stimulus material used. Future studies should use stronger stimuli to evoke emotions, e.g., by combining auditory and visual stimuli or using videos.
Keywords: Emotion Recognition, Psychophysiology, Measurement Environment
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