title: Affective Computing and the Impact of Gender and Age.
abstract: Affective computing aims at the detection of users' mental states, in particular, emotions and dispositions during human-computer interactions. Detection can be achieved by measuring multimodal signals, namely, speech, facial expressions and/or psychobiology. Over the past years, one major approach was to identify the best features for each signal using different classification methods. Although this is of high priority, other subject-specific variables should not be neglected. In our study, we analyzed the effect of gender, age, personality and gender roles on the extracted psychobiological features (derived from skin conductance level, facial electromyography and heart rate variability) as well as the influence on the classification results. In an experimental human-computer interaction, five different affective states with picture material from the International Affective Picture System and ULM pictures were induced. A total of 127 subjects participated in the study. Among all potentially influencing variables (gender has been reported to be influential), age was the only variable that correlated significantly with psychobiological responses. In summary, the conducted classification processes resulted in 20% classification accuracy differences according to age and gender, especially when comparing the neutral condition with four other affective states. We suggest taking age and gender specifically into account for future studies in affective computing, as these may lead to an improvement of emotion recognition accuracy.
authors.affiliation: Department of Psychosomatic Medicine and Psychotherapy, Medical Psychology, Ulm University, Ulm, Germany.
authors.forename: Stefanie
authors.initials: S
authors.lastname: Rukavina
authors.affiliation: Department of Psychosomatic Medicine and Psychotherapy, Medical Psychology, Ulm University, Ulm, Germany.
authors.forename: Sascha
authors.initials: S
authors.lastname: Gruss
authors.affiliation: Department of Psychosomatic Medicine and Psychotherapy, Medical Psychology, Ulm University, Ulm, Germany.
authors.forename: Holger
authors.initials: H
authors.lastname: Hoffmann
authors.affiliation: College of Teacher Education, Lishui University, Lishui, P.R. China.
authors.forename: Jun-Wen
authors.initials: JW
authors.lastname: Tan
authors.affiliation: Department of Psychosomatic Medicine and Psychotherapy, Medical Psychology, Ulm University, Ulm, Germany.
authors.forename: Steffen
authors.initials: S
authors.lastname: Walter
authors.affiliation: Department of Psychosomatic Medicine and Psychotherapy, Medical Psychology, Ulm University, Ulm, Germany.
authors.forename: Harald C
authors.initials: HC
authors.lastname: Traue
mesh_terms: D000368:Aged; D001519:Behavior / Q000502:physiology*; D004576:Electromyography; D004644:Emotions / Q000502:physiology*; D005783:Gender Identity; D006801:Humans; D010551:Personality / Q000502:physiology; D012879:Skin Physiological Phenomena; D014584:User-Computer Interface