Autonomic nervous system response patterns specificity to basic emotions

Collet, Christian; Vernet-Maury, E.; Delhomme, G.; Dittmar, A.

doi:10.1016/s0165-1838(96)00108-7

Cited by 213 publications

(115 citation statements)

References 49 publications

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“…Vinkers et al recently confirmed indications that stress influences body temperature in humans and found that body temperature rises with increasing stress [46]. In a study about autonomic nervous system response patterns evoked by emotions, skin temperature was demonstrated to be different in response to anger and fear [14].…”

Section: Biometric Sensorsmentioning

confidence: 86%

Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors

Züger

Fritz

2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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Interruptions of knowledge workers are common and can cause a high cost if they happen at inopportune moments. With recent advances in psycho-physiological sensors and their link to cognitive and emotional states, we are interested whether such sensors might be used to measure interruptibility of a knowledge worker. In a lab and a field study with a total of twenty software developers, we examined the use of psycho-physiological sensors in a real-world context. The results show that a Naive Bayes classifier based on psychophysiological features can be used to automatically assess states of a knowledge worker's interruptibility with high accuracy in the lab as well as in the field. Our results demonstrate the potential of these sensors to avoid expensive interruptions in a real-world context. Based on brief interviews, we further discuss the usage of such an interruptibility measure and interruption support for software developers. Interruptibility of Software Developers and its Prediction Using Psycho-Physiological SensorsManuela Züger and Thomas Fritz Department of Informatics University of Zurich, Switzerland {zueger, fritz}@ifi.uzh.ch ABSTRACTInterruptions of knowledge workers are common and can cause a high cost if they happen at inopportune moments. With recent advances in psycho-physiological sensors and their link to cognitive and emotional states, we are interested whether such sensors might be used to measure interruptibility of a knowledge worker. In a lab and a field study with a total of twenty software developers, we examined the use of psycho-physiological sensors in a real-world context. The results show that a Naïve Bayes classifier based on psychophysiological features can be used to automatically assess states of a knowledge worker's interruptibility with high accuracy in the lab as well as in the field. Our results demonstrate the potential of these sensors to avoid expensive interruptions in a real-world context. Based on brief interviews, we further discuss the usage of such an interruptibility measure and interruption support for software developers.

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Section: Biometric Sensorsmentioning

confidence: 86%

Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors

Züger

Fritz

2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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“…Bi-modal ASP : Two studies will be presented that employed bi-modal ASP and deviate only with respect to the stimuli that were used for emotion elicitation. The research in these two chapters also assessed the influence of emotion representations by analyzing the obtained data using both the dimensional valence-arousal model [105,176,202,452,567,647] and the six basic emotions [116,181,391]. Moreover, the impact of the environment (or context), the personality traits neuroticism and extroversion, and demographics on ASP was explored.…”

Section: Prologuementioning

confidence: 99%

“…The theory behind this model assumes that these emotion categories are hardcoded into our neural system and recognized universally [116,181,391] (cf. the debate on color categories as unveiled by Berlin and Kay [550] and the notion of basic level categories coined by Hoenkamp, Stegeman, and Schomaker [284]).…”

Section: Modeling Emotionmentioning

confidence: 99%

Affective signal processing (ASP) : unraveling the mystery of emotions

Broek¹

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“…The theory behind this model assumes that these emotion categories are hardcoded into our neural system and recognized universally [19,28,56] (cf. the debate on color categories as unveiled by Berlin and Kay [82]).…”

Section: Modeling Emotionmentioning

confidence: 99%

Ubiquitous emotion-aware computing

Broek

2011

Pers Ubiquit Comput

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Emotions are a crucial element for personal and ubiquitous computing. What to sense and how to sense it, however, remain a challenge. This study explores the rare combination of speech, electrocardiogram, and a revised Self-Assessment Mannequin to assess people's emotions. 40 people watched 30 International Affective Picture System pictures in either an office or a living-room environment. Additionally, their personality traits neuroticism and extroversion and demographic information (i.e., gender, nationality, and level of education) were recorded. The resulting data were analyzed using both basic emotion categories and the valence-arousal model, which enabled a comparison between both representations. The combination of heart rate variability and three speech measures (i.e., variability of the fundamental frequency of pitch (F0), intensity, and energy) explained 90% (p \ .001) of the participants' experienced valence-arousal, with 88% for valence and 99% for arousal (ps \ .001). The six basic emotions could also be discriminated (p \ .001), although the explained variance was much lower: 18-20%. Environment (or context), the personality trait neuroticism, and gender proved to be useful when a nuanced assessment of people's emotions was needed. Taken together, this study provides a significant leap toward robust, generic, and ubiquitous emotion-aware computing.

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Autonomic nervous system response patterns specificity to basic emotions

Cited by 213 publications

References 49 publications

Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors

Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors

Affective signal processing (ASP) : unraveling the mystery of emotions

Ubiquitous emotion-aware computing

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