Authors:
Martin Malčík
;
Miroslava Miklošíková
and
Tomáš Zemčík
Affiliation:
Department of Social Sciences, VSB-Technical University of Ostrava, 17. Listopadu 15, Ostrava, Czech Republic
Keyword(s):
Electrodermal Activity, Galvanic Skin Response, Heart Rate Variability, Wearable Devices, Emotion Diagnostics.
Abstract:
We live in an age in which technology provides us with constant access to virtual online services. Consumption and production of an immense amount of instant data, which is becoming the basic raw material autonomously processed by artificial intelligence algorithms, open up brave new possibilities and levels of research and its application in many traditional scientific disciplines. Biometrics is one of the disciplines experiencing an unexpected renaissance, owing to the wide availability of cheap sensory technologies connected to the network. We find great untapped potential, especially in devices that allow measuring the body’s physiological responses to emotional stimuli, such as heart rate (HR) and electrodermal activity (EDA), also known as galvanic skin response (GSR). Many readily available and professional wearable devices provide digital recordings of these variables. However, each of these technologies suffers from multiple shortcomings. These shortcomings stand in the way
of the mass popularization of the technology, which enables, among other things, real-time monitoring and digital recording of the body’s physiological reactions to emotional stimuli. In other words, creating big data that can be used for digital, automated reconstruction of certain aspects of emotionality. In our research, we have identified three main social areas where these technologies are of interest: laboratories, professionals working with the human psyche-body-emotionality, and regular users of biofeedback devices such as wearable devices (WD). Each of these groups has specific requirements in terms of the hardware implementation of the technology, and software and measurement methodology open to users. In our emotion laboratory, we have developed a series of comprehensive solutions, Sensetio, based on a thorough analysis of the needs of all three groups of users of biofeedback technologies. We intend to obtain standardized big data sets for further thorough scientific analysis.
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