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Depression Behavior Detection Model Based on Participation in Serious Games

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Rough Sets (IJCRS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10314))

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Abstract

Managing depression is one of the main challenges that health specialists have to deal with. Due to the cumulative nature of depression, the major problem is that a long-term observation of symptoms is required to make an accurate decision about an individual’s state. The depressed mood rate of an individual can be estimated according to recorded physiological and emotional information. We propose a mobile health monitoring system using wearable smart identification sensors (EEG, ECG, EMG, gaze tracking, and physical activity data) that capture stress and specific subject behaviors as a result of the participation in a serious game. The main objective is to study the impact of serious games on the human cognitive system in treating the early signs of depression by using a multi-level systems approach for representing the structure and dynamics of human cognitive functions. Our initial findings show that subjects with negative moods have been characterized by psychomotor retardation and lower correlation between the neural and cardiac systems.

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Author information

Authors and Affiliations

  1. Department of Multimedia Engineering, Faculty of Informatics, Kaunas University of Technology, Kaunas, Lithuania

    Rytis Maskeliūnas

  2. Department of Software Engineering, Faculty of Informatics, Kaunas University of Technology, Kaunas, Lithuania

    Tomas Blažauskas & Robertas Damaševičius

Authors
  1. Rytis Maskeliūnas
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  2. Tomas Blažauskas
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  3. Robertas Damaševičius
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Corresponding author

Correspondence to Robertas Damaševičius .

Editor information

Editors and Affiliations

  1. Polish-Japanese Academy of Information Technology, Warsaw, Poland

    Lech Polkowski

  2. University of Regina, Regina, Saskatchewan, Canada

    Yiyu Yao

  3. University of Warmia and Mazury, Olsztyn, Poland

    Piotr Artiemjew

  4. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  5. Southwest Jiaotong University, Chengdu, China

    Dun Liu

  6. Warsaw University, Warszawa, Poland

    Dominik Ślęzak

  7. Silesian University, Sosnowiec, Poland

    Beata Zielosko

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Maskeliūnas, R., Blažauskas, T., Damaševičius, R. (2017). Depression Behavior Detection Model Based on Participation in Serious Games. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10314. Springer, Cham. https://doi.org/10.1007/978-3-319-60840-2_31

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  • DOI: https://doi.org/10.1007/978-3-319-60840-2_31

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