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Sensors 2018, 18(1), 102; https://doi.org/10.3390/s18010102

Detection of Craving for Gaming in Adolescents with Internet Gaming Disorder Using Multimodal Biosignals

1
Department of Biomedical Engineering, Hanyang University, Seoul 04673, Korea
2
Center for Bionics, Korea Institute of Science and Technology, Seoul 02792, Korea
3
School of Electronic and Biomedical Engineering, Tongmyong University, Busan 48520, Korea
*
Author to whom correspondence should be addressed.
Received: 25 September 2017 / Revised: 12 December 2017 / Accepted: 13 December 2017 / Published: 1 January 2018
(This article belongs to the Special Issue Sensors for Health Monitoring and Disease Diagnosis)
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Abstract

The increase in the number of adolescents with internet gaming disorder (IGD), a type of behavioral addiction is becoming an issue of public concern. Teaching adolescents to suppress their craving for gaming in daily life situations is one of the core strategies for treating IGD. Recent studies have demonstrated that computer-aided treatment methods, such as neurofeedback therapy, are effective in relieving the symptoms of a variety of addictions. When a computer-aided treatment strategy is applied to the treatment of IGD, detecting whether an individual is currently experiencing a craving for gaming is important. We aroused a craving for gaming in 57 adolescents with mild to severe IGD using numerous short video clips showing gameplay videos of three addictive games. At the same time, a variety of biosignals were recorded including photoplethysmogram, galvanic skin response, and electrooculogram measurements. After observing the changes in these biosignals during the craving state, we classified each individual participant’s craving/non-craving states using a support vector machine. When video clips edited to arouse a craving for gaming were played, significant decreases in the standard deviation of the heart rate, the number of eye blinks, and saccadic eye movements were observed, along with a significant increase in the mean respiratory rate. Based on these results, we were able to classify whether an individual participant felt a craving for gaming with an average accuracy of 87.04%. This is the first study that has attempted to detect a craving for gaming in an individual with IGD using multimodal biosignal measurements. Moreover, this is the first that showed that an electrooculogram could provide useful biosignal markers for detecting a craving for gaming. View Full-Text
Keywords: internet gaming disorder; internet game addiction; biosignal analysis; craving; machine learning internet gaming disorder; internet game addiction; biosignal analysis; craving; machine learning
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Kim, H.; Ha, J.; Chang, W.-D.; Park, W.; Kim, L.; Im, C.-H. Detection of Craving for Gaming in Adolescents with Internet Gaming Disorder Using Multimodal Biosignals. Sensors 2018, 18, 102.

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