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http://dx.doi.org/10.7471/ikeee.2017.21.4.397

Smart Emotion Management System based on multi-biosignal Analysis using Artificial Intelligence  

Noh, Ayoung (Dept. of Computer Science and Engineering, Koreatech University)
Kim, Youngjoon (Dept. of Computer Science and Engineering, Koreatech University)
Kim, Hyeong-Su (Dept. of Computer Science and Engineering, Koreatech University)
Kim, Won-Tae (Dept. of Computer Science and Engineering, Koreatech University)
Publication Information
Journal of IKEEE / v.21, no.4, 2017 , pp. 397-403 More about this Journal
Abstract
In the modern society, psychological diseases and impulsive crimes due to stress are occurring. In order to reduce the stress, the existing treatment methods consisted of continuous visit counseling to determine the psychological state and prescribe medication or psychotherapy. Although this face-to-face counseling method is effective, it takes much time to determine the state of the patient, and there is a problem of treatment efficiency that is difficult to be continuously managed depending on the individual situation. In this paper, we propose an artificial intelligence emotion management system that emotions of user monitor in real time and induced to a table state. The system measures multiple bio-signals based on the PPG and the GSR sensors, preprocesses the data into appropriate data types, and classifies four typical emotional states such as pleasure, relax, sadness, and horror through the SVM algorithm. We verify that the emotion of the user is guided to a stable state by providing a real-time emotion management service when the classification result is judged to be a negative state such as sadness or fear through experiments.
Keywords
Multi-Biosignals; SVM; Biosignal Preprocessing; Emotion Classification; Emotion management;
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Times Cited By KSCI : 3  (Citation Analysis)
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