Intelligent Emotional Recognition Using Biometric Information and Stress Index

• Published in: Journal of Digital Contents Society Vol. 25; no. 8; pp. 2125 - 2133
• Main Authors: Kim, Tae-Yeun, Kim, Sung-Hwan
• Format: Journal Article
• Language: English
• Published: 한국디지털콘텐츠학회 31.08.2024
• Subjects: 컴퓨터학; Stress Index; Emotion Modeling; 스트레스 지수; 감성 모델링; SVM 알고리즘; 생체 정보; SVM Algorithm; Biometric Information; 생체 감성 인식; Biometric Emotion Recognition
• ISSN: 1598-2009; 2287-738X
• DOI: 10.9728/dcs.2024.25.8.2125

In this paper, input biometric values received from pulse sensor, blood pressure sensor, and blood glucose sensor were stored in the database, and emotions were classified according to the stress index using the Support Vector Machine (SVM) algorithm as a system that classifies the corresponding color and music by recognizing emotions according to the stress index after acquiring the user’s biometric information (blood sugar, diastolic blood pressure, systolic blood pressure, and pulse) through wireless sensors. The highest accuracy of 88.45% was obtained when the radial basis function (RBF) kernel parameter of the SVM algorithm using 3,000 datasets was set to σ=5, C=1, As a result of training, the average accuracy was calculated as 86.08%. The proposed bio-emotion recognition classification system using the SVM algorithm is expected to contribute to the research in user–computer emotional exchange by means of smart classification of colors and music based on the user's emotions. KCI Citation Count: 0