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Published in:
2018 | OriginalPaper | Chapter
Emotion Recognition Through Cardiovascular Response in Daily Life Using KNN Classifier
Authors : Youseop Jo, Hyunwoo Lee, Ayoung Cho, Mincheol Whang
Published in: Advances in Computer Science and Ubiquitous Computing
Publisher: Springer Singapore
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Abstract
Emotion in daily life is difficult to recognize due to disadvantageous of continuous measurement. This study was to develop the method for recognizing daily emotion from a measurement of daily cardiovascular response by using the developed wireless sensor. Seven subjects assessed subjective emotions based on Russell’s emotional circumplex model every 3 h wearing a photo-plethysmography (PPG) sensor. The heart rate variability (HRV) according to two emotional dimensions were tested by the Kruskal-Wallis test. Significant parameters of them were determined to be distinguished among emotions and were applied to recognize emotions using the K-Nearest Neighbor (KNN) algorithm. The arousal and valence were recognized with respective 88.2% and 56.2% accuracy. The methods in this study is extended to monitor and recognized in industrial domain and health care domain requiring recognition of long-term emotion.