A Method for Daily Normalization in Emotion Recognition

LEANDRO A. BUGNON; RAFAEL A. CALVO; DIEGO H. MILONE

Ciudad Autónoma de Buenos Aires

Congreso; 15th Argentine Symposium on Technology, AST 2014; 2014

Universidad de Palermo

Affects carry important information in human communica- tion and decision making, and their use in technology have grown in the past years. Particularly, emotions have a strong effect on physiology, which can be assessed by biomedical signals. This signals have the advan- tage that can be recorded continuously, but also can become intrusive. The present work introduce an emotion recognition scheme based only in photoplethysmography, aimed to lower invasiveness. The feature extrac- tion method was developed for a realistic real-time context. Furthermore, a feature normalization procedure was proposed to reduce the daily vari- ability. For classification, two well-known models were compared. The proposed algorithms were tested on a public database, which consist of 8 emotions expressed continuously by a single subject along different days. Recognition tasks were performed for several number of emotional cate- gories and groupings. Preliminary results shows a promising performance with up to 3 emotion categories. Moreover, the recognition of arousal and emotional events was improved for larger emotion sets.