Decision of Unstable Human Sentiments Using Bio Signals

Nishchal P. Bhole, Ayesha Butalia

Abstract: The capacity to identify sentiments is one of the signs of sentiments intelligence. This paper proposed UNSTABLE HUMAN SENTIMENTS DETECTION SYSTEM (UHSDS) to identify sentiments utilizing physiological signs acquired from numerous subjects. IAPS (International Affective Picture System) pictures were utilized to inspire target sentiments. Four physiological signals: Electrocardiogram (EKG or ECG) Blood Volume Pulse (BVP), Electromyography (EMG) and Skin Temperature (SKT) were chosen to obtain peculiarities for identification. Two pattern classification systems, Fisher Discriminate and SVM system are utilized and looked at for enthusiastic state grouping. The trial results show that the proposed UHSDS gives exceptionally steady and fruitful passionate characterization execution as 92 % in excess of six sentiments states. Experimenters measured higher Heart Rates amid remembered anger and happiness outside a research center environment with a Smartphone application that relied on photoplethysmography.

Keywords: The capacity to identify sentiments is one of the signs of sentiments intelligence This paper proposed UNSTABLE HUMAN SENTIMENTS DETECTION SYSTEM UHSDS to identify sentiments utilizing physiological signs acquired from numerous subjects IAPS International Affective Picture System pictures were utilized to inspire target sentiments Four physiological signalsElectrocardiogram EKG or ECG Blood Volume Pulse BVP, Electromyography EMG and Skin Temperature SKT were chosen to obtain peculiarities for identification Two pattern classification systems, Fisher Discriminate and SVM system are utilized and looked at for enthusiastic state grouping The trial results show that the proposed UHSDS gives exceptionally steady and fruitful passionate characterization execution as 92 % in excess of six sentiments states Experimenters measured higher Heart Rates amid remembered anger and happiness outside a research center environment with a Smartphone application that relied on photoplethysmography