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Wearable Recognition System for Emotional States Using Physiological Devices

Authors:
Ali Mehmood Khan
Michael Lawo

Keywords: Emotional states; Physiological devices; International Affective Picture System; Machine learning classifier; User studies

Abstract:
Recognizing emotional states is becoming a major part of a user's context for wearable computing applications. The system should be able to acquire a user's emotional states by using physiological sensors. We want to develop a personal emotional states recognition system that is practical, reliable, and can be used for health-care related applications. We propose to use the eHealth platform [1] which is a ready-made, light weight, small and easy to use device for recognizing a few emotional states like ‘Sad’, ‘Dislike’, ‘Joy’, ‘Stress’, ‘Normal’, ‘No-Idea’, ‘Positive’ and ‘Negative’ using decision tree (J48) classifier. In this paper, we present an approach to build a system that exhibits this property and provides evidence based on data for 8 different emotional states collected from 24 different subjects. Our results indicate that the system has an accuracy rate of approximately 98%. In our work, we used four physiological sensors i.e. ‘Blood Volume Pulse’ (BVP), ‘Electromyogram’ (EMG), ‘Galvanic Skin Response’ (GSR), and ‘Skin Temperature’ in order to recognize emotional states (i.e. stress, joy/happy, sad, normal/neutral, dislike, no-idea, positive and negative).

Pages: 131 to 137

Copyright: Copyright (c) IARIA, 2016

Publication date: April 24, 2016

Published in: conference

ISSN: 2308-4359

ISBN: 978-1-61208-470-1

Location: Venice, Italy

Dates: from April 24, 2016 to April 28, 2016