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What is AMIGOS

Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence
Publicly available database for emotion classification.
Published in Chapter:
Emotion Detection and Classification Using Machine Learning Techniques
Amita Umesh Dessai (Goa College of Engineering, India) and Hassanali G. Virani (Goa College of Engineering, India)
DOI: 10.4018/978-1-6684-5673-6.ch002
Abstract
This chapter analyzes 57 articles published from 2012 on emotion classification using bio signals such as ECG and GSR. This study would be valuable for future researchers to gain an insight into the emotion model, emotion elicitation and self-assessment techniques, physiological signals, pre-processing methods, feature extraction, and machine learning techniques utilized by the different researchers. Most investigators have used openly available databases, and some have created their datasets. The studies have considered the participants from the healthy age group and of similar cultural backgrounds. Fusion of the ECG and GSR parameters can help to improve classification accuracy. Additionally, handcrafted features fused with automatically extracted deep machine learning features can increase classification accuracy. Deep learning techniques and feature fusion techniques have improved classification accuracy.
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