Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 6: EECSI 2019

Classification of Physiological Signals for Emotion Recognition using IoT

Sadhana Tiwari (Indian Institute of Information Technology)
Sonali Agarwal (Indian Institute of Information Technology)
Muhammad Syafrullah (Universitas Budi Luhur)
Krisna Adiyarta (Universitas Budi Luhur)



Article Info

Publish Date
18 Sep 2019

Abstract

Emotion recognition gains huge popularity now a days. Physiological signals provides an appropriate way to detect human emotion with the help of IoT. In this paper, a novel system is proposed which is capable of determining the emotional status using physiological parameters, including design specification and software implementation of the system. This system may have a vivid use in medicine (especially for emotionally challenged people), smart home etc. Various Physiological parameters to be measured includes, heart rate (HR), galvanic skin response (GSR), skin temperature etc. To construct the proposed system the measured physiological parameters were feed to the neural networks which further classify the data in various emotional states, mainly in anger, happy, sad, joy. This work recognized the correlation between human emotions and change in physiological parameters with respect to their emotion.

Copyrights © 2019






Journal Info

Abbrev

EECSI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, ...