A Review on Physiological Signal Based Emotion Detection

Abstract

Emotions are feelings that are the result of biochemical processes in the body that are influenced by a variety of factors such as one's state of mind, situations, experiences, and surrounding environment. Emotions have an impact on one's ability to think and act. People interact with each other to share their thoughts and feelings. Emotions play a vital role in the field of medicine and can also strengthen the human computer interaction. There are different techniques being used to detect emotions based on facial features, texts, speech, and physiological signals. One of the physiological signal breathing is a parameter which represents an emotion. The rational belief that different breathing habits are correlated with different emotions has expanded the evidence for a connection between breathing and emotion. In this manuscript different recent investigations about the emotion recognition using respiration patterns have been reviewed. The aim of the survey is to sum up the latest technologies and techniques to help researchers develop a global solution for emotional detection system. Various researchers use benchmark datasets and few of them created their own dataset for emotion recognition. It is observed that many investigators used invasive sensors to acquire respiration signals that makes subject uncomfortable and conscious that affects the results. The numbers of subjects involved in the studies reviewed are of the same age and race which is the reason why the results obtained in those studies cannot be applied to diverse population. There is no single global solution exist.

Multimodal and Multidomain Feature Fusion for Emotion Classification Based on Electrocardiogram and Galvanic Skin Response Signals

“…Biological parameters such as ECG, GSR, Electroencephalograms (EEGs), and respiration rate can be used to detect emotions. However, using invasive respiratory sensors to collect data can be uncomfortable for participants [11]. Therefore, the use of non-invasive sensors could make the process more comfortable.…”

“…Although several techniques have been proposed for emotion classification using ECG and GSR modalities, none have explored emotion classification based Biological parameters such as ECG, GSR, Electroencephalograms (EEGs), and respiration rate can be used to detect emotions. However, using invasive respiratory sensors to collect data can be uncomfortable for participants [11]. Therefore, the use of non-invasive sensors could make the process more comfortable.…”