Masters Thesis

Bio-signal Based Emotion Detection System.

Recently there is a growing trend towards the emotional information to be used in the human-computer interaction. In order to get the correct interaction from the computer, a human has to provide the appropriate inputs. Inputs are recorded by various bio-medical sensors and processed for generating the appropriate data. For examples, Skin conductance is used to measure the skin potential between two nodes in the human body whereas heart rate as the name suggests is used to measure the variation in heart rate. Biomedical signals are generated using a neural network in a human body and used to estimate the emotions. As these signals are generated using the neural network, it is not possible to control it artificially. Due to this reason, it is the reliable source of the estimation of such information. Heart Rate Variability (HRV) and Galvanic Skin Response/Conductance (GSR) is changed when any type of emotion is induced in the human body. This change in signals represents certain characteristics which are used to estimate the emotions. Mainly there are two types of emotions which are negative emotions and positive emotions. Positive emotion includes happiness and normal behavior whereas negative emotion includes fear, anger and sadness. The current study investigated five different types of emotions. This research consists of measurement procedures for the emotion detection using biomedical signals.


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