Automatic emotion recognition has always been the talk of the town, for it finds numerous contributions to the welfare of different sectors of the society and enhances the standard of living. Emotion detection based on facial expression analysis, ECG, EEG and psychological signal processing are prevalent. Due to the drawbacks of the existing vision system for facial muscle action detection, such as it deals only with the frontal-view face images and is unable to handle the temporal dynamics of facial actions, emotion recognition using facial expression analysis is not always accurate. However, with the analysis of various psychological, EEG and ECG signal processing based emotion detection models, better efficiency, applicability to multiple users and that cause minimum amount of user inconvenience, have become plausible. As ECG signals are involuntary reactions of the body, and as such are very difficult to mask, unlike facial expressions, we intend this survey paper to be useful for the research communities working on affect detection using ECG signals processing. The paper covers automatic emotion detection model description, various linear and non-linear techniques of emotion detection specifically based on ECG signal processing. Furthermore, its limitations and applications are also explored.