Approaches, Applications, and Challenges in Physiological Emotion Recognition—A Tutorial Overview

An automatic emotion recognition system can serve as a fundamental framework for various applications in daily life from monitoring emotional well-being to improving the quality of through better regulation. Understanding process manifestation becomes crucial building systems. experience results changes not only interpersonal behavior but also physiological responses. Physiological signals are one most reliable means recognizing emotions since individuals cannot consciously manipulate them long duration. These be captured by medical-grade wearable devices, well commercial smart watches and bands. With shift research direction laboratory unrestricted life, devices have been employed ubiquitously. However, this has introduced several challenges, such low data quality, dependency on subjective self-reports, unlimited movement-related changes, artifacts signals. This tutorial provides an overview practical aspects recognition, experiment design, properties different modalities, existing datasets, suitable machine learning algorithms data, applications. It aims provide necessary psychological backgrounds theories emotions, thereby laying foundation recognition. Finally, discusses open directions possible solutions.