| Abstrak/Abstract |
Emotion recognition may establish a clinical framework for measuring emotional wellbeing and screening for quality of life, cognitive dysfunction, and mental disorder. Emotions are conveyed not just through interpersonal actions but also by several physiological differences. Emotions can be monitored using physiological signals in wearable devices such as smartwatches or wrist bands. However, there are various challenges for detecting emotion in unrestricted daily life using wearable or smartwatch devices. These challenges result in lower performances of such systems compared to semi-restricted and laboratory environment studies. The addition of uniqueness in each individual physiological signal, physical activity level, and activity type to the physiological signals can affect classification accuracy of these systems. To tackle these challenges, we present a brief literature review on the study of physiological signals using wearable devices primarily from the last three years. The phase of emotion recognition using physiological signals is briefly defined. This paper also presents listed forms of physiological signals and various sensors for detecting them. In addition, we discussed the emotional models and emotional stimulation approaches. This study is expected to bring new insight into research challenges, limitations, and possible future emotion detection and recognition using wearable or smartwatch devices. |
