Recently, modern people have excessive stress in their daily lives. With the advances in physiological sensors and wearable technology, people?s physiological status can be tracked, and stress levels can be recognized for providing beneficial services. Smartwatches and smartbands constitute the majority of wearable devices. Although they have an excellent potential for physiological stress recognition, some crucial issues need to be addressed, such as the resemblance of physiological reaction to stress and physical activity, artifacts caused by movements and low data quality. This paper focused on examining and differentiating physiological responses to both stressors and physical activity. Physiological data are collected in the laboratory environment, which contain relaxed, stressful and physically active states and they are differentiated successfully by using machine learning.
Machine learning, stress detection, affective computing, smart band, PPG, physical activity detection
CAN, YEKTA SAİD
"Stressed or just running? Differentiation of mental stress and physical activityby using machine learning,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 30:
1, Article 21.
Available at: https://journals.tubitak.gov.tr/elektrik/vol30/iss1/21