Before stress overcomes you, we overcome it : a digital solution to predict and relieve acute stress in young adults

Abstract

Stress is natural, especially during this unprecedented COVID-19 crisis that has brought various emotions and challenges. However, stress experienced over an extended period can lead to serious health problems. It is therefore important to timely detect and overcome it. Studies conducted in the past have shown the signi_cance of Electrodermal Activity (EDA) and Heart Rate Variability (HRV) in stress detection. We present a digital solution that involves both stress prediction and mitigation with the help of an Android Application. We use incremental learning to personalize the machine learning model that predicts stress arousal using HRV indices and EDA measurements collected continuously via a wearable device. If the user is found stressed at any moment, the application provides personalized recommendations for a stress-relieving activity. To provide personalized recommendations, we use a clustering algorithm preceded by Thompson Sampling to determine user activity preferences in the cold start phase.