Deep Learning-Based Stress Identification in Children: Unraveling Physiological Patterns

Abstract: Stress detection in children is a critical concern, given its profound impact on their well-being. This paper proposes a novel approach for identifying stress levels in children by analyzing physiological parameters, namely human body humidity, temperature, and step count. Leveraging deep learning techniques, we aim to develop a model capable of discerning stress levels, ultimately aiding in early intervention and support.

Keywords: Deep Learning, Stress Identification, Child Health, Physiological Parameters, Body Humidity, Body Tem- perature, Step Count.