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.
Index Terms: Deep Learning, Stress Identification, Child Health, Physiological Parameters, Body Humidity, Body Tem- perature, Step Count.
Cite:
Hima Vijayan V P*, Asif Shahkutty, Akshay S, "Deep Learning-Based Stress Identification in Children: Unraveling Physiological Patterns", IJIREEICE International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, vol. 12, no. 1, 2024, Crossref https://doi.org/: 10.17148/IJIREEICE.2024.12103.
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