Innovative Approaches in Early Detection of Depression: Leveraging Facial Image Analysis and Real-Time Chabot Interventions

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Author(s): Rasmita Kumari Mahanty (VNR Vignana Jyothi Institute of Engineering and Technology, India), Amrita Budarapu (G. Narayanamma Institute of Technology and Science, India), Nayan Rai (G. Narayanamma Institute of Technology and Science, India)and C. Bhagyashree (G. Narayanamma Institute of Technology and Science, India)
Copyright: 2025
Pages: 22
Source title: Modern Advancements in Surveillance Systems and Technologies
Source Author(s)/Editor(s): Dina Darwish (Ahram Canadian University, Egypt)
DOI: 10.4018/979-8-3693-6996-8.ch010

Keywords: Information Science Reference / Security & Forensics / Surveillance & Monitoring / Surveillance Systems

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Abstract

This chapter study is about Depression and it's a prevalent and significant medical disorder that significantly affects emotions, thoughts, and behaviors. As such, early detection and care are necessary to limit its severe repercussions, which include suicide and self-harm. Determining who is suffering from mental health issues is a difficult task that has historically relied on techniques such as patient interviews and Depression, Anxiety, and Stress (DAS) scores. Acknowledging the shortcomings of these traditional methods, this study seeks to develop a model designed especially for the early detection of depression and to provide individualized recommendations for interventions. Instead of verbal self-evaluation, this approach interprets emotional indicators that are subtle but indicative of depression symptoms using facial image analysis.

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Innovative Approaches in Early Detection of Depression: Leveraging Facial Image Analysis and Real-Time Chabot Interventions

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