Enhancing Mental Health Care with IoT and Machine Learning: Monitoring and Intervention
Abstract
Mental health care can benefit significantly from continuous monitoring and timely interventions. This paper explores the application of IoT and machine learning in enhancing mental health care. We propose a system that uses IoT devices to monitor physiological and behavioral indicators of mental health and machine learning algorithms to analyze this data for early detection of mental health issues such as depression and anxiety. The system also provides personalized intervention recommendations. A pilot study with participants suffering from mental health conditions shows promising results in improving mental health outcomes. The paper also addresses privacy concerns and the ethical use of data in mental health care.
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