Simulation Controlled for Stress Management and Detection Using IoT

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Nikhil N. Sadawarti; Isheeta Rohanker; Chinmay Joshi; Shruti Baghele; Dr. LEENA PATIL

Simulation Controlled for Stress Management and Detection Using IoT

Authors: Nikhil N. Sadawarti, Isheeta Rohanker, Chinmay Joshi, Shruti Baghele, Dr. LEENA PATIL

Unique Paper ID: 153668
Volume: 8
Issue: 8
PageNo: 200-203

Keywords: Stress Detection Health EEG GSR ECG Monitoring Affective Computing.

Abstract:
Depression is a part of life. Unpleasant emotional states that people experience in their emotional lives, such as working long hours in front of a computer. Depression can be beneficial, but it can also be detrimental to your health if it persists. Therefore, it is important to tell a person about his or her risky lifestyle and even to warn him or her before a major problem arises. To detect early depression, the Deep Learning (DL) method, using real-time data and measuring heart rate, can. determine a person's emotional state, and the Internet of Things (IoT) is used to educate patients about their depressive conditions. Depression is a state of emotional or psychological distress caused by internal or external events. The human body responds to stress by releasing complex hormones and substances such as adrenaline and cortisol. Borderline Personality Disorder affects those under high blood pressure (BPD). Severe depression in people who have already been diagnosed with a borderline personality disorder or schizophrenia can be dangerous

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ISSN: 2349-6002
Volume: 8
Issue: 8
PageNo: 200-203

Simulation Controlled for Stress Management and Detection Using IoT

Available:https://ijirt.org/article?manuscript=153668

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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