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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21686
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Total Authors : 22487
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| Paper Title: | Machine Learning Based Personalised Mental Health Monitoring and Recommendation for Better Life |
| Authors Name: | Gowthami T D , Karthik D G , Abhishek Kumar M , Dr. Sandesh R S , Dr. Roopa B S |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_204179
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| Published Paper Id: | IJRTI2505274 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Mental illness impacts 970 million individuals worldwide, with the most prevalent disorders being depression and anxiety. Even though the need for mental health care is increasing, there are vast inequalities particularly in low- and middle-income nations where 70% of those afflicted have no access to treatment. To fill this gap, the suggested Mental Health Monitoring App assists users in their management of mental health by monitoring physical activity habits, sleep patterns, and daily activities. These include wake-up times, meals, and physical exercise. Driven by machine learning algorithms, the app examines data like activity levels, steps, sleep quality, and daily rhythms to identify early warning signs of mental health conditions, sends notifications, tips, and prompts to encourage healthier habits like improved sleep, consistent exercise, and awareness. Customized advice guides users in creating healthy habits, which strive to avert mental health decline. Developed on secure foundations such as MongoDB, the application ensures that data is protected and kept confidential. Wearable devices and healthcare APIs are integrated to provide real-time data collection for enhancing user understanding while preserving confidentiality. This personalized, nurturing approach bridges gaps in mental health services, promotes resilience, and enables users to track and enhance wellness with confidence. |
| Keywords: | Mental health, Machine learning, Personalized monitoring, Wearable devices, Recommendation system, Artificial Intelligence (AI) in healthcare, Behavioural analysis |
| Cite Article: | "Machine Learning Based Personalised Mental Health Monitoring and Recommendation for Better Life", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.c634-c641, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505274.pdf |
| Downloads: | 000407 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505274
Registration ID:204179
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: c634-c641 Country: bengaluru, karnataka, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505274 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505274 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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