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@article{169785,
        author = {AKSHARA K and ELIZABETH MARIYA JOSE},
        title = {Wearable Tech In Mental Health: A Comprehensive Review of Monitoring and Machine Learning Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {2562-2572},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169785},
        abstract = {The systematic survey paper "Wearable Tech In Mental Health: A Comprehensive Review of Monitoring and Machine Learning Applications" critically examines the current evolution in the research landscape regarding wearable sensors for detection and management in anxiety, stress, and panic disorders.  Several types of physiological and behavioral data are being evaluated that these devices typically collect, such as heart rate variability, electrodermal activity, sleep, and their efficiency for real-time monitoring and predicting mood or mental health problems. Additionally, the review suggests the application of wearable technology in union with ML models which would improve the precision and generalization of measures across a population related to mental health.The article spans many research gaps, such as the recommended studies that take advantage of larger populations, ethical issues (especially concerning data privacy), etc. It also mentions the importance of efforts on developing larger scale user independent models and clinically relevant explainable AI systems designed to promote usefulness for practitioners in the field. The conclusion is that while the use and intervention of wearable technology has enormous promise for personalized mental health intervention, further work is still necessary to address the challenges indicated with wearable technology in mental health before the potential impact of widespread use can be accomplished.},
        keywords = {Anxiety, Ethical Considerations,  Machine Learning Models, Mental Health, Panic Disorders, Physiological Monitoring,  Privacy, Wearable Technology},
        month = {November},
        }