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@article{191741,
        author = {Sonam and Unnati Mudgal},
        title = {AI-Powered Health Monitoring using wearable bands and Its Role in Detecting Body Type, Skin Responses, Allergies & Nutrition Needs},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {87-91},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191741},
        abstract = {Advances in wearable biosensing and artificial intelligence are enabling highly personalized health monitoring in everyday life. This paper proposes an AI-powered smart wearable band capable of continuously analysing body signals while also charging itself using energy harvested from the user. The device integrates modern sensors such as PPG (photoplethysmography), accelerometers, temperature sensors, and electrodermal activity electrodes to measure heart rate variability, motion, skin response, and other physiological signals. A smartphone camera or onboard optical sensor can additionally capture skin images for dermatological assessment. Machine learning algorithms and predictive analytics analyse these data streams to identify patterns related to body type, food sensitivities, allergic reactions, and nutritional needs. What makes the system unique is its energy-harvesting design: thermoelectric generators convert body heat into electrical power using the Seebeck effect, while piezoelectric or triboelectric mechanisms convert mechanical motion—such as walking or wrist movement—into supplementary energy. This self-charging capability reduces reliance on external charging and enables longer, continuous monitoring. As the AI model learns from the user over time, it becomes increasingly personalized, offering early warnings and lifestyle recommendations. The system demonstrates the potential of combining self-powered wearables, biosensing, and artificial intelligence to support preventive and data-driven healthcare.},
        keywords = {Photoplethysmography, accelerometers, electrodermal activity, physiological signals, dermatological assessment, energy harvesting, Seebeck effect.},
        month = {},
        }