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@article{165239,
        author = {Priyadarshini and Nagashree and Tanuja and Zakera Tasneem},
        title = {AI Based Stroke Disease Prediction System Using ECG & PPG Bio Signals},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {11},
        number = {1},
        pages = {755-761},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165239},
        abstract = {Over the last few decades, the most common death in worldwide because of cardiovascular disease. It is the unpredictability and random time of the occurrence that makes the disease more dangerous. The death rate will be reduced by regular supervision of clinicians and early detection of cardiac diseases. Unfortunately, people suffering from sudden cardiac arrests have low survival rates. During the COVID-19 pandemic, the personalized patient care is modernized are mostly incorporated in cardiovascular community and clinical applications to achieve medical breakthroughs. The sensors built in textiles, wrist watches, ECG patch recorders and vests patches are targeted at the healthcare professions for the early detection of acute decompensation and improved prognostication. We proposed by which it is used for adaptive fall detection for paralyzed patients/elders and heart stroke prediction. A real-time data of the patient such as blood pressure, body temperature, heart rate and humidity can be monitored and analyzed by System. Our proposed wearable device saves the lives of patient and reduces the death rate by taking immediate care.},
        keywords = {},
        month = {},
        }