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- W3048693078 abstract "The continuous health monitoring for the elderly is a critical issue that may lead to saving people nowadays. The physiological signal of the human body can be measured using the Internet of Things (IoT) devices that are attached to the human body. We proposed a wearable IoT devices that attached to a patient cloth that has contact with body skin directly, and then this device will continuously send a signal to the server and recorded in database wirelessly. The apps will pull the data continuously and provide a generic chart as a symbol of physical signal condition of the patients either they are in a normal state or emergency state. The data set is preselected only for elderly with age more than 60. Also, the deep learning analysis has proven to be useful for giving a wearable IOT device towards heart failure/disease with 76% accuracy. This percentage might be improved further in the future works with a more suitable data set. The decision of deep learning analysis used either notifies or does not notify the relative according to the elderly condition. It will be compared with historical data of the patient to see abnormalities and then provide a decision either the status emergency, cautionary or just regular symptom. In a case of the emergency state, the apps can send alert to nearby relative/family or medical staff to give first aid. The proposed system will enable both patient and their family to remain mobile and live in less worry due to the smart health monitoring system." @default.
- W3048693078 created "2020-08-18" @default.
- W3048693078 creator A5000541391 @default.
- W3048693078 date "2020-01-01" @default.
- W3048693078 modified "2023-09-26" @default.
- W3048693078 title "Intelligent Wearable IOT Continuous Monitoring System for Elderly Based on Deep Learning Algorithm" @default.
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- W3048693078 doi "https://doi.org/10.1007/978-3-030-42934-8_15" @default.
- W3048693078 hasPublicationYear "2020" @default.
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