Publication:
A Mobile Application to Predict and Manage High Blood Pressure and Personalized Recommendations

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Article

Date

2019-12-05

Authors

Rajapaksha, S. K
Abhayarathne, W. J. A
Kumari, S. G. K
De Silva, M. V. L. U
Wijesuriya, W. M. S. M

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IEEE

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Abstract

The purpose of this investigation is to present a mobile application using AI expert and how to predict and manage high blood pressure and provide personalized recommendations to lower it. Basically, the system interprets the inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to the diversity of food components and a large number of dietary sources, it is challenging to perform a real-time selection of diet patterns that must fulfill one's nutrition needs and with considering your health issues and diseases. In this research, to address this issue to present an android based system, called Smart Blood Pressure Recommendation app. The purpose of this system is to allow patients to have an easy way to monitor their health and to see how their blood pressure has changed over time. This offer advice or suggestions, without having to schedule an appointment. As the system continues to gather data from a patient, it begins to offer advice its own if it finds that the patient's current conditions fit a certain condition or pattern. To generate a recommendation, it refers to an Ontology based data model. The data model gains information about its knowledge by doctors and nutritionists that can be used by AI expert. This research helps users to identify their previous record charts of blood pressure, reliable alarms for user blood pressure medication, popup notifications, build health diary and also share log data processing through the AI expert.

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Keywords

Mobile Application, Predict, Manage High Blood Pressure, Personalized, Recommendations

Citation

S. Rajapaksha, W. J. A. Abhayarathne, S. G. K. Kumari, M. V. L. U. De Silva and W. M. S. M. Wijesuriya, "A Mobile Application to Predict and Manage High Blood Pressure and Personalized Recommendations," 2019 International Conference on Advancements in Computing (ICAC), 2019, pp. 422-426, doi: 10.1109/ICAC49085.2019.9103337.

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