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A Web and Mobile Applications for Self-control of Patient Blood Pressure Through Mobiles and Biometrics Devices

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Ubiquitous Computing and Ambient Intelligence (UCAmI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10586))

Abstract

In this article, we want to present a platform that allows the integration of different applications for the follow-up of patients with chronic diseases. We are developing two elements: the first one, is a mobile application that allows the capture and processing of vital sign for patient with high blood pressure (hypertension). This application allows to store the patient data obtained, the show historical and trends of the stored measures, a list of foods to consume, alerts and recommendations according to ranges of measures obtained. The second one, is a web application, this application allows the doctor and patients relatives to have updated information of the disease behavior through the measures obtained, food consumed, and others. Through this web application, we can also generate statistics about average measures in a given time, by age, by region, by specific date.

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References

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Acknowledgments

The first author is member of the National Research Investigator award (SNI) from the SENACYT as a National Research. This article is presented as part of a project ITE15-001 financed by SENACYT and development by Technological University of Panama, Columbus University and Universidad Cooperativa de Colombia.

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Correspondence to Vladimir Villarreal .

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Villarreal, V., Nielsen, M., Samudio, M. (2017). A Web and Mobile Applications for Self-control of Patient Blood Pressure Through Mobiles and Biometrics Devices. In: Ochoa, S., Singh, P., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2017. Lecture Notes in Computer Science(), vol 10586. Springer, Cham. https://doi.org/10.1007/978-3-319-67585-5_25

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  • DOI: https://doi.org/10.1007/978-3-319-67585-5_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67584-8

  • Online ISBN: 978-3-319-67585-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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