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Framework for Monitoring Peruvian Patients with Hypertension using a Smartwatch and GPT

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Authors
Rosales, Miguel
Huacacolque, Enzo
Castillo-Sequera, Jose Luis
Wong, Lenis
Issue Date
2024-01-01
Keywords
Hypertension, Framework, Blood pressure
Smartwatch, GPT, Blood pressure monitoring

Metadata
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Publisher
IEEE Computer Society
Journal
Conference of Open Innovation Association, FRUCT
URI
http://hdl.handle.net/10757/676107
Abstract
Indexed keywords Sustainable Development Goals SciVal Topics Abstract Hypertension has been a silent disease that has affected a large part of the world population; in 2022, 5.5 million cases were registered in Peru. Current treatments show an inadequate control of this disease. Therefore, a framework is proposed to build an application for remote monitoring of hypertensive patients using technologies such as smartwatches and artificial intelligence of GPT, considering the diagnostic methodologies of hypertension used in the world, physiological variables and the implementation of GPT-4 as an assistant for the correct treatment of hypertension. The methodology was followed: selection of measurement techniques, selection of physiological variables, selection of the smartwatch model, implementation of GPT-4 and construction of a mobile application. The experimentation had two scenarios: (a) use of the traditional model and (b) using the proposed method. The results of the experimentation showed that the time to measure and record blood pressure and heart rate (TMR) was 44.44% faster with the app. The medical diagnosis time (TMD) was 80% more efficient than the traditional method. In addition, in the expert judgment evaluation, patients and cardiologists rated the solution with 4.2 and 4.1 points respectively, valuing it as 'agree' in use of the proposed solution.
Type
info:eu-repo/semantics/article
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
ISSN
23057254
Collections
Seccion en procesamiento

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