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Heart Rate Monitoring System using Max30102 Sensor and Gaussian Naive Bayes Algorithm

by Beni Mustiko Aji, Wahyu Sri Utami
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 47
Year of Publication: 2023
Authors: Beni Mustiko Aji, Wahyu Sri Utami
10.5120/ijca2023923249

Beni Mustiko Aji, Wahyu Sri Utami . Heart Rate Monitoring System using Max30102 Sensor and Gaussian Naive Bayes Algorithm. International Journal of Computer Applications. 185, 47 ( Dec 2023), 7-12. DOI=10.5120/ijca2023923249

@article{ 10.5120/ijca2023923249,
author = { Beni Mustiko Aji, Wahyu Sri Utami },
title = { Heart Rate Monitoring System using Max30102 Sensor and Gaussian Naive Bayes Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2023 },
volume = { 185 },
number = { 47 },
month = { Dec },
year = { 2023 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number47/33004-2023923249/ },
doi = { 10.5120/ijca2023923249 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:29:04.433130+05:30
%A Beni Mustiko Aji
%A Wahyu Sri Utami
%T Heart Rate Monitoring System using Max30102 Sensor and Gaussian Naive Bayes Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 47
%P 7-12
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Heart health is a crucial aspect for the elderly, as it is the leading cause of death in Indonesia. However, the elderly often do not receive sufficient monitoring on a regular basis at Ngudi Makmur Integrated Health Post. Therefore, a solution is proposed to overcome this problem by introducing a heart rate monitoring system using Max30102 sensor and Gaussian Naive Bayes algorithm. The system is designed to monitor the heart rate and display the heart health condition based on the average of the measurements taken. The calibration results of the device used showed an accuracy rate of 95.8%, while testing the Gaussian Naive Bayes algorithm with the k-fold cross-validation method resulted in an accuracy of 91%. The envisioned system aims to enhance the motivation of elderly individuals at Posyandu Ngudi Makmur, encouraging them to consistently undergo routine heart health checks.

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Index Terms

Computer Science
Information Sciences

Keywords

Gaussian Naive Bayes Heart Rate Max30102 Sensor Monitoring.

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