Automated Vital Signs Checker: An Alternative Method of Vital Signs Monitoring for Dialysis Patients at Home

Christopher Y. Basmayor; Lourd Dhinber G. Tangaran; Hyacynth Vianka V. Baylosis; Pearl Joy N. Ornopia; Jerome B. Amor; Rey S. Mabatid

Christopher Y. Basmayor Department of Computer Engineering, University of San Jose-Recoletos, Philippines
Lourd Dhinber G. Tangaran Department of Computer Engineering, University of San Jose-Recoletos, Philippines
Hyacynth Vianka V. Baylosis Department of Computer Engineering, University of San Jose-Recoletos, Philippines
Pearl Joy N. Ornopia Department of Computer Engineering, University of San Jose-Recoletos, Philippines
Jerome B. Amor Department of Computer Engineering, University of San Jose-Recoletos, Philippines http://orcid.org/0009-0003-9759-5417
Rey S. Mabatid Department of Computer Engineering, University of San Jose-Recoletos, Philippines

Abstract

Purpose – This study emphasizes the need to monitor vital signs in dialysis patients and how vital signs can offer crucial information about maintaining blood pressure, assessing heart rate, tracking the body's temperature, and measuring oxygen saturation especially when the dialysis patients are at home.

Method – An alternative vital signs checker system was developed to monitor their health at home conveniently. To obtain precise essential sign measurements, the system utilizes the MLX90614 sensor for body temperature, the MAX30100 sensor for heart rate and oxygen level, and the Sunrom blood pressure module for systolic and diastolic blood pressure readings.

Results – The proposed system exhibits a promising result compared to conventional devices. After conducting 20 tests from 10 different subjects, it demonstrated a temperature sensor accuracy of a percentage error of 2.99% at 1cm, 5.55% at 2 cm, and 6.98% at 3 cm. Moreover, the system achieves a 5.72% percentage error in heart rate measurement, a 1.01% percentage error in measuring oxygen levels, a 5.36% error rate for systolic blood pressure measurement, and a 5.51% error rate for diastolic blood pressure measurement.

Conclusion – With low percentage errors in multiple vital sign measurements, including body temperature, heart rate, oxygen levels, and blood pressure, the system offers reliable and convenient monitoring capabilities.

Recommendations – Several suggestions for future research to ensure the successful design and implementation such as improvement of the user design interface, explore potential machine learning applications, and a language-adaptive user manual.

Research Implications – the successful integration of sensors presents significant implications for continuous and comprehensive monitoring of vital signs, the systems automation reduces the burden of healthcare professionals, improves patient outcomes through early intervention, and enhances healthcare efficiency by providing real-time data for more informed decision-making for healthcare professionals.

Author Biographies

Pearl Joy N. Ornopia, Department of Computer Engineering, University of San Jose-Recoletos, Philippines

Christopher Y. Basmayor, Hyacinth Vianka V. Baylosis, Lourd Dhinber G. Tangaran, and Pearl Joy N. Ornopia are all fourth-year Computer Engineering students at the University of San Jose-Recoletos upon the completion of this thesis.

Rey S. Mabatid, Department of Computer Engineering, University of San Jose-Recoletos, Philippines

Engr. Jerome B. Amor and Engr. Rey S. Mabatid are instructors at the University of San Jose-Recoletos Computer Engineering Department.