Remote monitoring of vital signs: pulse, temperature, and oxygen saturation using cloud computing

Telemedicine has gained significant relevance by allowing patients to be attended to at any time and place, reducing the cost and time of medical care. Therefore, this research aimed at the development of a remote monitoring system for vital signs using cloud computing. Through surveys and expert input, specific system requirements were identified. The chosen sensors, MAX30102 and MLX90614, accurately captured pulse, oxygen saturation, and body temperature. The Arduino Mega-Embedded board facilitated data acquisition, while the Raspberry Pi Zero W enabled remote data transmission. The ThingSpeak platform was used for communication, and the system architecture was established through hardware and software tests. The system’s functionality was verified through expert judgment and statistical tests, showing no significant differences compared to commercial equipment. The remote sampling time for vital sign data was approximately 117 seconds. Overall, this study successfully implemented a robust and efficient remote monitoring system for patients undergoing home treatment.

Authors

Publication Details

Journal
Revista Facultad de Ingeniería Universidad de Antioquia
Published
2024-09-10
DOI
https://doi.org/10.17533/udea.redin.20240941
Citations
1
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.18
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Remote monitoring of vital signs: pulse, temperature, and oxygen saturation using cloud computing

Edgar A. Manzano, Josias N. Rojas, Mauricio Alonso Bejarano Reyes
1 citations
Revista Facultad de Ingeniería Universidad de Antioquia
Non-Invasive Vital Sign Monitoring
0.18
article

Remote monitoring of vital signs: pulse, temperature, and oxygen saturation using cloud computing

Edgar A. Manzano, Josias N. Rojas, Mauricio Alonso Bejarano Reyes
article en
1 citations

Abstract

Telemedicine has gained significant relevance by allowing patients to be attended to at any time and place, reducing the cost and time of medical care. Therefore, this research aimed at the development of a remote monitoring system for vital signs using cloud computing. Through surveys and expert input, specific system requirements were identified. The chosen sensors, MAX30102 and MLX90614, accurately captured pulse, oxygen saturation, and body temperature. The Arduino Mega-Embedded board facilitated data acquisition, while the Raspberry Pi Zero W enabled remote data transmission. The ThingSpeak platform was used for communication, and the system architecture was established through hardware and software tests. The system’s functionality was verified through expert judgment and statistical tests, showing no significant differences compared to commercial equipment. The remote sampling time for vital sign data was approximately 117 seconds. Overall, this study successfully implemented a robust and efficient remote monitoring system for patients undergoing home treatment.

Revista Facultad de Ingeniería Universidad de Antioquia(114)
Openalex Percentile: Top 53%
Non-Invasive Vital Sign Monitoring
0.18
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.