Performance Evaluation of IoT-based SpO2 Monitoring Systems for COVID-19 Patients

  • Trie Maya Kadarina Universitas Mercu Buana
  • Rinto Priambodo
DOI: https://doi.org/10.35882/jeeemi.v3i2.1
Keywords: IoT; SpO2; Monitoring System; COVID-19

Abstract

Internet of Things (IoT) applications can be used in healthcare services to monitor patients remotely. One implementation is that it is used to monitor COVID-19 patients. During the COVID-19 pandemic, people who are infected without symptoms must self-isolate so that the virus does not spread. Measurement of blood oxygen levels or SpO2 is one of the measurements that must be carried out in routine examination procedures for self-isolating patients for early detection of silent hypoxemia in COVID-19 patients. Previous research has developed an IoT-based health monitoring system with a Wireless Body Sensor Network (WBSN) and a gateway that can be used for data acquisition and transmission. The system uses a home pulse oximeter to measure SpO2 and heart rate and an Android application that functions as an IoT gateway to collect data from sensors and add location information before sending data to the server. The WBSN has been successfully integrated with two types of open source IoT platforms, namely ThingsBoard and Elasticsearch Logstash Kibana (ELK). However, it is necessary to carry out further studies on analytical and experimental performance tests of the two systems. Therefore, the purpose of this study is to develop a performance evaluation of the IoT-based SpO2 monitoring systems using the Thingsboard and ELK as IoT platforms. To evaluate the performace we ran the monitoring system on both platforms using pulse oximeter and Android device as IoT gateway with HTTP and MQTT as transport protocol for sending the data to the server. From this study we found that average time of message delivery in ELK compared to ThingsBoard using the same protocols was higher but stable.

Downloads

Download data is not yet available.

References

C. Sandeepa, C. Moremada, N. Dissanayaka, T. Gamage, and M. Liyanage, "Social Interaction Tracking and Patient Prediction System for Potential COVID-19 Patients," 2020, doi: 10.1109/5GWF49715.2020.9221268.

R. P. Singh, M. Javaid, A. Haleem, and R. Suman, "Internet of things (IoT) applications to fight against COVID-19 pandemic," Diabetes Metab. Syndr. Clin. Res. Rev., vol. 14, no. 4, pp. 521–524, Jul. 2020, doi: 10.1016/j.dsx.2020.04.041.

M. Otoom, N. Otoum, M. A. Alzubaidi, Y. Etoom, and R. Banihani, "An IoT-based framework for early identification and monitoring of COVID-19 cases," Biomed. Signal Process. Control, 2020, doi: 10.1016/j.bspc.2020.102149.

R. Jouffroy, D. Jost, and B. Prunet, "Prehospital pulse oximetry: A red flag for early detection of silent hypoxemia in COVID-19 patients," Critical Care. 2020, doi: 10.1186/s13054-020-03036-9.

S. Shah et al., "Novel Use of Home Pulse Oximetry Monitoring in COVID-19 Patients Discharged From the Emergency Department Identifies Need for Hospitalization," Acad. Emerg. Med., 2020, doi: 10.1111/acem.14053.

J. Teo, "Early Detection of Silent Hypoxia in Covid-19 Pneumonia Using Smartphone Pulse Oximetry," Journal of Medical Systems. 2020, doi: 10.1007/s10916-020-01587-6.

A. Adriansyah and A. G. Amrullah, "Design of Health Monitoring Framework Model using oneM2M Standard," Int. J. Electr. Energy Power Syst. Eng., vol. 4, no. 1, pp. 107–112, Feb. 2021, doi: 10.31258/ijeepse.4.1.107-112.

M. Hassanalieragh et al., "Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges," 2015, doi: 10.1109/SCC.2015.47.

T. M. Kadarina and R. Priambodo, "Monitoring heart rate and SpO2 using Thingsboard IoT platform for mother and child preventive healthcare," 2018, doi: 10.1088/1757-899X/453/1/012028.

R. Priambodo and T. M. Kadarina, "Monitoring Self-isolation Patient of COVID-19 with Internet of Things," 2020, doi: 10.1109/Comnetsat50391.2020.9328953.

M. Bajer, "Building an IoT data hub with elasticsearch, Logstash and Kibana," 2017, doi: 10.1109/FiCloudW.2017.101.

N. Shah, D. Willick, and V. Mago, "A framework for social media data analytics using Elasticsearch and Kibana," Wirel. Networks, 2018, doi: 10.1007/s11276-018-01896-2.

A. A. Ismail, H. S. Hamza, and A. M. Kotb, "Performance Evaluation of Open Source IoT Platforms," 2019, doi: 10.1109/GCIoT.2018.8620130.

P. Pierleoni, R. Concetti, A. Belli, and L. Palma, "Amazon, Google and Microsoft Solutions for IoT: Architectures and a Performance Comparison," IEEE Access, 2020, doi: 10.1109/ACCESS.2019.2961511.

P. H. Vilela, J. J. P. C. Rodrigues, P. Solic, K. Saleem, and V. Furtado, "Performance evaluation of a Fog-assisted IoT solution for e-Health applications," Futur. Gener. Comput. Syst., 2019, doi: 10.1016/j.future.2019.02.055.

Published
2021-07-19
How to Cite
[1]
Trie Maya Kadarina and R. Priambodo, “Performance Evaluation of IoT-based SpO2 Monitoring Systems for COVID-19 Patients”, j.electron.electromedical.eng.med.inform, vol. 3, no. 2, pp. 64-71, Jul. 2021.
Issue
Vol 3 No 2 (2021): July
Section
Electronics

Copyright (c) 2021 Trie Maya Kadarina, Rinto Priambodo

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlikel 4.0 International (CC BY-SA 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).