Abnormal heart rate detection through real-time heart monitoring application
Health monitoring that requires doctors and patients at the healthcare center may not be practical during the coronavirus disease 2019 (COVID-19) pandemic. Alternatively, mobile health (mHealth) should be embraced to minimize contact between patients and healthcare personnel. This research aims to e...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Institute of Advanced Engineering and Science
2023
|
Subjects: | |
Online Access: | http://eprints.utm.my/105628/1/FizaAbdulRahim2023_AbnormalHeartRateDetectionThroughRealTime.pdf http://eprints.utm.my/105628/ http://dx.doi.org/10.11591/eei.v12i4.4933 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.105628 |
---|---|
record_format |
eprints |
spelling |
my.utm.1056282024-05-06T06:45:07Z http://eprints.utm.my/105628/ Abnormal heart rate detection through real-time heart monitoring application Hashim, Ummi Namirah Salahuddin, Lizawati Hashim, Ummi Rabaah Naim, Mohd. Hariz Raja Ikram, Raja Rina Abdul Rahim, Fiza T Technology (General) Health monitoring that requires doctors and patients at the healthcare center may not be practical during the coronavirus disease 2019 (COVID-19) pandemic. Alternatively, mobile health (mHealth) should be embraced to minimize contact between patients and healthcare personnel. This research aims to enhance the detection of abnormal heart rate (HR) detection by developing a real-time heart rate monitoring (RTHM) application. Sixteen healthy adults participated in a physical real-time HR monitoring testbed. Participants HR was measured for three minutes resting and three minutes performing moderate-intensity physical activity. The results were compared with the polar beat app. Additionally, the energy consumption, the time taken to receive an alarm message, and an acceptance test were analyzed. The app is acceptably accurate, the mean absolute percentage error less than 2%. The response time to receive the alarm message is 30 seconds on average, which is under an acceptable range of medical standards. Moreover, the app is power efficient, 477 mW on average. Participants show a positive attitude towards using RTHM. RTHM is expected to provide a more plausible tool for monitoring the heart towards enhancing abnormal HR detection by promoting patient-oriented healthcare and minimizing sudden deaths due to heart failure. Institute of Advanced Engineering and Science 2023 Article PeerReviewed application/pdf en http://eprints.utm.my/105628/1/FizaAbdulRahim2023_AbnormalHeartRateDetectionThroughRealTime.pdf Hashim, Ummi Namirah and Salahuddin, Lizawati and Hashim, Ummi Rabaah and Naim, Mohd. Hariz and Raja Ikram, Raja Rina and Abdul Rahim, Fiza (2023) Abnormal heart rate detection through real-time heart monitoring application. Bulletin of Electrical Engineering and Informatics, 12 (4). pp. 2495-2505. ISSN 2089-3191 http://dx.doi.org/10.11591/eei.v12i4.4933 DOI : 10.11591/eei.v12i4.4933 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
language |
English |
topic |
T Technology (General) |
spellingShingle |
T Technology (General) Hashim, Ummi Namirah Salahuddin, Lizawati Hashim, Ummi Rabaah Naim, Mohd. Hariz Raja Ikram, Raja Rina Abdul Rahim, Fiza Abnormal heart rate detection through real-time heart monitoring application |
description |
Health monitoring that requires doctors and patients at the healthcare center may not be practical during the coronavirus disease 2019 (COVID-19) pandemic. Alternatively, mobile health (mHealth) should be embraced to minimize contact between patients and healthcare personnel. This research aims to enhance the detection of abnormal heart rate (HR) detection by developing a real-time heart rate monitoring (RTHM) application. Sixteen healthy adults participated in a physical real-time HR monitoring testbed. Participants HR was measured for three minutes resting and three minutes performing moderate-intensity physical activity. The results were compared with the polar beat app. Additionally, the energy consumption, the time taken to receive an alarm message, and an acceptance test were analyzed. The app is acceptably accurate, the mean absolute percentage error less than 2%. The response time to receive the alarm message is 30 seconds on average, which is under an acceptable range of medical standards. Moreover, the app is power efficient, 477 mW on average. Participants show a positive attitude towards using RTHM. RTHM is expected to provide a more plausible tool for monitoring the heart towards enhancing abnormal HR detection by promoting patient-oriented healthcare and minimizing sudden deaths due to heart failure. |
format |
Article |
author |
Hashim, Ummi Namirah Salahuddin, Lizawati Hashim, Ummi Rabaah Naim, Mohd. Hariz Raja Ikram, Raja Rina Abdul Rahim, Fiza |
author_facet |
Hashim, Ummi Namirah Salahuddin, Lizawati Hashim, Ummi Rabaah Naim, Mohd. Hariz Raja Ikram, Raja Rina Abdul Rahim, Fiza |
author_sort |
Hashim, Ummi Namirah |
title |
Abnormal heart rate detection through real-time heart monitoring application |
title_short |
Abnormal heart rate detection through real-time heart monitoring application |
title_full |
Abnormal heart rate detection through real-time heart monitoring application |
title_fullStr |
Abnormal heart rate detection through real-time heart monitoring application |
title_full_unstemmed |
Abnormal heart rate detection through real-time heart monitoring application |
title_sort |
abnormal heart rate detection through real-time heart monitoring application |
publisher |
Institute of Advanced Engineering and Science |
publishDate |
2023 |
url |
http://eprints.utm.my/105628/1/FizaAbdulRahim2023_AbnormalHeartRateDetectionThroughRealTime.pdf http://eprints.utm.my/105628/ http://dx.doi.org/10.11591/eei.v12i4.4933 |
_version_ |
1800082639536783360 |
score |
13.211869 |