A real-time heartbeat monitoring using wearable device and machine learning

Eko Sakti Pramukantoro, Akio Gofuku

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Wearable devices and edge computing enable for self-monitoring of heartbeat conditions. The advantage of self-monitoring is allowing for independent, anywhere, and anytime inspections. Typically, a wearable device on the market comes with a smartphone-based application and is meant for fitness tracking. Moreover, the device's ability to produce a gold standard cardiovascular recording enables the utilization of a sensor to capture cardiovascular data. This research provides a system for real-time monitoring and interpreting RR Interval data from Polar H10 data by using numerous machine learning methods. Therefore, the analyzer was trained to classify data into five categories: normal, supraventricular, ventricular ectopic, fusion, and unknown. The analyzers can predict heartbeats in less than one second, with the decision tree algorithm being the fastest to predict and the support vector machine algorithm is the most accurate.

Original languageEnglish
Title of host publicationLifeTech 2022 - 2022 IEEE 4th Global Conference on Life Sciences and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages270-272
Number of pages3
ISBN (Electronic)9781665419048
DOIs
Publication statusPublished - 2022
Event4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022 - Osaka, Japan
Duration: Mar 7 2022Mar 9 2022

Publication series

NameLifeTech 2022 - 2022 IEEE 4th Global Conference on Life Sciences and Technologies

Conference

Conference4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022
Country/TerritoryJapan
CityOsaka
Period3/7/223/9/22

Keywords

  • arrhythmia
  • CVD
  • edge computing

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Instrumentation
  • Education

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