Real-time ECG Monitoring and Arrhythmia Detection Using Android-based Mobile Devices
Overview
Affiliations
We developed an application for Android™-based mobile devices that allows real-time electrocardiogram (ECG) monitoring and automated arrhythmia detection by analyzing ECG parameters. ECG data provided by pre-recorded files or acquired live by accessing a Shimmer™ sensor node via Bluetooth™ can be processed and evaluated. The application is based on the Pan-Tompkins algorithm for QRS-detection and contains further algorithm blocks to detect abnormal heartbeats. The algorithm was validated using the MIT-BIH Arrhythmia and MIT-BIH Supraventricular Arrhythmia databases. More than 99% of all QRS complexes were detected correctly by the algorithm. Overall sensitivity for abnormal beat detection was 89.5% with a specificity of 80.6%. The application is available for download and may be used for real-time ECG-monitoring on mobile devices.
Arora N, Mishra B Healthc Technol Lett. 2023; 10(3):35-52.
PMID: 37265835 PMC: 10230560. DOI: 10.1049/htl2.12043.
Real-Time Heart Arrhythmia Detection Using Apache Spark Structured Streaming.
Ilbeigipour S, Albadvi A, Akhondzadeh Noughabi E J Healthc Eng. 2021; 2021:6624829.
PMID: 33968352 PMC: 8084659. DOI: 10.1155/2021/6624829.
An Improved Real-Time R-Wave Detection Efficient Algorithm in Exercise ECG Signal Analysis.
Zhang Z, Li Z, Li Z J Healthc Eng. 2020; 2020:8868685.
PMID: 32802303 PMC: 7411458. DOI: 10.1155/2020/8868685.
Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis.
De Ridder B, Van Rompaey B, Kampen J, Haine S, Dilles T JMIR Cardio. 2019; 2(1):e4.
PMID: 31758768 PMC: 6834218. DOI: 10.2196/cardio.8802.
Reviewing Mobile Apps to Control Heart Rate in Literature and Virtual Stores.
Garcia J, Gongora Alonso S, Diez I, Garcia-Zapirain B, Castillo C, Coronado M J Med Syst. 2019; 43(4):80.
PMID: 30783824 DOI: 10.1007/s10916-019-1202-z.