An Android-based application for real-time ECG monitoring correctly detected >99% of QRS complexes and identified abnormal heartbeats with 89.5% sensitivity and 80.6% specificity.
Does an Android-based mobile application accurately detect QRS complexes and abnormal heartbeats in ECG data?
An Android-based mobile application demonstrated high accuracy for QRS detection and moderate-to-high sensitivity and specificity for abnormal heartbeat detection, enabling real-time ECG monitoring on mobile devices.
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.
Gradl et al. (Wed,) conducted a other in Arrhythmia. Android-based mobile application for real-time ECG monitoring and automated arrhythmia detection was evaluated on QRS complex detection and abnormal heartbeat detection. An Android-based application for real-time ECG monitoring correctly detected >99% of QRS complexes and identified abnormal heartbeats with 89.5% sensitivity and 80.6% specificity.