Real-time ECG monitoring and arrhythmia detection using Android-based 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.
Digital Sports Group, Pattern Recognition Lab, Computer Science Department, Friedrich-Alexander University of Erlangen-Nuremberg, Germany.
Stefan
S
Gradl
Patrick
P
Kugler
Clemens
C
Lohmuller
Bjoern
B
Eskofier
D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D040421:Cell Phone; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted