Automated Differentiation between Normal Sinus Rhythm, Atrial Tachycardia, Atrial Flutter and Atrial Fibrillation during Electrophysiology

Intracardiac Electrogram (IEGM) are examined during Cardiac Electrophysiology (EP) for detection, differentiation, analysis and treatment of different arrhythmias. The arrhythmia detection involves EP stimulation, observing IEGM response on monitor screens, and manual evaluation of IEGM key features. The process is time consuming and requires high level of expertise of Electro physiologists. During an EP stimulation process, a patient may develop Atrial Fibrillation (AF) and it is important for patient to be taken out of the AF before further proceeding with the procedure. It is required to automate the arrhythmia detection process during an EP study for real time monitoring of the patient condition and safety. In our previous work, successful detection of Atrio-Ventricular Reentrant Tachycardia and Atrio-Ventricular Nodal Re-entry Tachycardia was achieved in time domain. This work has been undertaken to automatically detect the AF as well as differentiate it from Atrial Flutter (AFL), Atrial Tachycardia (AT) and Normal Sinus Rhythm (NSR). In proposed work, non parametric technique has been applied on atrial IEGM signal for estimation of Dominant frequency (DF) to find out atrial activation rate during NSR, AT, AFL and AF. A new spectral parameter, Average Power Spectral Ratio (APSR), has been defined for ensuring reliability of DF for AF detection as well as differentiation of AF from other atrial arrhythmias. The proposed system successfully detects and differentiates between NSR, AT, AFL and AF with an accuracy of 99.52%. The proposed system can also be effectively used for additional therapeutic application by implantable cardioverter defibrillators.