Lightweight Electrocardiogram Signal Quality-Aware VT/VF Detector for Resource-Constrained Life-Threatening Monitoring Devices

Ventricular tachycardia (VT) and ventricular fibrillation (VF) are life threatening arrhythmias which lead to sudden cardiac arrest (SCA).The timely detection of VT and VF is vital, as automated external defibrillators rely on accurate VT/VF identification to deliver life-saving defibrillation and restore normal sinus rhythm during SCA. Continuous monitoring of electrocardiogram (ECG) signals plays a pivotal role in the early detection of VT/VF, potentially reducing mortality associated with SCA. However, the reliability of continuous ECG monitoring is often compromised by various noise sources, necessitating assessment of signal quality to ensure accurate VT/VF detection. This letter presents a real-time signal quality assessment (SQA)-based VT/VF detection method using zero-crossing rate. The SQA-based VT/VF detection method is tested on single and multi-lead datasets. The method is tested on real-time ECG signals collected from subjects with cardiac arrhythmias. Compared to zero crossing rate-based VT/VF detection without SQA, the proposed SQA-based method reduced the false detection rate by up to 7.38 % on a single-lead dataset and 59.22% on lead 1 of a multi-lead dataset. The method, implemented on Arduino Due platform, consumed energy of 5.79 mJ and processing time of 13 ms, validating its real-time feasibility on resource-constrained wearable health monitoring devices.