A bi-LSTM Neural Network for ECG-based Shockable Arrhythmia Detection

Ventricular fibrillation and tachycardia are two life-threatening cardiac disorders, called shockablearrhythmias. Developing a fast and accurate algorithm for detecting shockable rhythms is very important in realapplications. It could be embedded in AED devices to help patients with out-of-hospital heart attacks. Aneffective bi-LSTM network is introduced in this paper for the detection of shockable rhythms

کلیدواژه ها:

ECG (Electrocardiography) ، Shockable Rhythms ، Deep neural networks ، bi-LSTM ، VentricularFibrillation ، Ventricular Tachycardia