Prediction and Detection of Ventricular Fibrillation Using Complex Features and AI-Based Classification
Monica Fira,
Hariton-Nicolae Costin,
Liviu Goras
Abstract:We analyzed the possibility of detecting and predicting ventricular fibrillation (VF), a medical emergency that may put people’s lives at risk, as the medical prognosis depends on the time in which medical personnel intervene. Therefore, besides immediate detection of VF, the possibility of predicting VF 40 or even 50 min in advance was analyzed. For testing the proposed algorithm, we used ECG signals taken from the MIT-BIH database, namely, Malignant Ventricular Ectopy Database, Sudden Cardiac Death Holter Da… Show more
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