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Frontiers in Physics
We present a fully automatic and fast ECG arrhythmia classifier based on a simple brain-inspired machine learning approach known as Echo State Networks. Our classifier has a low-demanding feature processing that only requires a single ECG lead. Its training and validation follows an inter-patient procedure. Our approach is compatible with an online classification that aligns well with recent advances in health-monitoring wireless devices and wearables. The use of a combination of ensemblesdoi:10.3389/fphy.2019.00103 fatcat:gyxtvpbdlnht7lnbp7qjlsdbge