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Authors: Jérôme Van Zaen ; Olivier Chételat ; Mathieu Lemay ; Enric Calvo and Ricard Delgado-Gonzalo

Affiliation: Swiss Center for Electronics and Microtechnology (CSEM), Rue Jaquet-Droz 1, Neuchâtel, Switzerland

ISBN: 978-989-758-353-7

Keyword(s): ECG, Cardiac Arrhythmias, Neural Networks, Deep Learning, Wearable Sensors.

Abstract: While most heart arrhythmias are not immediately harmful, they can lead to severe complications. In particular, atrial fibrillation, the most common arrhythmia, is characterized by fast and irregular heart beats and increases the risk of suffering a stroke. To detect such abnormal heart conditions, we propose a system composed of two main parts: a smart vest with two cooperative sensors to collect ECG data and a neural network architecture to classify heart rhythms. The smart vest uses two dry bi-electrodes to record a single lead ECG signal. The biopotential signal is then streamed via a gateway to the cloud where a neural network detects and classifies the heart arrhythmias. We selected an architecture that combines convolutional and recurrent layers. The convolutional layers extract relevant features from sliding windows of ECG and the recurrent layer aggregates them for a final softmax layer that performs the classification. Our neural network achieves an accuracy of 87.50% on the dataset of the challenge of Computing in Cardiology 2017. (More)

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Paper citation in several formats:
Van Zaen, J.; Chételat, O.; Lemay, M.; Calvo, E. and Delgado-Gonzalo, R. (2019). Classification of Cardiac Arrhythmias from Single Lead ECG with a Convolutional Recurrent Neural Network.In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, ISBN 978-989-758-353-7, pages 33-41. DOI: 10.5220/0007347900330041

@conference{biosignals19,
author={Jérôme Van Zaen. and Olivier Chételat. and Mathieu Lemay. and Enric M. Calvo. and Ricard Delgado{-}Gonzalo.},
title={Classification of Cardiac Arrhythmias from Single Lead ECG with a Convolutional Recurrent Neural Network},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS,},
year={2019},
pages={33-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007347900330041},
isbn={978-989-758-353-7},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS,
TI - Classification of Cardiac Arrhythmias from Single Lead ECG with a Convolutional Recurrent Neural Network
SN - 978-989-758-353-7
AU - Van Zaen, J.
AU - Chételat, O.
AU - Lemay, M.
AU - Calvo, E.
AU - Delgado-Gonzalo, R.
PY - 2019
SP - 33
EP - 41
DO - 10.5220/0007347900330041

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