Multi-stage SVM approach for cardiac arrhythmias detection in short single-lead ECG recorded by a wearable device.

Journal: Physiological measurement

PMID: 30102239

Abstract

OBJECTIVE: Use of wearable ECG devices for arrhythmia screening is limited due to poor signal quality, small number of leads and short records, leading to incorrect recognition of pathological events. This paper introduces a novel approach to classification (normal/'N', atrial fibrillation/'A', other/'O', and noisy/'P') of short single-lead ECGs recorded by wearable devices.

Authors

Radovan Smisek

Faculty of Electrical Engineering and Communication, Department of Biomedical Engineering, Brno University of Technology, Technická 12, 616 00 Brno, Czechia. Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czechia. Author to whom any correspondence should be addressed.
Jakub Hejc
Marina Ronzhina
Andrea Nemcova
Lucie Marsanova
Jana Kolarova
Lukas Smital
Martin Vitek

Keywords

Atrial Fibrillation Decision Trees Electrocardiography Heart Rate Determination Humans Multilevel Analysis Reproducibility of Results Support Vector Machine Wavelet Analysis Wearable Electronic Devices

External Resources

View on PubMed Access via DOI PubMed (30102239)

Multi-stage SVM approach for cardiac arrhythmias detection in short single-lead ECG recorded by a wearable device.

Abstract

Authors

Keywords

External Resources

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