Automatic Detection of Atrial Fibrillation from Ballistocardiogram (BCG) Using Wavelet Features and Machine Learning

Bin Yu, Biyong Zhang, Lisheng Xu, Peng Fang, Jun Hu

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)

Samenvatting

This paper presents an unobtrusive method for automatic detection of atrial fibrillation (AF) from single-channel ballistocardiogram (BCG) recordings during sleep. We developed a remote data acquisition system that measures BCG signals through an electromechanical-film sensor embedded into a bed's mattress and transmits the BCG data to a remote database on the cloud server. In the feasibility study, 12 AF patients' data were recorded during entire night of sleep. Each BCG recording was split into nonoverlapping 30s epochs labeled either AF or normal. Using the features extracted from stationary wavelet transform of these epochs, three popular machine learning classifiers (support vector machine, K-nearest neighbor, and ensembles) have been trained and evaluated on the set of 7816 epochs employing 30% hold-out validation. The results showed that all the trained classifiers could achieve an accuracy rate above 91.5%. The optimized ensembles model (Bagged Trees) could achieve accuracy, sensitivity, and specificity of 0.944, 0.970 and 0.891, respectively. These results suggest that the proposed BCG-based AF detection can be a potential initial screening and detection tool of AF in home-monitoring applications.

Originele taal-2Engels
Titel2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's4322-4325
Aantal pagina's4
ISBN van elektronische versie9781538613115
DOI's
StatusGepubliceerd - jul 2019
Evenement41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Duitsland
Duur: 23 jul 201927 jul 2019

Congres

Congres41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
LandDuitsland
StadBerlin
Periode23/07/1927/07/19

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