Literature DB >> 26577165

HeartSearcher: finds patients with similar arrhythmias based on heartbeat classification.

Juyoung Park1, Kyungtae Kang2.   

Abstract

Long-term electrocardiogram data can be acquired by linking a Holter monitor to a mobile phone. However, most systems of this variety are simply designed to detect arrhythmia through heartbeat classification, and do not provide any additional support for clinical decisions. HeartSearcher identifies patients with similar arrhythmias from heartbeat classifications, by summarising each patient's typical heartbeat pattern in the form of a regular expression, and then ranking patients according to the similarities of their patterns. Results obtained using electrocardiogram data from the MIT-BIH arrhythmia database show that this abstraction reduces the volume of heartbeat classifications by 98% on average, offering great potential to support clinical decisions.

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Year:  2015        PMID: 26577165      PMCID: PMC8687414          DOI: 10.1049/iet-syb.2015.0011

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  13 in total

1.  The impact of the MIT-BIH arrhythmia database.

Authors:  G B Moody; R G Mark
Journal:  IEEE Eng Med Biol Mag       Date:  2001 May-Jun

2.  Support vector machine-based expert system for reliable heartbeat recognition.

Authors:  Stanislaw Osowski; Linh Tran Hoai; Tomasz Markiewicz
Journal:  IEEE Trans Biomed Eng       Date:  2004-04       Impact factor: 4.538

3.  Weighted conditional random fields for supervised interpatient heartbeat classification.

Authors:  Gaël de Lannoy; Damien Francois; Jean Delbeke; Michel Verleysen
Journal:  IEEE Trans Biomed Eng       Date:  2011-10-10       Impact factor: 4.538

4.  Heartbeat classification using feature selection driven by database generalization criteria.

Authors:  Mariano Llamedo; Juan Pablo Martinez
Journal:  IEEE Trans Biomed Eng       Date:  2010-08-19       Impact factor: 4.538

5.  A patient-adapting heartbeat classifier using ECG morphology and heartbeat interval features.

Authors:  Philip de Chazal; Richard B Reilly
Journal:  IEEE Trans Biomed Eng       Date:  2006-12       Impact factor: 4.538

6.  Heartbeat classification using morphological and dynamic features of ECG signals.

Authors:  Can Ye; B V K Vijaya Kumar; Miguel Tavares Coimbra
Journal:  IEEE Trans Biomed Eng       Date:  2012-08-15       Impact factor: 4.538

7.  A patient-adaptive profiling scheme for ECG beat classification.

Authors:  Miad Faezipour; Adnan Saeed; Suma Chandrika Bulusu; Mehrdad Nourani; Hlaing Minn; Lakshman Tamil
Journal:  IEEE Trans Inf Technol Biomed       Date:  2010-09

8.  Real-time classification of ECGs on a PDA.

Authors:  Jimena Rodríguez; Alfredo Goñi; Arantza Illarramendi
Journal:  IEEE Trans Inf Technol Biomed       Date:  2005-03

9.  Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices.

Authors:  Stefan Gradl; Patrick Kugler; Clemens Lohmuller; Bjoern Eskofier
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2012

10.  Management of acute myocardial infarction in patients presenting with persistent ST-segment elevation: the Task Force on the Management of ST-Segment Elevation Acute Myocardial Infarction of the European Society of Cardiology.

Authors:  Frans Van de Werf; Jeroen Bax; Amadeo Betriu; Carina Blomstrom-Lundqvist; Filippo Crea; Volkmar Falk; Gerasimos Filippatos; Keith Fox; Kurt Huber; Adnan Kastrati; Annika Rosengren; P Gabriel Steg; Marco Tubaro; Freek Verheugt; Franz Weidinger; Michael Weis
Journal:  Eur Heart J       Date:  2008-11-12       Impact factor: 29.983

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