An adaptive QRS detection algorithm for ultra-long-term ECG recordings.

Malik, John; Soliman, Elsayed Z; Wu, Hau-Tieng

Malik, John; Soliman, Elsayed Z; Wu, Hau-Tieng.

Afiliação

Malik J; Department of Mathematics, Duke University, Durham, NC, USA.
Soliman EZ; Epidemiological Cardiology Research Center (EPICARE), Department of Epidemiology and Prevention, and Department of Medicine, Cardiology Section, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Wu HT; Department of Mathematics, Duke University, Durham, NC, USA; Department of Statistical Science, Duke University, Durham, NC, USA; Mathematics Division, National Center for Theoretical Sciences, Taipei, Taiwan. Electronic address: hauwu@math.duke.edu.

J Electrocardiol ; 60: 165-171, 2020.

Article em En | MEDLINE | ID: mdl-32380280

Assuntos

Eletrocardiografia; Processamento de Sinais Assistido por Computador; Algoritmos; Bases de Dados Factuais; Frequência Cardíaca; Humanos

Palavras-chave

Long-term ECG recording; Physionet; QRS detection

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Sinais Assistido por Computador / Eletrocardiografia Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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