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Sinopsis
The ECG is an electrical manifestation of contractile activity of the heart. Artifacts like 50/60 Hz power line interference, baseline wander and electromyogram will disturb the ECG morphology, making the analysis of ECG difficult.Five signal processing algorithms aimed at enhancement of the ECG data and subsequent arrhythmia detection are presented in this book. They are (1) Multiscale principal component analysis (MSPCA) based algorithm for enhancing the ECG data, (2) Cumulant based autoregressive modeling algorithm for ECG enhancement, (3) Higher order statistics (HOS) for arrhythmia detection, (4) Cumulant based Teager energy operator(TEO) for arrhythmia detection, (5) PVC identification using Discrete cosine transform (DCT)-Teager energy operator (TEO) model. The efficiency of the algorithms, is evaluated in terms of statistical measures like Root mean square error (RMSE), Root mean square deviation (RMSD), Root mean square variance (RMSV) and correlation coefficient. The methods are compared with the existing well-known adaptive filter and Empirical mode decomposition based methods.
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Reseña del editor
The ECG is an electrical manifestation of contractile activity of the heart. Artifacts like 50/60 Hz power line interference, baseline wander and electromyogram will disturb the ECG morphology, making the analysis of ECG difficult.Five signal processing algorithms aimed at enhancement of the ECG data and subsequent arrhythmia detection are presented in this book. They are (1) Multiscale principal component analysis (MSPCA) based algorithm for enhancing the ECG data, (2) Cumulant based autoregressive modeling algorithm for ECG enhancement, (3) Higher order statistics (HOS) for arrhythmia detection, (4) Cumulant based Teager energy operator(TEO) for arrhythmia detection, (5) PVC identification using Discrete cosine transform (DCT)-Teager energy operator (TEO) model. The efficiency of the algorithms, is evaluated in terms of statistical measures like Root mean square error (RMSE), Root mean square deviation (RMSD), Root mean square variance (RMSV) and correlation coefficient. The methods are compared with the existing well-known adaptive filter and Empirical mode decomposition based methods.
Biografía del autor
Dr.Sharmila Vallem received Ph.D degree from JNTU Hyderabad, Telangana, India in 2016. She is a Professor of ECE at Kamala Institute of Technology & Science, Singapur, Karimnagar, India. Dr. Ashoka Reddy Komalla received Ph.D degree from IIT Madras, India in 2008. He is a Professor of ECE at Kakatiya Institute of Technology & Science,Warangal,India
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Some Methods for ECG Signal Analysis for Arrhythmia Detection
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LAP LAMBERT Academic Publishing Jun 2017, 2017
ISBN 10: 3330334606
ISBN 13: 9783330334601
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The ECG is an electrical manifestation of contractile activity of the heart. Artifacts like 50/60 Hz power line interference, baseline wander and electromyogram will disturb the ECG morphology, making the analysis of ECG difficult.Five signal processing algorithms aimed at enhancement of the ECG data and subsequent arrhythmia detection are presented in this book. They are (1) Multiscale principal component analysis (MSPCA) based algorithm for enhancing the ECG data, (2) Cumulant based autoregressive modeling algorithm for ECG enhancement, (3) Higher order statistics (HOS) for arrhythmia detection, (4) Cumulant based Teager energy operator(TEO) for arrhythmia detection, (5) PVC identification using Discrete cosine transform (DCT)-Teager energy operator (TEO) model. The efficiency of the algorithms, is evaluated in terms of statistical measures like Root mean square error (RMSE), Root mean square deviation (RMSD), Root mean square variance (RMSV) and correlation coefficient. The methods are compared with the existing well-known adaptive filter and Empirical mode decomposition based methods. 140 pp. Englisch. Nº de ref. del artículo: 9783330334601
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Some Methods for ECG Signal Analysis for Arrhythmia Detection
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330334606
ISBN 13: 9783330334601
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The ECG is an electrical manifestation of contractile activity of the heart. Artifacts like 50/60 Hz power line interference, baseline wander and electromyogram will disturb the ECG morphology, making the analysis of ECG difficult.Five signal processing algorithms aimed at enhancement of the ECG data and subsequent arrhythmia detection are presented in this book. They are (1) Multiscale principal component analysis (MSPCA) based algorithm for enhancing the ECG data, (2) Cumulant based autoregressive modeling algorithm for ECG enhancement, (3) Higher order statistics (HOS) for arrhythmia detection, (4) Cumulant based Teager energy operator(TEO) for arrhythmia detection, (5) PVC identification using Discrete cosine transform (DCT)-Teager energy operator (TEO) model. The efficiency of the algorithms, is evaluated in terms of statistical measures like Root mean square error (RMSE), Root mean square deviation (RMSD), Root mean square variance (RMSV) and correlation coefficient. The methods are compared with the existing well-known adaptive filter and Empirical mode decomposition based methods. Nº de ref. del artículo: 9783330334601
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Some Methods for ECG Signal Analysis for Arrhythmia Detection
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330334606
ISBN 13: 9783330334601
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vallem SharmilaDr.Sharmila Vallem received Ph.D degree from JNTU Hyderabad, Telangana, India in 2016. She is a Professor of ECE at Kamala Institute of Technology & Science, Singapur, Karimnagar, India. Dr. Ashoka Reddy Komalla receiv. Nº de ref. del artículo: 153339745
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Some Methods for ECG Signal Analysis for Arrhythmia Detection
Publicado por
LAP LAMBERT Academic Publishing Jun 2017, 2017
ISBN 10: 3330334606
ISBN 13: 9783330334601
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Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The ECG is an electrical manifestation of contractile activity of the heart. Artifacts like 50/60 Hz power line interference, baseline wander and electromyogram will disturb the ECG morphology, making the analysis of ECG difficult.Five signal processing algorithms aimed at enhancement of the ECG data and subsequent arrhythmia detection are presented in this book. They are (1) Multiscale principal component analysis (MSPCA) based algorithm for enhancing the ECG data, (2) Cumulant based autoregressive modeling algorithm for ECG enhancement, (3) Higher order statistics (HOS) for arrhythmia detection, (4) Cumulant based Teager energy operator(TEO) for arrhythmia detection, (5) PVC identification using Discrete cosine transform (DCT)-Teager energy operator (TEO) model. The efficiency of the algorithms, is evaluated in terms of statistical measures like Root mean square error (RMSE), Root mean square deviation (RMSD), Root mean square variance (RMSV) and correlation coefficient. The methods are compared with the existing well-known adaptive filter and Empirical mode decomposition based methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch. Nº de ref. del artículo: 9783330334601
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Some Methods for ECG Signal Analysis for Arrhythmia Detection
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330334606
ISBN 13: 9783330334601
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paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Nº de ref. del artículo: ERICA82933303346066
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