9783330334601 - Some Methods for ECG Signal Analysis for Arrhythmia Detection di Vallem, Sharmila; Komalla, Ashoka Reddy (6 risultati)

Taschenbuch. Condizione: Neu. Some Methods for ECG Signal Analysis for Arrhythmia Detection | Sharmila Vallem (u. a.) | Taschenbuch | 140 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330334601 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Taschenbuch. Condizione: 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.

Condizione: 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.

Taschenbuch. Condizione: 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.

Taschenbuch. Condizione: 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.