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Advanced Methods and Tools for ECG Data Analysis.
Here?s a cutting-edge, practical book that offers you a thorough understanding of state-of-the-art techniques for electrocardiogram (ECG) data analysis. Placing emphasis on the selection, modeling, classification, and interpretation of data based on advanced signal processing and artificial intellig...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Norwood :
Artech House,
2006.
|
| Colección: | Engineering in Medicine & Biology.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Clifford, Gari D. | |
| 245 | 1 | 0 | |a Advanced Methods and Tools for ECG Data Analysis. |
| 260 | |a Norwood : |b Artech House, |c 2006. | ||
| 300 | |a 1 online resource (399 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Engineering in Medicine & Biology | |
| 505 | 0 | |a Advanced Methods and Tools for ECG Data Analysis; Contents v; Preface xi; Chapter 1 The Physiological Basis of the Electrocardiogram 1; Chapter 2 ECG Acquisition, Storage, Transmission, and Representation 27; Chapter 3 ECG Statistics, Noise, Artifacts, and Missing Data 55; Chapter 4 Models for ECG and RR Interval Processes 101; Chapter 5 Linear Filtering Methods 135; Chapter 6 Nonlinear Filtering Techniques 171; Chapter 7 The Pathophysiology Guided Assessment of T-Wave Alternans 197; Chapter 8 ECG-Derived Respiratory Frequency Estimation 215; Chapter 9 Introduction to Feature Extraction 245. | |
| 505 | 8 | |a Chapter 10 ST Analysis 269Chapter 11 Probabilistic Approaches to ECG Segmentation and Feature Extraction 291; Chapter 12 Supervised Learning Methods for ECG Classification/Neural Networks and SVM Approaches 319; Chapter 13 An Introduction to Unsupervised Learning for ECG Classification 339; About the Authors 367; Index 371. | |
| 520 | |a Here?s a cutting-edge, practical book that offers you a thorough understanding of state-of-the-art techniques for electrocardiogram (ECG) data analysis. Placing emphasis on the selection, modeling, classification, and interpretation of data based on advanced signal processing and artificial intelligence techniques, the book helps you design, implement, and evaluate software systems used for the analysis of ECG and related data. | ||
| 588 | 0 | |a Print version record. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Electrocardiography |x Data processing. | |
| 650 | 0 | |a Heart |x Diseases |x Diagnosis. | |
| 650 | 6 | |a Électrocardiographie |x Informatique. | |
| 650 | 6 | |a Cœur |x Maladies |x Diagnostic. | |
| 650 | 7 | |a Electrocardiography |x Data processing |2 fast | |
| 650 | 7 | |a Heart |x Diseases |x Diagnosis |2 fast | |
| 758 | |i has work: |a Advanced methods and tools for ECG data analysis (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGDpt7qX9yPR3f4RQDxhVy |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 1 | |z 9781580539661 | |
| 830 | 0 | |a Engineering in Medicine & Biology. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=338739 |z Texto completo |
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