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Feature Engineering and Computational Intelligence in ECG Monitoring

Editors: Liu, Chengyu, Li, Jianqing (Eds.)

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  • Includes a wealth of research on feature engineering and computational intelligence solutions for ECG monitoring
  • Furthers our understanding of the interface between physiological signal analysis and machine learning
  • Inspires further research on rational applications of feature engineering and computational intelligence in ECG monitoring
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eBook $139.00
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  • ISBN 978-981-15-3824-7
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Hardcover $179.99
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  • ISBN 978-981-15-3823-0
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About this book

This book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these methods can be efficiently used to address the emerging challenges of dynamic, continuous & long-term individual ECG monitoring and real-time feedback. By doing so, it provides a “snapshot” of the current research at the interface between physiological signal analysis and machine learning. It also helps clarify a number of dilemmas and encourages further investigations in this field, to explore rational applications of feature engineering and computational intelligence in ECG monitoring. The book is intended for researchers and graduate students in the field of biomedical engineering, ECG signal processing, and intelligent healthcare.

About the authors

Dr. Chengyu Liu received his B.S. and Ph.D. degrees in Biomedical Engineering from Shandong University, China, in 2005 and 2010 respectively. He completed his postdoctoral training at Shandong University, China; Newcastle University, UK; and Emory University, USA. He is currently the Interim Dean of the School of Instrument Science and Engineering at Southeast University, a Professor of the State Key Laboratory of Bioelectronics, and the founding Director of the Wearable Heart-Sleep-Emotion Intelligent Monitoring Lab at Southeast University. He is also the founding Chair of the China Physiological Signal Challenge (from 2018), which focuses on challenging ECG signal processing issues. He is a member of the journal committee of the International Federation for Medical and Biological Engineering (IFMBE), an international advisory board member for Physiological Measurement and the Journal of Medical and Biological Engineering. His research topics include wearable ECG & vital-sign monitoring, machine learning for medical big data, early detection, and device development for cardiovascular diseases. He has published over 180 journal/conference papers. 
Dr. Jianqing Li received his B.S. and M.S. degrees in Automatic Technology, and his Ph.D. degree in Measurement Technology and Instruments from the School of Instrument Science and Engineering, Southeast University, China, in 1986, 1990 and 2000 respectively. He is currently the Vice-President of Nanjing Medical University, a Professor at the School of Biomedical Engineering and Informatics, Nanjing Medical University, and a Professor at the School of Instrument Science and Engineering at Southeast University. He is the founding Director of the Key Laboratory of Clinical Medical Engineering in Nanjing Medical University, and the deputy Director of the Jiangsu Key Lab of Remote Measurement and Control at Southeast University, where he leads the research on medical-industry, cross-innovation cooperation, medical device development and clinical applications. His research topics include wearable medical sensors and signal processing, rehabilitation robot technology, and robot telepresence technology. He has been awarded funding for more than 20 research projects and holds over 20 patents.

Table of contents (15 chapters)

Table of contents (15 chapters)
  • Feature Engineering and Computational Intelligence in ECG Monitoring: An Introduction

    Pages 3-9

    Liu, Chengyu (et al.)

  • Representative Databases for Feature Engineering and Computational Intelligence in ECG Processing

    Pages 13-29

    Gao, Hongxiang (et al.)

  • An Overview of Signal Quality Indices on Dynamic ECG Signal Quality Assessment

    Pages 33-54

    Liu, Feifei (et al.)

  • Signal Quality Features in Dynamic ECGs

    Pages 55-71

    Li, Yixuan (et al.)

  • Motion Artefact Suppression Method for Wearable ECGs

    Pages 73-88

    Zhang, Huanqian (et al.)

Buy this book

eBook $139.00
price for USA in USD
  • ISBN 978-981-15-3824-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA in USD
  • ISBN 978-981-15-3823-0
  • Free shipping for individuals worldwide. COVID-19 shipping restrictions apply.
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Feature Engineering and Computational Intelligence in ECG Monitoring
Editors
  • Chengyu Liu
  • Jianqing Li
Copyright
2020
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-15-3824-7
DOI
10.1007/978-981-15-3824-7
Hardcover ISBN
978-981-15-3823-0
Edition Number
1
Number of Pages
X, 268
Number of Illustrations
24 b/w illustrations, 77 illustrations in colour
Topics

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