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© 2020

Feature Engineering and Computational Intelligence in ECG Monitoring

  • Chengyu Liu
  • Jianqing Li

Benefits

  • 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

Book
  • 3.9k Downloads

Table of contents

  1. Front Matter
    Pages i-x
  2. Introduction

  3. Databases Available for Research

    1. Front Matter
      Pages 11-11
  4. Relevance of Signal Quality

    1. Front Matter
      Pages 31-31
    2. Feifei Liu, Shoushui Wei, Fei Lin, Xinge Jiang, Chengyu Liu
      Pages 33-54
    3. Yixuan Li, Chengyu Liu, Yuwei Zhang, Jianqing Li
      Pages 55-71
    4. Huanqian Zhang, Jianlong Zhao
      Pages 73-88
  5. Latest Techniques for Machine Leaning

    1. Front Matter
      Pages 89-89
    2. Qing Pan, Xinyi Li, Luping Fang
      Pages 91-111
    3. Runnan He, Yang Liu, Henggui Zhang
      Pages 113-141
    4. Wenjie Cai, Danqin Hu
      Pages 143-156
    5. Yaowei Li, Frédéric Precioso, Chengyu Liu
      Pages 157-174
  6. Practical Applications

    1. Front Matter
      Pages 175-175
    2. Caiyun Ma, Shoushui Wei, Chengyu Liu
      Pages 177-195
    3. Xiaotong Dong, Shoushui Wei, Hongru Jiang, Chengyu Liu
      Pages 197-213
    4. Jian Dai, Zehui Sun, Xianliang He
      Pages 215-226
    5. Kejun Dong, Li Zhao, Chengyu Liu
      Pages 227-243

About this book

Introduction

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.

Keywords

Electrocardiogram (ECG) Feature engineering Computational intelligence Machine learning ECG Monitoring

Editors and affiliations

  • Chengyu Liu
    • 1
  • Jianqing Li
    • 2
  1. 1.The State Key Laboratory of Bioelectronics, School of Instrument Science and EngineeringSoutheast UniversityNanjingChina
  2. 2.School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjingChina

About the editors

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.

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