Feature Engineering and Computational Intelligence in ECG Monitoring - Tapa blanda

 
9789811538261: Feature Engineering and Computational Intelligence in ECG Monitoring
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ISBN 10: 9811538263 ISBN 13: 9789811538261
Editorial: Springer, 2021

Sinopsis

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.

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Acerca del autor

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.

De la contraportada

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.

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Editorial
Springer
Año de publicación
2021
Idioma
Inglés
ISBN 10 
9811538263
ISBN 13 
9789811538261
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
280
Editor
Liu Chengyu, Li Jianqing
Contacto del fabricante
Springer Nature Customer Service Center GmbH
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Alemania

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9789811538230: Feature Engineering and Computational Intelligence in ECG Monitoring

Edición Destacada

ISBN 10:  9811538239 ISBN 13:  9789811538230
Editorial: Springer, 2020
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