Publication – Call for ChaptersThe book with Springer Nature entitled Feature Engineering and Computational Intelligence in ECG Monitoring calls for chapters.
The purpose of this book is to summarize the feature engineering and computational intelligence solutions for ECG monitoring, with an emphasis on how these methods can be efficiently used on the emerging need and challenge -- dynamic, continuous & long-term individual ECG monitoring and real-time feedback, aiming to provide a “snapshot” of the state of current research at the interface between physiological signal analysis and machine learning. It could help clarify some dilemmas and encourage further investigations in this field, to explore rational applications of feature engineering and computational intelligence in clinical practices for ECG monitoring.
Original, high quality contributions that are not yet published or that are not currently under review by other journals or peer-reviewed conferences are welcomed, with special emphasis on, but not limited to, a number of correlative chapter topics.
Click Book Proposal for more details.
If you use the Challenge data for paper publication, please cite this paper for Challenge data description:
H. X. Gao, C. Y. Liu∗, X. Y. Wang, L. N. Zhao, Q. Shen, E. Y. K. Ng, and J. Q. Li. An Open-Access ECG Database for Algorithm Evaluation of QRS Detection and Heart Rate Estimation. Journal of Medical Imaging and Health Informatics, 2019, 9(9): 1853–1858.