Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach

Subasi PhD., Abdulhamit

ISBN 10: 0128174447 / ISBN 13: 9780128174449

Published by Academic Press, 2019

About this Item

Fast & Free Shipping â Good condition with a solid cover and clean pages. Shows normal signs of use such as light wear or a few marks highlighting, but overall a well-maintained copy ready to enjoy. Supplemental items like CDs or access codes may not be included.

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Bibliographic Details

• Title: Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach
• Publisher: Academic Press
• Publication Date: 2019
• Language: English
• ISBN 10: 0128174447
• ISBN 13: 9780128174449
• Binding: Soft cover
• Condition: good

About this title

Synopsis

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more.

This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.

• Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction
• Explains how to apply machine learning techniques to EEG, ECG and EMG signals
• Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series

About the Author

Abdulhamit Subasi is a highly specialized expert in the fields of Artificial Intelligence, Machine Learning, and Biomedical Signal and Image Processing. His extensive expertise in applying machine learning across diverse domains is evident in his numerous contributions, including the authorship of multiple book chapters, as well as the publication of a substantial body of research in esteemed journals and conferences. His career has spanned various prestigious institutions, including the Georgia Institute of Technology in Georgia, USA, where he served as a dedicated researcher. In recognition of his outstanding research contributions, Subasi received the prestigious Queen Effat Award for Excellence in Research in May 2018. His academic journey includes a tenure as a Professor of computer science at Effat University in Jeddah, Saudi Arabia, from 2015 to 2020. Since 2020, he has assumed the role of Professor of medical physics at the Faculty of Medicine, University of Turku in Turku, Finland