Overview
- Focuses on the traditional and advanced signal processing methods for knee joint vibroarthrography
- Describes a number of effective computer-aided methods for the analysis of nonlinear and nonstationary biomedical signals
- Introduces a number of the latest advances in machine learning and pattern recognition techniques for biomedical signal classification
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Bioengineering (BRIEFSBIOENG)
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Table of contents (5 chapters)
Keywords
About this book
This book presents the cutting-edge technologies of knee joint vibroarthrographic signal analysis for the screening and detection of knee joint injuries. It describes a number of effective computer-aided methods for analysis of the nonlinear and nonstationary biomedical signals generated by complex physiological mechanics. This book also introduces several popular machine learning and pattern recognition algorithms for biomedical signal classifications. The book is well-suited for all researchers looking to better understand knee joint biomechanics and the advanced technology for vibration arthrometry.
Dr. Yunfeng Wu is an Associate Professor at the School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China.
Authors and Affiliations
Bibliographic Information
Book Title: Knee Joint Vibroarthrographic Signal Processing and Analysis
Authors: Yunfeng Wu
Series Title: SpringerBriefs in Bioengineering
DOI: https://doi.org/10.1007/978-3-662-44284-5
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2015
Softcover ISBN: 978-3-662-44283-8Published: 19 February 2015
eBook ISBN: 978-3-662-44284-5Published: 29 January 2015
Series ISSN: 2193-097X
Series E-ISSN: 2193-0988
Edition Number: 1
Number of Pages: XIV, 81
Number of Illustrations: 15 b/w illustrations, 17 illustrations in colour
Topics: Biomedical Engineering and Bioengineering, Rehabilitation Medicine, Signal, Image and Speech Processing, Pattern Recognition