Knee Joint Vibroarthrographic Signal Processing and Analysis

verfasst von: Yunfeng Wu

Verlag: Springer Berlin Heidelberg

Buchreihe : SpringerBriefs in Bioengineering

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

This chapter describes the knee joint anatomy in the human body, along with its biomechanical behaviors. The text presents the structures of femoropatellar, medial and lateral femorotibial articulations. The chapter also provides an overview of different types of knee joint disorders and the related medical diagnosis methods.

Yunfeng Wu

Chapter 2. Signal Acquisition and Preprocessing

Abstract

This chapter describes the detailed settings of the knee joint vibroarthrographic signal acquisition system. The text also presents a cascade moving average filter method to estimate the baseline wander in the raw signal, along with the combination of the ensemble empirical mode decomposition and detrended fluctuation analysis algorithms to remove the random noise. The filtering techniques for reduction of muscle contraction interference are also reviewed in the chapter.

Yunfeng Wu

Chapter 3. Signal Analysis

Abstract

This chapter provides an overview of the knee joint vibroarthrographic signal analysis methods, including the spatiotemporal analysis, time-frequency analysis, and statistical analysis. The spatiotemporal analysis concentrates on the morphological description of waveform complexity and the detection of physiological or pathological events in the time scale. The time-frequency analysis investigates the time-varying spectral contents in the signal. The statistical analysis focuses on the statistical characteristics and nonlinear dynamics of the nonstationary VAG signal.

Yunfeng Wu

Chapter 4. Feature Computing and Signal Classifications

Abstract

In this chapter, we describe the feature computing and pattern analysis methods for VAG signal classifications. The purpose of feature selection is to study the feature correlations and then exclude the redundant features before pattern classifications. The reduction of feature dimensions may avoid excessive computation expenses, such that the pattern analysis methods based on the most informative features can also achieve favorable classification results. The signal classification methods include Fisher’s linear discriminant analysis, radial basis function network, Vapnik and least-squares support vector machines, Bayesian decision rule, and multiple classifier fusion systems. The text also presents the common diagnostic performance techniques such as cross-validation, confusion matrix, and receiver operating characteristic curves. Finally, we review the state-of-the-art methods for the VAG signal classifications and compare the results reported in recent literature.

Yunfeng Wu

Chapter 5. Summary and Research Directions

Abstract

This chapter reviews the cutting-edge biomedical technologies for knee joint pathology diagnosis, and summarizes the major developments of knee joint vibroarthrographic signal analysis. The future research topics are also discussed in the conclusive text.

Yunfeng Wu

Titel: Knee Joint Vibroarthrographic Signal Processing and Analysis
verfasst von: Yunfeng Wu
Verlag: Springer Berlin Heidelberg
Electronic ISBN: 978-3-662-44284-5
Print ISBN: 978-3-662-44283-8
DOI: https://doi.org/10.1007/978-3-662-44284-5