Innovative Analyses of Human Movement is conveniently divided into three parts: the mathematics and statistics applied to variability in human movements, dynamical systems methods and directional circular statistics as applied to coordination in human movements, and the analysis of complex data sets. Each of the nine chapters is well organized and provides sample data sets and examples of how to use and apply the techniques. Contributors from all over the world provide knowledge about human movement.
The text includes complete, step-by-step examples that illustrate how each
technique applies to data analysis. It also presents techniques using a tutorial
approach to prepare readers for real-life research studies. Many other features
make this an easy-to-use tool for human movement scientists:
• Key terms are highlighted in the text and defined in a glossary for quick understanding.
• Work problems allow you to test your skills in using and solving the described technique.
• Suggested readings and resources listed for each chapter point you to additional background information.
• Web sites point readers to relevant software and information.
In addition, the book uses a case study approach that will help readers quickly associate the method of interest with the appropriate application. If you’re a student or professional who deals with measurement issues in human movement, this resource is a must.
About the Editor
Nicholas Stergiou, PhD, is associate professor and coordinator of the HPER Biomechanics Laboratory at the University of Nebraska at Omaha. He has contributed chapters in two exercise science books and has published extensively in many prestigious journals in the field. Stergiou is a member of the American Society of Biomechanics and the International Society of Biomechanics. He earned a PhD in biomechanics from the University of Oregon, a master’s degree in exercise science and biomechanics from the University of Nebraska at Omaha, and a bachelor’s degree in physical education from Aristotle University, Thessaloniki, Greece. Stergiou and his wife, Ann, reside in Omaha and enjoy playing sports and traveling in their spare time.
Table of Contents
List of Contributors
Part I Methods to Examine Variability in Human Movement
- Chapter 1 Single-Subject Analysis
Expanding Experimental Design Horizons
Human Movement Characteristics
Issues Relative to Data Analysis and Evaluation
- Chapter 2 Considerations of Movement Variability in Biomechanics Research
The Nature of Intra-Individual Movement Variability
Variability and Biological Health
Methodological Considerations of Movement Variability
Traditional Methods for Quantifying Variability
- Chapter 3 Nonlinear Tools in Human Movement
Other Available Software and Algorithms
Part II Methods to Examine Coordination and Stability in Human Movement
- Chapter 4 Applied Dynamic Systems Theory for the Analysis of Movement
Phase Portraits and Phase Angles
Point Estimate Relative Phase
Discrete Relative Phase
Complete Examples for the Application of Dynamical Systems Theory Tools
- Chapter 5 Directional Statistics
Why Are Directional Statistics Needed?
Examples of Directional Statistics
Representation of Circular and Axial Data
Tests of Uniformity
Comparisons of Two or More Samples
Hypothesis Testing for Second-Order Analysis
List of Symbols
- Chapter 6 Mathematical Measures of Coordination and Variability in Gait
Response Surface Methodology
Part III Advanced Methods for Data Analysis in Human Movement
- Chapter 7 Time Series Analysis: The Cross-Correlation Function
Time Series Analyses
Defining the Cross-Correlation Function
Pearson Product-Moment Correlations
Other Measures of Similarity
Cross-Correlation as a Method for Estimating Spectral Content
- Chapter 8 Principles and Applications of Bootstrapping Statistical Analysis
Bootstrap Samples and Bootstrap Sampling Distributions
How Bootstrapping Works
Practical Issues of Bootstrapping Applications
Advantages and Limitations of Bootstrapping
- Chapter 9 Power Spectrum Analysis and Filtering
Time and Frequency Domain Representations: A Simple Signal
Frequency Domain Transform and the Discrete Fourier Transform
Biomechanical Data Filtering
The Differentiation Process
Joint Time-Frequency Domain Representations
The Wigner Function
Appendix A Answers to Work Problems
Appendix B Data Sets for Chapter 2
Appendix C Data Sets for Chapter 4 Work Problems
About the Editor
A resource for biomechanists, motor behavior and control specialists, rehab medicine researchers, biomedical researchers, sports medicine researchers, and ergonomists; a textbook for undergraduate and graduate biomechanics and motor behavior and motor control students.