Nonlinear Analysis for Human Movement Variability

Human movement variability can be defined as the typical variations that are present in motor performance and are observed across multiple repetitions of a task. This variability is inherent within all biological systems. It can also be observed easily as it is almost impossible for an individual, even an elite performer, to perform two identical actions of the same task. Nonlinear Analysis for Human Movement Variability, Second edition presents a different approach to studying human movement variability, based on the temporal structure of variability, that is how movement changes over time despite repetitive tasks. Featuring nine new chapters and numerous case studies, this second edition investigates human movement patterns and how these impact our daily lives. The new edition goes beyond the basics, while maintaining a simple and approachable style and having been fully updated with the latest findings from the research, focusing heavily on methodological developments and inclusion of examples from literature. New topics covered include recurrence quantification analysis, multifractal analysis, fractal correlation and regression, and multiscale probability distribution functions plus much more. New MATLAB code and datasets will accompany each chapter to facilitate teaching and learning. The reader will gather a thorough and detailed analysis and evaluation of how to measure human movement variability. This book will be an ideal purchase for any student interested in understanding human movement variability including those in fields such as biomechanics and kinesiology, along with students from biomedical, industrial, and mechanical engineering. Its appeal will extend to ergonomists, clinicians, practitioners, and physiologists too. This title also features PowerPoint slides for instructors to use in their classroom to enhance learning, alongside code and data.

Nikolaos "Nick" Stergiou is the Distinguished Community Research Chair and Professor in Biomechanics at the University of Nebraska at Omaha (UNO), USA, where he also directs the Center for Research in Human Movement Variability. He is the Founding Chair of the first academic Department of Biomechanics offering BS, MS, and PhD degrees. A global authority on Nonlinear Dynamics and human movement variability, he has published over 250 peer-reviewed papers with 17,000+ citations. Dr. Stergiou is a Fellow of multiple prestigious organizations, including the American Association for the Advancement of Science. His research, funded by over $40 million from NIH, NASA, and others, has advanced surgical training and rehabilitation techniques. He spearheaded the creation of the world's first Biomechanics Research Building and its expansion, supported by $17.6 million in private donations, solidifying UNO as a leader in biomechanics research. Aaron D. Likens is an Associate Professor in the Department of Biomechanics and Director of the Quantitative Analysis Research Core at the Center for Research on Human Movement Variability (MOVCENTR) at the University of Nebraska at Omaha, USA. He earned his Ph.D. in Perception, Action, and Cognition from Arizona State University in 2016 and his research focuses on applying nonlinear dynamical systems theory, fractal analysis, and advanced statistical methods to study human movement variability, with applications in gait biomechanics, interpersonal coordination, and military load carriage. Dr. Likens has published over 40 peer-reviewed articles in prestigious journals and secured over $3 million in research funding from NIH, NSF, and the Department of Defense. He has developed innovative methods for analyzing behavioral time series and teaches courses in analytical methods for biomechanics.

1. Introduction. 2. Time Series. 3. State Space Reconstruction. 4. Lyapunov Exponent. 5. An Introduction to Recurrence Quantification Analysis for Movement Scientists. 6. Surrogation. 7. Autocorrelation Function, Mutual Information, and Correlation Dimension. 8. Movement is Rough and Irregular: An Introduction to Fractal Analysis. 9. Multifractal analysis: A window on the nonlinear release/constraint of degrees of freedom. 10. Multiscale probability density function analysis. 11. Fractal Methods of Association. 12. Measuring Complexity: A Guided Tour of Information Focused Univariate Time Series Methods. 13. Time-Frequency Analysis of Human Movement. 14. Symbolic Regression: A Tool for Discovering Equations of Human Movement Dynamics.