Textbook in PDF format

This book provides a concise discussion of fundamental functional data analysis (FDA) techniques for analysing biomechanical data, along with an up-to-date review of their applications. The core of the book covers smoothing, registration, visualisation, functional principal components analysis and functional regression, framed in the context of the challenges posed by biomechanical data and accompanied by an extensive case study and reproducible examples using R. This book proposes future directions based on recently published methodological advancements in FDA and emerging sources of data in biomechanics. This is a vibrant research area, at the intersection of applied statistics, or more generally, data science, and biomechanics and human movement research. This book serves as both a contextual literature review of FDA applications in biomechanics and as an introduction to FDA techniques for applied researchers. In particular, it provides a valuable resource for biomechanics researchers seeking to broaden or deepen their FDA knowledge.
Preface
Acknowledgements
Introduction
Preparing Biomechanical Data for Functional Data Analysis
Exploring Variation in Biomechanical Data
Functional Regression Models in Biomechanics
Case Study: The GaitRec Data
Future Directions of FDA in Biomechanics