Interview with Edward Gunning: Functional Data Analysis in Biomechanics
As technology advances at a rapid pace and data collection grows increasingly complex, our ability to capture high-quality, high-frequency data from biomechanical systems has grown significantly. This presents both an opportunity to gain deeper insights into the intricacies of human movement and a challenge to develop robust tools for analyzing and interpreting the resulting data.
Functional Data Analysis (FDA) and human movement have been intrinsically linked since the seminal work of Ramsay. FDA provides a powerful statistical framework that models entire sequences of measurements as single functional entities, opening new pathways for understanding movement dynamics.
Although FDA has gained popularity in the biomechanics community, analyses have largely focused on Functional Principal Component Analysis (FPCA). While FPCA is often useful and serves as a key component in many advanced FDA procedures, it may not be suitable for every scenario.
The purpose of this blog is to spotlight a new book, Functional Data Analysis in Biomechanics: A Concise Review of Core Techniques, Applications, and Emerging Areas, which aims to bridge this gap and extend beyond FPCA-based approaches. By offering accessible guidance and a comprehensive overview of FDA techniques, this book serves as a valuable resource for biomechanics researchers seeking to expand or deepen their understanding of FDA and apply these methods more effectively in their work.
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