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PCA of waveforms and functional PCA: A primer for biomechanics.

Warmenhoven, J, Bargary, N, Liebl, D, Harrison, A, Robinson, MA, Gunning, E and Hooker, G (2020) PCA of waveforms and functional PCA: A primer for biomechanics. Journal of Biomechanics, 116. ISSN 1873-2380

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Abstract

Principal components analysis (PCA) of waveforms and functional PCA (fPCA) are statistical approaches used to explore patterns of variability in biomechanical curve data, with fPCA being an accepted statistical method grounded within the functional data analysis (FDA) statistical framework. This technical note demonstrates that PCA of waveforms is the most rudimentary form of FDA, and consequently can be rationalised within the FDA framework of statistical processes. Mathematical proofing applied demonstrations of both techniques, and an example of when fPCA may be of greater benefit to control over smoothing of functional principal components is provided using an open access motion sickness dataset. Finally, open access software is provided with this paper as means of priming the biomechanics community for using these methods as a part of future functional data explorations.

Item Type: Article
Uncontrolled Keywords: 0903 Biomedical Engineering, 0913 Mechanical Engineering, 1106 Human Movement and Sports Sciences
Subjects: R Medicine > RC Internal medicine > RC1200 Sports Medicine
Divisions: Sport & Exercise Sciences
Publisher: Elsevier
Related URLs:
Date Deposited: 15 Jan 2021 12:12
Last Modified: 15 Jan 2021 12:12
DOI or Identification number: 10.1016/j.jbiomech.2020.110106
URI: https://researchonline.ljmu.ac.uk/id/eprint/14271

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