4.3 Article

One-dimensional statistical parametric mapping in Python

Journal

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/10255842.2010.527837

Keywords

topological statistics; ground reaction force; kinematic trajectory analysis; open-source software; object-oriented programming; probabilistic finite element modelling

Funding

  1. Japanese Ministry of Education, Culture, Sports, Science and Technology
  2. Natural Environment Research Council [NE/H004246/1] Funding Source: researchfish
  3. NERC [NE/H004246/1] Funding Source: UKRI

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Statistical parametric mapping (SPM) is a topological methodology for detecting field changes in smooth n-dimensional continua. Many classes of biomechanical data are smooth and contained within discrete bounds and as such are well suited to SPM analyses. The current paper accompanies release of 'SPM1D', a free and open-source Python package for conducting SPM analyses on a set of registered 1D curves. Three example applications are presented: (i) kinematics, (ii) ground reaction forces and (iii) contact pressure distribution in probabilistic finite element modelling. In addition to offering a high-level interface to a variety of common statistical tests like t tests, regression and ANOVA, SPM1D also emphasises fundamental concepts of SPM theory through stand-alone example scripts. Source code and documentation are available at: www.tpataky.net/spm1d/.

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