One-dimensional statistical parametric mapping in Python

  • Pataky T
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Abstract

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/.

Author-supplied keywords

  • Ground reaction force
  • Kinematic trajectory analysis
  • Objectoriented programming
  • Open-source software
  • Probabilistic finite element modelling
  • Topological statistics

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Authors

  • Todd C. Pataky

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