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One-dimensional statistical parametric mapping in Python

Comput Methods Biomech Biomed Engin. 2012;15(3):295-301. doi: 10.1080/10255842.2010.527837. Epub 2011 Jul 14.

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/.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Data Interpretation, Statistical*
  • Humans
  • Models, Biological*
  • Models, Statistical*
  • Programming Languages*
  • Software*
  • User-Computer Interface*