One-dimensional statistical parametric mapping in Python

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Pataky, Todd C.¹

One-dimensional statistical parametric mapping in Python

Comput Methods Biomech Biomed Eng. March 2012;15(3):295-301

©2012 Taylor & Francis

Affiliations

¹Department of Bioengineering, Shinshu University, Tokida 3-15-1, Ueda, Nagano, Japan
Abstract and keywords

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/.

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

DOI: 10.1080/10255842.2010.527837

PubMed: 21756121

WoS: 000301596800009
History

Received: 2010-04-25

Revised: 2010-09-25

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