In Biomechanics, as in other areas of knowledge, it is usual to analyze data that change over time. Despite the temporal nature of these data, a substantial part of the current investigation still uses the analysis of means and standard deviations of specific curve parameters.
This approach, despite its merit, when applied to the analysis of time series, may lead to the loss of relevant information associated with the general behavior of the curves. Fortunately, alternatives already exist, namely the Statistical Parametric Mapping.
Statistical Parametric Mapping (SPM) is a technique that allows statistical analysis of data that change over time, like most of human movement data (e.g. angles, forces velocities).
The SPM extends the application of traditionally used statistical tests (ANOVA t-tests and linear regressions) on discrete variables to curves that change over time, such as those found in kinematics or kinetics.
Anyone can use the procedures inherent to the SPM as long as they learn the fundamental principles that support the selected statistical technique and apply that knowledge through simple tools. For further details please see the video of this link.
We hope you will be able to attend,
By the Organizing Committee
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