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Online workshop: Statistical Parametric Mapping in Biomechanics

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  • Online workshop: Statistical Parametric Mapping in Biomechanics

    Online workshop (paid course): Basic principles Statistical Parametric Mapping in Biomechanics

    Statistical Parametric Mapping (SPM) is an analysis technique that allows the statistical analysis of continuous biomechanical data including 1D force and kinematic curves, mitigating biases associated with subjective analysis decisions. It works very similar to the basic statistical analyses we all know, such as t-tests, ANOVA, and linear regression, but it extends these to one-dimensional data analysis. Anyone can use it with a little bit of training, which requires one to learn the key principles that underpin the technique, and then apply these principles using a relatively easy software interface. COVID-19 has made it impossible to organise face to face workshops as we have done during past years. Therefore we have developed an online self-paced learning environment in which the same materials are covered as would be in a two-day workshop.

    Online training description
    Through recorded expert presentations you will learn to understand the key concepts underpinning SPM. Through worksheets you will conduct basic SPM analyses in Matlab (Matlab licence not provided with the course!) and learn how to present these. Through brief self-evaluation tests you will gain valuable feedback on how you are progressing through the sessions. Estimated time to complete the entire workshop is 30-40 hours. Whilst in the future in-person workshops will still be organised as before (see, this online version facilitates rapid and self-regulated workshop completion from anywhere in the world at any time.

    See introductory video.

    Topics covered as part of the training
    • Principles of probability and Random Field Theory
    • Running a t-test using SPM
    • Linear regression using SPM
    • ANOVA using SPM

    Todd C. Pataky, Mark A. Robinson and Jos Vanrenterghem.

    Further information (registrations available from Friday 17th September 2021):