====== Tutorial Overview ======

Get more comfortable with all that Sift has to offer by working through the following tutorials.


==== Tutorial Data Files ====

Sift's tutorials use real data sets wherever possible in order to demonstrate realistic scenarios and avoid overly simplistic examples. Download links to the tutorial datasets can be found [[Sift:Tutorials:Tutorial_Files|here]].

==== Getting Started ====

Working through these four tutorials will provide you with an overview of how Sift lets you analyse your motion capture data sets from start to finish.

  * **Tutorial 1: [[Sift:Tutorials:Load_and_View_Data|Load signals into Sift and view them]]**
  * **Tutorial 2: [[Sift:Tutorials:Clean_your_Data|Clean your data]]**
  * **Tutorial 3: [[Sift:Tutorials:Perform_Principal_Component_Analysis|Perform Principal Component Analysis]]**
  * **Tutorial 4: [[Sift:Tutorials:Export_Results|Export your results]]**

==== Principal Component Analysis ====

[[Sift:Principal_Component_Analysis:Using_Principal_Component_Analysis_in_Biomechanics|PCA]] is a key analytical feature in Sift, allowing you to represent complex biomechanicals waveforms in low-dimensional spaces while maintaining most of the waveforms' information. This tutorial will provide you with an overview of how to perform PCA in Sift and of your options for follow-on analysis.

  * **[[Sift:Tutorials:Perform_Principal_Component_Analysis|Perform Principal Component Analysis]]**: This tutorial provides an overview of performing PCA. This tutorial is the same as the PCA tutorial in the "Getting Started" section.
  * **[[Sift:Tutorials:Run_K-Means|Run K-Means]]**: This tutorial shows how you can use the k-means algorithms to cluster the results of PCA analysis.
  * **[[Sift:Tutorials:Outlier_Detection_with_PCA|PCA Outlier Detection]]**: This tutorial shows how you can use outlier detection methods to find outliers from your PCA analysis.


==== Statistical Parametric Mapping ====

  * **[[sift:tutorials:perform_statistical_parametric_mapping|Perform Statistical Parametric Mapping]]**: This tutorial explores the uses of SPM in Sift, and how you can use it to draw useful analysis.

==== Public Data Sets ====

Exploring publicly available data with Sift is a great way to understand the original paper, learn about Sift's features, and get ideas for your own work.

  * **[[Sift:Tutorials:Treadmill_Walking_in_Healthy_Individuals|Treadmill Walking In Healthy Individuals]]**: This tutorial shows how you can use Visual3D and Sift to automate the processing of large-scale data sets.
  * **[[Sift:Tutorials:OpenBiomechanics_Project:Build_CMZ_Files|OpenBiomechanics Project: Build CMZs Files]]**: This tutorial shows how you can combine .c3d files and metadata into CMZ files for analysis in Sift.
  * **[[Sift:Tutorials:OpenBiomechanics_Project:Analysis_of_Baseball_Hitters_at_Different_Levels_of_Competition|Analysis of Baseball Hitters at Different Levels of Competition]]**: This tutorial shows how you can use Sift to automate the processing of large-scale data sets, and how metadata can be used to help you refine queries.
  * **[[Sift:Tutorials:OpenBiomechanics_Project:Analysis_of_Shoulder_Angular_Velocity_Baseball_Pitching|Analysis of Shoulder Angular Velocity between Elite Level and Average Collegiate Pitchers]]**: This tutorial shows you how to compare two groups using the normal database feature.