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This shows you the differences between two versions of the page.

--- sift:tutorials:tutorial_overview [2024/06/26 20:21] – created sgranger
+++ sift:tutorials:tutorial_overview [2025/03/14 15:16] (current) – Merged Command Line and Directory Watchers sections. wikisysop
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-====== Tutorial_Overview ======
+====== Tutorial Overview ======
 Get more comfortable with all that Sift has to offer by working through the following tutorials.
-\\
-==== Contents ====
-  * [[#Tutorial_Data_Files|1 Tutorial Data Files]]
-  * [[#Getting_Started|2 Getting Started]]
-  * [[#Principal_Component_Analysis|3 Principal Component Analysis]]
-  * [[#Public_Data_Sets|4 Public Data Sets]]
@@ Line 31: / Line 19: @@
 ==== Principal Component Analysis ====
-[[Sift:Principal_Component_Analysis:PCA_Overview|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: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.
+==== Building a Normal Database ====
+  * **[[sift:tutorials:build_normal_database|Build a Normal Database]]**: This tutorial explores the uses of the Normal Database builder in Sift to generate a reference dataset.
+  * **[[sift:tutorials:compute_GPS_and_GDI|Compute Gait Profile Score (GPS) and Gait Deviation Index (GDI)]]**: This tutorial explores how to leverage Sift's Normal Database files to compute GPS and GDI for individual subjects.
+  * **[[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.
+==== Gait Scores ====
+  * **[[sift:tutorials:compute_GPS_and_GDI|Compute Gait Profile Score (GPS) and Gait Deviation Index (GDI)]]**: This tutorial explores how to leverage Sift's Normal Database files to compute GPS and GDI for individual subjects.
+==== Command Line Interface and Console Application ====
+  * **[[sift:tutorials:command_line|Batch Processing through the Command Line]]**: This tutorial demonstrates how Sift's command line interface can be used to automate analysis tasks and how these tasks can be automated using the Windows operating system.
+  * **[[sift:tutorials:using_directory_watchers| Automating Work Flow With Directory Watchers]]**: This tutorial demonstrates how Sift's directory watchers can be used to automate an entire processing pipeline via the command line.
 ==== Public Data Sets ====
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   * **[[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.