Table of Contents
Tutorial Files
Sift's tutorials use real data sets wherever possible in order to demonstrate realistic scenarios and avoid overly simplistic examples.
Getting Started
Load and View Data
This tutorial can be completed with any CMZ file. You can use a data set from a Visual3D Workshop at a recent ASB meeting. Visual3D Workshop @ ASB.
Clean your Data
This tutorial uses overground walking data from four subjects. The subjects walked at three different speeds; slow, normal and fast. Four Subjects Walking Data Set.
Perform Principal Component Analysis
This tutorial uses overground walking data from roughly 100 subjects divided into two conditions: normal control and osteoarthritis (moderate to severe). This data set can be found in the Demo folder of your Sift installation.
Export Results
This tutorial uses the same overground walking data set as the Clean your Data tutorial. Four Subjects Walking Data Set.
It also uses predefined queries that have been saved in a .q3d file. AnkleAngles.q3d.
Principal Component Analysis
Perform Principal Component Analysis
This tutorial uses overground walking data from roughly 100 subjects divided into two conditions: normal control and osteoarthritis (moderate to severe). This data set can be found in the Demo folder of your Sift installation.
Run K-Means
This tutorial also uses overground walking data from roughly 100 subjects divided into two conditions: normal control and osteoarthritis (moderate to severe). This data set can be found in the Demo folder of your Sift installation.
Outlier Detection with PCA
This tutorial uses a data set from a Visual3D Workshop at a recent ASB meeting. Visual3D Workshop @ ASB.
Open Source Datasets
These tutorials demonstrate how Sift can be used to explore and analyse different publicly available datasets.
Treadmill Walking in Healthy Individuals
This tutorial explores Fukuchi et al.'s public data set of marker-based motion capture to describe healthy individuals walking overground and on a treadmill.
The data set is available through Figshare: Data Set.
Supporting files are provided to simplify some of the tutorial's steps: Supporting Files.
OpenBiomechanics Project
The Build CMZs Files, Analysis of Baseball Hitters at Different Levels of Competition, and Analysis of Shoulder Angular Velocity between Elite Level and Average Collegiate Pitchers using Sift tutorials all use motion capture data from Driveline Baseball's OpenBiomechanics data set.
The data set is available through Github: Data Set.
Driveline Baseball also provides a website describing the complete OpenBiomechanics data set: Website.
Supporting files to simplify each tutorial are also available:
- Build CMZ Files: Supporting Files.
- Analysis of Baseball Hitters: Supporting Files.
- Analysis of Shoulder Angular Velocity: Supporting Files.