Sift can be used to explore publicly available data sets such as the Healthy Human Walking data set, This tutorial will show you how to use Visual3D to process the .c3d files from this data set, and then how to clean and visualize the data using Sift.
This tutorial uses publicly available data from the paper A biomechanics dataset of healthy human walking at various speeds, step lengths and step widths, which provides an overview of how the data was collected, processed, and stored. Briefly, force plate data and marker-based motion capture data were collected for 10 different participants over 33 walking trials each, with various step lengths, step widths, step frequencies, and speeds. Ground reaction force data were sampled at 1200 Hz and motion capture data were sampled at 120 Hz.
We are interested in the .c3d files that can be downloaded here.
Also necessary are the Visual3D pipeline scripts, model templates, and Sift query definitions that can be downloaded here.
Our first step is to process each participant's .c3d files into a CMZ file with the necessary signals and events. 1. Open Visual3D and click on the Pipeline toolbar option.
2. Open Pipeline, select the Create_CMOs.v3s pipeline script associated with this tutorial, and then Execute Pipeline.
The Create_CMOs script loads a static trial and a model template for a set of dynamic trials, modifies force platform parameters in line with Visual3D's recommendations, cleans force assignments, computes gait events, and produces a report for the signals of interest. For this data set we want one CMZ per participant, so the following steps would need to be performed for each Participant separately.
1. To create Participant 1's CMZ file, choose p1_c3dfiles/p1_standing_1.c3d file as the static calibration file.
2. Choose Model_Template_CMotion_v2.mdh as the model file.
3. Set Participant 1's weight, height, and foot width according to the anthropometric information included in the paper.
4. Choose the remaining 33 .c3d files in the p1_c3dfiles folder as the dynamic trials.
5. Choose Sample_Report_Template.rgt as the report template.
6. Save the results as Participant_1.cmz.
Only Participant 1's CMZ file is needed for this tutorial, so you can close Visual3D and continue on to the next section once these steps are complete.
The processing done in Visual3D allows us to extract signal traces from all of our desired gait sequences from the .c3d files, but not all of these are suitable for further analysis. The number of traces involved makes it impractical to clean this data set in Visual3D, there are more than 3000 traces for Participant 1 alone, but Sift gives us the ability to visualize the ground reaction forces and make inclusion/exclusion decisions for each trace. A detailed explanation of this process can be found in the Clean your data tutorial.
Now that Participant 1's CMZ file has been cleaned of any unwanted traces, we are ready to perform some preliminary analysis and visualize the data set. Our goal in this section is to reproduce Figure 3 in the paper.
In this tutorial you learned how Sift, along with Visual3D, can be used to explore and analyse public data sets. You learned how to take the raw data found in the Healthy Human Walking data set's .c3d files and reproduce Figure 3 from the associated paper.
Paper van der Zee, T.J., Mundinger, E.M. & Kuo, A.D. A biomechanics dataset of healthy human walking at various speeds, step lengths and step widths. Sci Data 9, 704 (2022). DOI
Data set van der Zee, T.J., Mundinger, E.M. & Kuo, A.D. A biomechanics dataset of healthy human walking at various speeds, step lengths and step widths. figshare. Collection. (2022). DOI