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Table of Contents
Excluding Data in Sift
In biomechanics, some trials or trace may not be suitable for analysis. A missed marker, an incorrect force plate assignment, or an unexpected movement during a trial can all introduce noise into the results. Rather than deleting these trials outright, Sift allows users to flag them for exclusion, which keeps the analysis clean while preserving the original data.
Data cleaning is an ongoing process, and exclusions can be revisited at any time as new issues are identified.
How Exclusions Work
Excluding a trace removes it from analysis (and optionally, plots), but does not delete the underlying data. Exclusions can be undone at any time using Ctrl+Z or by right-clicking a workspace and selecting Re-Include Data, and excluded traces can be toggled back on to review them alongside valid data.
Sift supports three levels of exclusion:
- Individual trace — exclude a single signal cycle only
- All traces at those frames — exclude all queried signals during the same cycle
- Entire trial — exclude all data from the affected trial
Writing Exclusions Back to the Data
Once exclusions have been identified, they can be written back to the original workspace files. This is done by adding a “Bad” event to the excluded cycle…. See excluded_traces
It is also possible to tag entire trials that contain excluded data, making it easy to identify and filter problematic files downstream.
Plot Options
Two display options in the plot are available:
- Hide Excluded Data: removes excluded traces from the plot entirely.
- Show Excluded Data: keeps excluded traces visible in the plot while still omitting them from analysis.
Tutorials
- Clean your Data — A step-by-step walkthrough of using Sift to identify and exclude bad trials across a full dataset, using a ground reaction force quality check as an example.




