When to use
- For research protocol documentation and descriptive session summaries
- For preparing ConductVision Human Tracking video workflows
- For organizing export-ready methods text, filenames, or CSV quality checks
Create standardized filenames and a session manifest for human research video before ConductVision upload.

filename,participant,date,protocol,view,condition,trial P001_20260602_GAIT_SAG_BASE_trial01.mp4,P001,20260602,GAIT,SAG,BASE,1 P001_20260602_GAIT_SAG_BASE_trial02.mp4,P001,20260602,GAIT,SAG,BASE,2 P001_20260602_GAIT_SAG_BASE_trial03.mp4,P001,20260602,GAIT,SAG,BASE,3 P001_20260602_GAIT_SAG_BASE_trial04.mp4,P001,20260602,GAIT,SAG,BASE,4 P001_20260602_GAIT_SAG_BASE_trial05.mp4,P001,20260602,GAIT,SAG,BASE,5 P001_20260602_GAIT_SAG_BASE_trial06.mp4,P001,20260602,GAIT,SAG,BASE,6 Research video files were named using a structured participant/session/trial convention. Research use only. This tool is for education, protocol documentation, and research workflow planning. It is not for care decisions, participant triage, or health advice.
When to use
Do not use for
Use participant, subject, trial, protocol, and research session language. Avoid care-directed interpretations.
Store source video, keypoint exports, confidence values, and session notes so outputs remain auditable.
Run one short pilot and inspect visibility, lighting, scale references, and keypoint confidence before collecting a full dataset.
The tool performs deterministic arithmetic, checklist generation, or CSV summary operations in the browser. It does not assess injuries, classify participants for care, or replace a protocol approved for research use.
Last validated 2026-06-02. Calculations are designed for planning and documentation support; verify procurement decisions against manufacturer specifications or institutional SOPs.
ConductScience Human Video Session Label Generator (v0.10.253). ConductScience, Inc. 2026. Available at: https://conductscience.com/tools/human-video-session-label-generator
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Mathis A et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat Neurosci. 2018;21(9):1281-1289.