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
Document jump-landing research observations with a checklist-style movement score and exportable notes.

Observed flags
3
Research note
Several observed landing flags
Jump landing research summary Observed flags: 3 Research note: Several observed landing flags [ ] Limited trunk control observed [x] Knee valgus or medial collapse observed [ ] Asymmetric foot contact observed [x] Limited knee flexion on landing [ ] Wide or narrow stance outside protocol target [ ] Audible or visibly hard landing [x] Uncontrolled rebound or extra step [ ] Upper-limb compensation noted Jump-landing observations were documented from research video review and are not an injury assessment. 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 Jump Landing Score Calculator (v0.10.253). ConductScience, Inc. 2026. Available at: https://conductscience.com/tools/jump-landing-score-calculator
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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.
ConductVision can map jump-landing keypoints, joint angles, and landing events from research video.
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