Open Source, Open Science: Development of OpenLESS as the Automated Landing Error Scoring System

Area of Science:

• Biomechanics
• Movement Science
• Clinical Assessment

Background:

• Assessing lower extremity movement quality during jump-landing is crucial for injury prevention and rehabilitation.
• Current methods like the Landing Error Scoring System (LESS) are time-consuming and require manual scoring.
• There is a need for automated, efficient tools to analyze functional movement in clinical settings.

Purpose of the Study:

• To develop and validate the Open Landing Error Scoring System (OpenLESS), an open-source, markerless motion capture tool.
• To assess the validity of OpenLESS against expert LESS scores in healthy and post-anterior cruciate ligament reconstruction (ACLR) populations.
• To evaluate the intersession reliability of OpenLESS in an athlete cohort.

Main Methods:

• Developed OpenLESS software to automatically score jump-landing movement quality from 3D kinematics.
• Collected data from 92 participants across healthy, post-ACLR, and amateur athlete cohorts.
• Assessed validity using intraclass correlation coefficients (ICC) against expert LESS scores and reliability across four time points.

Main Results:

• OpenLESS demonstrated good agreement with expert LESS scores in healthy (ICC=0.79) and post-ACLR (ICC=0.88) cohorts.
• Automated scoring significantly reduced analysis time compared to manual scoring (under 15 minutes vs. 18.5 hours).
• Excellent intersession reliability was observed (ICC > 0.89) with a SEM of 0.98 errors and MDC of 2.72 errors.

Conclusions:

• OpenLESS is a promising, efficient, and automated tool for assessing jump-landing quality.
• The system shows good validity against expert raters and excellent reliability in field settings.
• OpenLESS addresses the need for objective and timely movement analysis in clinical practice and research.