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

Abstract

Context: The Open Landing Error Scoring System (OpenLESS) is a novel development aimed at automating the LESS for assessment of lower extremity movement quality during a jump-landing task. With increasing utilization of clinical measures to monitor outcomes and limited time during clinical visits for a lengthy analysis of functional movement, there is a pressing need to extend automation efforts. Addressing these issues, OpenLESS is an open-source tool that utilizes a freely available markerless motion capture system to automate the LESS using three-dimensional kinematics.

Objective: To describe the development of OpenLESS, examine the validity against expert rater LESS scores in healthy and clinically relevant cohorts, and assess the intersession reliability collected across four time points in an athlete cohort.

Design: Observational.

Participants: 92 participants (72 females and 20 males, mean age 23.3 years) from healthy, post-anterior cruciate ligament reconstruction (ACLR; median 33 months since surgery), and amateur athlete cohorts.

Main outcome measures: A software package, "OpenLESS," was developed to interpret movement quality (LESS score) from kinematics captured from markerless motion capture. Validity and reliability were assessed with intraclass correlation coefficients (ICC), standard error of measure (SEM), and minimal detectable change (MDC).

Results: OpenLESS agreed well with expert rater LESS scores for healthy (ICC _{2, k} =0.79) and clinically relevant, post-ACLR cohorts (ICC _{2, k} =0.88). The automated OpenLESS system reduced scoring time, processing all 159 trials in under 15 minutes compared to the 18.5 hours (7 minutes per trial) required for manual expert rater scoring. When tested outside laboratory conditions, OpenLESS showed excellent reliability across repeated sessions (ICC _{2, k} >0.89), with a SEM of 0.98 errors and MDC of 2.72 errors.

Conclusion: OpenLESS shows promise as an efficient, automated tool for clinically assessing jump-landing quality, with good validity versus experts in healthy and post-ACLR populations, and excellent field reliability, addressing the need for objective movement analysis.

Key points: OpenLESS accurately detected jump-landing events (ICC>0.99) using markerless motion capture, validating its use as an alternative to laboratory-based force plate measurements.The automated scoring system showed good agreement with expert raters in healthy (ICC=0.79) and post-ACLR (ICC=0.88) populations.OpenLESS demonstrated good to excellent test-retest reliability (ICC=0.89) across multiple testing sessions, with minimal score variation, supporting its utility for longitudinal movement assessment.