Effect of high and low-supportive footwear on female tri-planar knee moments during single limb landing

Effects of Footwear on Anterior Cruciate Ligament Forces during Landing in Young Adult Females

Rates of anterior cruciate ligament (ACL) rupture in young people have increased markedly over the past two decades, with females experiencing greater growth in their risk compared to males. In this study, we determined the effects of low- and high-support athletic footwear on ACL loads during a standardized drop-land-lateral jump in 23 late-/post-pubertal females. Each participant performed the task unshod, wearing low- (Zaraca, ASICS) or high- (Kayano, ASICS) support shoes (in random order), and three-dimensional body motions, ground-reaction forces, and surface electromyograms were synchronously acquired. These data were then used in a validated computational model of ACL loading. One-dimensional statistical parametric mapping paired t-tests were used to compare ACL loads between footwear conditions during the stance phase of the task. Participants generated lower ACL forces during push-off when shod (Kayano: 624 N at 71-84% of stance; Zaraca: 616 N at 68-86% of stance) compared to barefoot (770 N and 740 N, respectively). No significant differences in ACL force were observed between the task performed wearing low- compared to high-support shoes. Compared to barefoot, both shoe types significantly lowered push-off phase peak ACL forces, potentially lowering risk of ACL injury during performance of similar tasks in sport and recreation.

What did the ankle say to the knee? Estimating knee dynamics during landing - A systematic review and meta-analysis

BACKGROUND

Landing-based measures of the knee are often used to assess risk of anterior cruciate ligament (ACL) injury and inform prevention strategies. There is less understanding of the ankle's influence on knee measures during landing.

OBJECTIVE

1. Examine interactions of dynamic ankle measures alongside various subject and task characteristics on knee dynamics in vertical landing and 2. Determine whether ankle measures alone can estimate dynamic knee measures associated with ACL injury risk.

DESIGN

Systematic review and meta-analysis.

METHODS

Electronic databases Medline, EMBASE, CINAHL, Web of Science and Cochrane were screened for studies that included measurement of initial contact angles and internal joint moments of both the ankle and knee during landing in uninjured individuals.

RESULTS

28 studies were included for analysis. Using 1144 landing trials from 859 individuals, RRelief F algorithm ranked dynamic ankle measures more important than landing task and subject characteristics in estimating knee dynamics. An adaptive boosting model using four dynamic ankle measures accurately estimated knee extension (R² = 0.738, RMSE = 3.65) and knee abduction (R² = 0.999, RMSE = 0.06) at initial contact and peak knee extension moment (R² = 0.988, RMSE = 0.13) and peak knee adduction moment (R² = 1, RMSE = 0.00).

CONCLUSIONS

Dynamic ankle measures can accurately estimate initial contact angles and peak moments of the knee in vertical landing, regardless of landing task or individual subject characteristics. This study provides a theoretical basis for the importance of the ankle in ACL injury prevention.

Modelling the loading mechanics of anterior cruciate ligament

BACKGROUND AND OBJECTIVES

The anterior cruciate ligament (ACL) plays a crucial role in knee stability and is the most commonly injured knee ligament. Although ACL loading patterns have been investigated previously, the interactions between knee loadings transmitted to ACL remain elusive. Understanding the loading mechanism of ACL during dynamic tasks is essential to prevent ACL injuries. Therefore, we propose a computational model that predicts the force applied to ACL in response to knee loading in three planes of motion.

METHODS

First, a three-dimensional (3D) computational model was developed and validated using available cadaveric experimental data to predict ACL force. This 3D model was then combined with a neuromusculoskeletal model of lower limb and used to estimate in vivo ACL forces during a standardised drop-landing task. The neuromusculoskeletal model utilised movement data collected from female participants during a dynamic task and calculated lower limb joint kinematics and kinetics, as well as muscle forces.

RESULTS

The total ACL force predicted by the 3D computational ACL force model was in good agreement with cadaveric data, as strong correlation (r² = 0.96 and P < 0.001), minimal bias, and narrow limits of agreement were observed. The combined model further illustrated that the ACL is primarily loaded through the sagittal plane, mainly due to muscle loading.

CONCLUSIONS

The proposed computational model is the first validated model that can provide an accessible tool to develop and test knee ACL injury prevention programs for people with normal ACL. This method can be extended to study the abnormal ACL upon the availability of relevant experimental data.