Spatiotemporal Gait Parameters as Predictors of Lower-Limb Overuse Injuries in Military Training

The Agreement between Wearable Sensors and Force Plates for the Analysis of Stride Time Variability

The variability and regularity of stride time may help identify individuals at a greater risk of injury during military load carriage. Wearable sensors could provide a cost-effective, portable solution for recording these measures, but establishing their validity is necessary. This study aimed to determine the agreement of several measures of stride time variability across five wearable sensors (Opal APDM, Vicon Blue Trident, Axivity, Plantiga, Xsens DOT) and force plates during military load carriage. Nineteen Australian Army trainee soldiers (age: 24.8 ± 5.3 years, height: 1.77 ± 0.09 m, body mass: 79.5 ± 15.2 kg, service: 1.7 ± 1.7 years) completed three 12-min walking trials on an instrumented treadmill at 5.5 km/h, carrying 23 kg of an external load. Simultaneously, 512 stride time intervals were identified from treadmill-embedded force plates and each sensor where linear (standard deviation and coefficient of variation) and non-linear (detrended fluctuation analysis and sample entropy) measures were obtained. Sensor and force plate agreement was evaluated using Pearson's r and intraclass correlation coefficients. All sensors had at least moderate agreement (ICC > 0.5) and a strong positive correlation (r > 0.5). These results suggest wearable devices could be employed to quantify linear and non-linear measures of stride time variability during military load carriage.

Association between Self-reported Sleep Quality and Single-task Gait in Young Adults: A Study Using Machine Learning

Objective  The objective of the present study was to find biomechanical correlates of single-task gait and self-reported sleep quality in a healthy, young population by replicating a recently published study. Materials and Methods  Young adults ( n  = 123) were recruited and were asked to complete the Pittsburgh Sleep Quality Inventory to assess sleep quality. Gait variables ( n  = 53) were recorded using a wearable inertial measurement sensor system on an indoor track. The data were split into training and test sets and then different machine learning models were applied. A post-hoc analysis of covariance (ANCOVA) was used to find statistically significant differences in gait variables between good and poor sleepers. Results  AdaBoost models reported the highest correlation coefficient (0.77), with Support-Vector classifiers reporting the highest accuracy (62%). The most important features associated with poor sleep quality related to pelvic tilt and gait initiation. This indicates that overall poor sleepers have decreased pelvic tilt angle changes, specifically when initiating gait coming out of turns (first step pelvic tilt angle) and demonstrate difficulty maintaining gait speed. Discussion  The results of the present study indicate that when using traditional gait variables, single-task gait has poor accuracy prediction for subjective sleep quality in young adults. Although the associations in the study are not as strong as those previously reported, they do provide insight into how gait varies in individuals who report poor sleep hygiene. Future studies should use larger samples to determine whether single task-gait may help predict objective measures of sleep quality especially in a repeated measures or longitudinal or intervention framework.

Increased Barefoot Stride Variability Might Be Predictor Rather than Risk Factor for Overuse Injury in the Military

Footwear usage could be a promising focus in reducing musculoskeletal injury risk in lower extremities commonly observed among the military. The goal of this research was to find potential gait-related risk factors for lower leg overuse injuries. Cases (n = 32) were active-duty infantry soldiers who had suffered an overuse injury in the previous six months of service before enrolling in the study. The control group (n = 32) included infantry soldiers of the same age and gender who did not have a history of lower leg overuse injury. In the gait laboratory, individuals were asked to walk on a 5-m walkway. Rearfoot eversion, ankle plantar/dorsiflexion and stride parameters were evaluated for barefoot and shod conditions. Barefoot walking was associated with higher stride time variability among cases. According to the conditional regression analysis, stride time variability greater than 1.95% (AUC = 0.77, 95% CI (0.648 to 0.883), p < 0.001) during barefoot gait could predict lower leg overuse injury. Increased barefoot gait variability should be considered as a possible predictive factor for lower leg overuse injury in the military, and gait with military boots masked stride-related differences between soldiers with and without lower leg overuse injury.

The Influence of Sport-Related Concussion on Lower Extremity Injury Risk: A Review of Current Return-to-Play Practices and Clinical Implications

Sport-related concussions (SRCs) are now classified as a major health concern affecting athletes across all sporting levels, with recent evidence suggesting upwards of 3.8 million SRCs occur each year. Multiple injury surveillance datasets have recently determined that athletes post-SRC, compared to non-concussed counterparts, are at greater risk for lower extremity (LE) injury beyond the resolution of traditional SRC assessment batteries. However, it is presently uncertain if common clinical practices (symptom reporting, neuropsychological (NP) examination, and static postural control analysis) can determine athletes at risk for LE injury following an SRC. A comprehensive review of the literature determined that these tools may not reveal subtle cognitive and neuromuscular deficits that lead to subsequent LE injury during dynamic sporting tasks. Current return-to-play (RTP) protocols should consider clarifying the addition of specific objective locomotor analysis, such as gait tasks and sport-specific maneuvers, to determine the risk of LE injury after an athlete has sustained an SRC.

The Landing Error Scoring System Real-Time test as a predictive tool for knee injuries: A historical cohort study

PURPOSE

To assess the value of the Landing error score system - real time test as a predictive tool for knee injuries among combat soldiers in the Israeli defense forces.

METHODS

All 2474 Israeli defense forces' combat soldiers enrolled at the Israeli defense forces Injury Prevention and Rehabilitation Center were included. A retrospective cohort study was conducted. The predictive variable assessed was the landing error score system - real time score. The three main outcome variables were the incidence of overuse knee injuries, the meniscal injury, and the anterior cruciate ligament injury. Receiver operator characteristic analysis was performed to evaluate the test's potential as a predictive tool and in order to establish optimal cutoff scores.

RESULTS

The area under the curve of the receiver operation curves demonstrated no predictive value of the landing error score system - real time test for all three outcome variables (knee injuries: area under the curve 0.526, 95% confidence interval 0.498, 0.554, anterior cruciate ligament injuries: area under the curve 0.496, 95% confidence interval 0.337, 0.656, meniscus injuries: area under the curve 0.515, 95% confidence interval 0.454, 0.576).

INTERPRETATION

Based on the results of this study, the landing error score system - real time test has no predictive value for knee overuse injuries, meniscal injuries, and anterior cruciate ligament injuries. However, due to the small number of cases of anterior cruciate ligament injuries, the predictive value for anterior cruciate ligament injuries of this test should be further investigated.

Statistical Parametric Mapping as a Measure of Differences Between Limbs: Applications to Clinical Populations

In healthy individuals, symmetrical lower-extremity movement is often assumed and calculated using discrete points during various tasks. However, measuring overall movement patterns using methods such as statistical parametric mapping (SPM) may allow for better interpretation of human movement. This study demonstrated the ability of SPM to assess interlimb differences in lower-extremity movement during 2 example tasks: running and landing. Three-dimensional motion analysis was used to determine sagittal and frontal plane lower-extremity joint angles in (1) young and older individuals during running and (2) patients with anterior cruciate ligament reconstruction and uninjured control athletes during landing. Interlimb differences within each group were compared using SPM and paired t tests on peak discrete angles. No differences between limbs were found between young and older runners using SPM. Peak ankle eversion and plantar flexion angles differed between limbs in young and older runners. Sagittal plane hip angle varied between limbs in uninjured control athletes. Frontal plane ankle angle and sagittal plane knee and hip angles differed between limbs in patients with anterior cruciate ligament reconstruction using SPM and discrete analysis. These data suggest that SPM can be useful to determine clinically meaningful interlimb differences during running and landing in multiple populations.

Evaluation of Two Simple Functional Tests to Predict Attrition from Combat Service in Female Light Infantry Soldiers

BACKGROUND Worldwide, there is a high attrition rate, or dropout rate, from combat in trained soldiers, mainly due to musculoskeletal injuries. This study aimed to determine whether the use of an upper limb stability test, the Upper Quarter Y-Balance Test (UQYBT), and a modified version of the Ranger Test (MRT) that included a lower limb step-up endurance test, could predict attrition from combat service in female infantry soldiers. MATERIAL AND METHODS In 2015, a group of 167 newly recruited female light infantry soldiers were evaluated using the UQYBT and the MRT. Data regarding attrition from combat service were collected in 2017, 18 months after screening. Multiple logistic regression analysis was used to determine the predictive effect of body mass index (BMI), UQYBT, and MRT scores on attrition from combat service. RESULTS Fifty-three female soldiers (31.7%) dropped out of combat service during the 18 months following recruitment. The MRT score was a significant predictor of attrition, with each additional incremental increase in the MRT score reducing the attrition rate by 6.8% (OR=0.934; 95% CI, 0.895-0.975). A cutoff MRT score of 12 increments predicted attrition with 73.7% sensitivity and 50.9% specificity. The UQYBT scores and BMI were not significant predictors. CONCLUSIONS The use of the MRT during military training, was a predictive screening method to predict attrition from combat service in Israeli female infantry soldiers. Further studies are required to evaluate the use of the MRT in other groups of women in the military.