Association Between Markerless Motion Capture Screenings and Musculoskeletal Injury Risk for Military Trainees: A Large Cohort and Reliability Study

Viability of Structured Gait Retraining for Improving Clinical Outcomes Following Running-related Injury in Active Duty Service Members

INTRODUCTION

All branches of the U.S. Military have a running component of their physical readiness testing battery. Running-related musculoskeletal injuries affect 20 to 40% of DoD Service Members each year. Running form has not historically been addressed with military running-related injuries. To assess the utility of a structured gait retaining protocol designed to treat the onset of running-related pain and/or injury by correcting identified biomechanical risk factors for injury and improve clinical outcomes.

STUDY DESIGN

Case series.

MATERIALS AND METHODS

A total of 160 Active Duty Service Members (ADSMs) with running-related lower-body musculoskeletal injuries were referred by a physical therapist for a multisession gait retraining program termed "Run with CLASS" (Cadence, Lean, Alignment, Soft-landing, Strike). Run with CLASS utilized various drills to emphasize impact progression, proximal strengthening, and proprioception and spatial awareness.

RESULTS

Results revealed that the implemented gait retraining protocol significantly improved running parameters following lower-body injury as evidenced by increased cadence, improved functional assessment scores, and a marked transition from predominantly heel strike to forefoot strike patterns during running.

CONCLUSIONS

A 3-week supervised gait retraining program focused on the gait retraining program termed "Run with CLASS" (Cadence, Lean, Alignment, Soft-landing, Strike) was successful in altering biomechanics of self-selected running gait by increasing cadence and transitioning ADSMs to a forefoot foot strike. Additionally, ADSMs reported significant improvements on the self-reported functional scores on the University of Wisconsin Running Injury and Recovery Index and Single Assessment Numerical Evaluation.

LEVEL OF EVIDENCE

4.

Reliability of Markerless Motion Capture Systems for Assessing Movement Screenings

Background

Movement screenings are commonly used to detect unfavorable movement patterns. Markerless motion capture systems have been developed to track 3-dimensional motion.

Purpose

To determine the reliability of movement screenings assessed using a markerless motion capture system when comparing the results of multiple systems and multiple collection periods.

Study Design

Descriptive laboratory study.

Methods

The inter- and intrarater reliability of a commercially available markerless motion capture system were investigated in 21 recreationally active participants aged between 18 and 22 years. A total of 39 kinematic variables arising from 10 fundamental upper and lower body movements typical of a screening procedure in sports performance were considered. The data were statistically analyzed in terms of relative error via the intraclass correlation coefficient (ICC) and absolute error via the residual standard error (RSE).

Results

Both inter- and intrarater reliability ICCs were at least moderate across all variables (ICC, >0.50), with most movements and corresponding variables having excellent reliability (ICC, >0.90). Although maximum knee valgus angles were the kinematic variables with the lowest interrater reliability (ICCs, 0.59-0.82) and moderate relative agreement, there was agreement in absolute terms with an RSE of <1.3°.

Conclusion

Findings indicated that markerless motion capture provides reliable measurements of joint position during a movement screen, which allows for a more objective evaluation of the direction and subsequent success of interventions. However, practitioners should consider relative and absolute agreements when applying information provided by these systems.

Clinical Relevance

Markerless motion capture systems may assist clinicians by reliably assessing movement screenings using different systems over different collection periods.

Incidence and Risk Factors for Bone Stress Injuries in United States Air Force Special Warfare Trainees

OBJECTIVES

To determine (1) the incidence rate of lower extremity (LE) bone stress injuries (BSIs) in United States Air Force Special Warfare (AFSPECWAR) trainees during the first 120 days of training, and (2) factors associated with sustaining a LE BSI.

DESIGN

Retrospective cohort study.

METHODS

AFSPECWAR Airmen (n = 2,290, mean age = 23.7 ± 3.6 years) entering an intensive 8-week preparatory course "SW-Prep" between October 2017 and May 2021. We compared anthropometric measurements, previous musculoskeletal injury (MSKI), fitness measures, and prior high-impact sports participation in those that did and did not suffer a BSI during the 120-day observation period using independent t-tests and chi-square tests. A multivariable binary logistic regression was used to determine factors associated with suffering a BSI.

RESULTS

A total of 124 AFSPECWAR trainees suffered a BSI during the surveillance period, yielding an incidence proportion of 5.41% and an incidence rate of 1.4 BSIs per 100 person-months. The multivariate logistic regression revealed that lower 2-minute sit-up scores, no prior history of participation in a high-impact high-school sport, and a history of prior LE MSKI were associated with suffering a BSI. A receiver operator characteristic curve analysis yielded an area under the curve (AUC) of 0.727.

CONCLUSION

BSI incidence proportion for our sample was similar to those seen in other military settings. Military trainees without a history of high-impact sports participation who achieve lower scores on sit-ups tests and have a history of LE MSKI have a higher risk for developing a LE BSI during the first 120 days of AFSPECWAR training.

Identifying special operative trainees at-risk for musculoskeletal injury using full body kinematics

Introduction: Non-combat musculoskeletal injuries (MSKIs) during military training significantly impede the US military's functionality, with an annual cost exceeding $3.7 billion. This study aimed to investigate the effectiveness of a markerless motion capture system and full-body biomechanical movement pattern assessments to predict MSKI risk among military trainees. Methods: A total of 156 male United States Air Force (USAF) airmen were screened using a validated markerless biomechanics system. Trainees performed multiple functional movements, and the resultant data underwent Principal Component Analysis and Uniform Manifold And Projection to reduce the dimensionality of the time-dependent data. Two approaches, semi-supervised and supervised, were then used to identify at-risk trainees. Results: The semi-supervised analysis highlighted two major clusters with trainees in the high-risk cluster having a nearly five times greater risk of MSKI compared to those in the low-risk cluster. In the supervised approach, an AUC of 0.74 was produced when predicting MSKI in a leave-one-out analysis. Discussion: The application of markerless motion capture systems to measure an individual's kinematic profile shows potential in identifying MSKI risk. This approach offers a novel way to proactively address one of the largest non-combat burdens on the US military. Further refinement and wider-scale implementation of these techniques could bring about substantial reductions in MSKI occurrence and the associated economic costs.

Musculoskeletal Injury Risk Stratification: A Traffic Light System for Military Service Members

Risk factor identification is a critical first step in informing musculoskeletal injury (MSKI) risk mitigation strategies. This investigation aimed to determine if a self-reported MSKI risk assessment can accurately identify military service members at greater MSKI risk and determine whether a traffic light model can differentiate service members' MSKI risks. A retrospective cohort study was conducted using existing self-reported MSKI risk assessment data and MSKI data from the Military Health System. A total of 2520 military service members (2219 males: age 23.49 ± 5.17 y, BMI 25.11 ± 2.94 kg/m²; and 301 females: age 24.23 ± 5.85 y, BMI 25.59 ± 3.20 kg/m², respectively) completed the MSKI risk assessment during in-processing. The risk assessment consisted of 16 self-report items regarding demographics, general health, physical fitness, and pain experienced during movement screens. These 16 data points were converted to 11 variables of interest. For each variable, service members were dichotomized as at risk or not at risk. Nine of the 11 variables were associated with a greater MSKI risk and were thus considered as risk factors for the traffic light model. Each traffic light model included three color codes (i.e., green, amber, and red) to designate risk (i.e., low, moderate, and high). Four traffic light models were generated to examine the risk and overall precision of different cut-off values for the amber and red categories. In all four models, service members categorized as amber [hazard ratio (HR) = 1.38-1.70] or red (HR = 2.67-5.82) were at a greater MSKI risk. The traffic light model may help prioritize service members who require individualized orthopedic care and MSKI risk mitigation plans.

Inter-Device Reliability of a Three-Dimensional Markerless Motion Capture System Quantifying Elementary Movement Patterns in Humans

With advancements in technology able to quantify wide-ranging features of human movement, the aim of the present study was to investigate the inter-device technological reliability of a three-dimensional markerless motion capture system (3D-MCS), quantifying different movement tasks. A total of 20 healthy individuals performed a test battery consisting of 29 different movements, from which 214 different metrics were derived. Two 3D-MCS located in close proximity were utilized to quantify movement characteristics. Independent sample t-tests with selected reliability statistics (i.e., intraclass correlation coefficient (ICC), effect sizes, and mean absolute differences) were used to evaluate the agreement between the two systems. The study results suggested that 95.7% of all metrics analyzed revealed negligible or small between-device effect sizes. Further, 91.6% of all metrics analyzed showed moderate or better agreement when looking at the ICC values, while 32.2% of all metrics showed excellent agreement. For metrics measuring joint angles (198 metrics), the mean difference between systems was 2.9 degrees, while for metrics investigating distance measures (16 metrics; e.g., center of mass depth), the mean difference between systems was 0.62 cm. Caution is advised when trying to generalize the study findings beyond the specific technology and software used in this investigation. Given the technological reliability reported in this study, as well as the logistical and time-related limitations associated with marker-based motion capture systems, it may be suggested that 3D-MCS present practitioners with an opportunity to reliably and efficiently measure the movement characteristics of patients and athletes. This has implications for monitoring the health/performance of a broad range of populations.

Predictive utility of commercial grade technologies for assessing musculoskeletal injury risk in US Marine Corps Officer candidates

Recently, commercial grade technologies have provided black box algorithms potentially relating to musculoskeletal injury (MSKI) risk and functional movement deficits, in which may add value to a high-performance model. Thus, the purpose of this manuscript was to evaluate composite and component scores from commercial grade technologies associations to MSKI risk in Marine Officer Candidates. 689 candidates (Male candidates = 566, Female candidates = 123) performed counter movement jumps on SPARTA™ force plates and functional movements (squats, jumps, lunges) in DARI™ markerless motion capture at the start of Officer Candidates School (OCS). De-identified MSKI data was acquired from internal OCS reports for those who presented to the Physical Therapy department for MSKI treatment during the 10 weeks of training. Logistic regression analyses were conducted to validate the utility of the composite scores and supervised machine learning algorithms were deployed to create a population specific model on the normalized component variables in SPARTA™ and DARI™. Common MSKI risk factors (cMSKI) such as older age, slower run times, and females were associated with greater MSKI risk. Composite scores were significantly associated with MSKI, although the area under the curve (AUC) demonstrated poor discrimination (AUC = .55-.57). When supervised machine learning algorithms were trained on the normalized component variables and cMSKI variables, the overall training models performed well, but when the training models were tested on the testing data the models classified MSKI "by chance" (testing AUC avg = .55-.57) across all models. Composite scores and component population specific models were poor predictors of MSKI in candidates. While cMSKI, SPARTA™, and DARI™ models performed similarly, this study does not dismiss the use of commercial technologies but questions the utility of a singular screening task to predict MSKI over 10 weeks. Further investigations should evaluate occupation specific screening, serial measurements, and/or load exposure for creating MSKI risk models.

Pre-neuromusculoskeletal injury Risk factor Evaluation and Post-neuromusculoskeletal injury Assessment for Return-to-duty/activity Enhancement (PREPARE) in military service members: a prospective, observational study protocol

BACKGROUND

Non-battle related musculoskeletal injuries (MSKI) are one of the primary medical issues diminishing Service member medical readiness. The MSKI problem is challenging because it is difficult to assess all of the factors that increase MSKI risk and influence post-MSKI outcomes. Currently, there are no high-throughput, clinically-feasible, and comprehensive assessments to generate patient-centric data for informing pre- and post-MSKI risk assessment and mitigation strategies. The objective of the "Pre-neuromusculoskeletal injury Risk factor Evaluation and Post-neuromusculoskeletal injury Assessment for Return-to-duty/activity Enhancement (PREPARE)" study is to develop a comprehensive suite of clinical assessments to identify the patient-specific factors contributing to MSKI risks and undesired post-MSKI outcomes.

METHODS

This is a phased approach, multi-center prospective, observational study (ClinicalTrials.gov number: NCT05111925) to identify physical and psychosocial factors contributing to greater MSKI risk and undesired post-MSKI outcomes, and to identify and validate a minimal set of assessments to personalize risk mitigation and rehabilitation strategies. In Phase I, one cohort (n = 560) will identify the physical and psychosocial factors contributing to greater MSKI risks (single assessment), while a second cohort (n = 780) will identify the post-MSKI physical and psychosocial factors contributing to undesired post-MSKI outcomes (serial assessments at enrollment, 4 weeks post-enrollment, 12 weeks post-enrollment). All participants will complete comprehensive movement assessments captured via a semi-automated markerless motion capture system and instrumented walkway, joint range of motion assessments, psychosocial measures, and self-reported physical fitness performance and MSKI history. We will follow participants for 6 months. We will identify the minimum set of clinical assessments that provide requisite data to personalize MSKI risk mitigation and rehabilitation strategies, and in Phase II validate our optimized assessments in new cohorts.

DISCUSSION

The results of this investigation will provide clinically relevant data to efficiently inform MSKI risk mitigation and rehabilitation programs, thereby helping to advance medical care and retain Service members on active duty status.

TRIAL REGISTRATION

PREPARE was prospectively registered on ClinicalTrials.gov (NCT05111925) on 5 NOV 2021, prior to study commencement.

Physiological biomarker monitoring during arduous military training: Maintaining readiness and performance

OBJECTIVES

Physiological and psychological stressors can degrade soldiers' readiness and performance during military training and operational environments. Integrative and holistic assessments of biomarkers across diverse human performance optimization domains during multistressor training can be leveraged to provide actionable insight to military leadership regarding service member health and readiness.

DESIGN/METHOD

A broad categorization of biomarkers, to include biochemical measures, bone and body composition, psychometric assessments, movement screening, and physiological load can be incorporated into robust analytical pipelines for understanding the complex factors that impact military human performance.

RESULTS

In this perspective commentary we overview the rationale, selection, and methodologies for monitoring biomarker domains that are relevant to military research and specifically highlight methods that have been incorporated in a research program funded by the Office of Naval Research, Code 34 Biological and Physiological Monitoring and Modeling of Warfighter Performance.

CONCLUSIONS

The integration of screening and continuous monitoring methodologies via robust analytical approaches will provide novel insight for military leaders regarding health, performance, and readiness outcomes during multistressor military training.

Force plate vertical jump scans are not a valid proxy for physical fitness in US special warfare trainees

Background: The United States Air Force Special Warfare Training Wing (SWTW) administers a comprehensive physical fitness test to active duty Airmen entering the Special Warfare training pipeline. The Sparta Science™ system utilizes proprietary software to analyze the force-time curve of a vertical jump and purports to serve as a proxy for traditional military fitness tests. The Sparta Science™ system produces four proprietary metrics, including the Sparta™ Score, which is correlated to high magnitudes of force production purportedly performance. This study investigated how Sparta™ Jump Scans correlate to components of a physical fitness test utilized within the SW training pipeline. Methods: At the entry and exit of an 8-week Special Warfare Training Wing preparatory course (SW PREP), 643 trainees completed both an initial and final Sparta™ Jump Scan and a Candidate Fitness Test (CFT). The Candidate Fitness Test consists of eight components and tests several different domains of fitness including strength, power, muscular endurance, swimming proficiency, and cardiovascular fitness. Paired t-tests were used to determine if Sparta™ Jump Scan metrics and CFT components changed during SW PREP. Sparta™ Score's correlation was assessed against every other Sparta™ Jump Scan metric and all CFT fitness measures. Results: This study found that the Sparta™ Jump Scan metrics decline slightly over SW PREP (p < 0.05; negligible-small effect size), while most CFT measures improve (p < 0.05; small-medium effect size). Changes in Sparta™ Jump Scan metrics did not reflect the changes in CFT performance over SW PREP (r ²: 0.00-0.03). Conclusion: The Sparta™ Score was not correlated to the most tactically-relevant fitness measures (rucking and swimming), and only weakly correlated with the only jumping measure on the fitness test, the standing broad jump.

Repeatability of Motion Health Screening Scores Acquired from a Three-Dimensional Markerless Motion Capture System

The purpose of the present study was to examine the repeatability of five algorithm-derived motion health screening scores (i.e., readiness, explosiveness, functionality, quality, and dysfunction) obtained from an innovative three-dimensional markerless motion capture system, composed of eight high-definition cameras recording at 60 fps. Thirteen females and six males performed two sets of three motion capture screenings, separated one week apart (six in total). The screenings consisted of 20 body movements performed in sequential order. Each screening within a testing session was separated by a 30 min rest interval to avoid the possible influence of fatigue. A trained research team member, facing the participant and standing outside of the camera capture range, was present to demonstrate each individual movement. The order in which motions were performed was identical across all participants. Repeated measures analysis of variance and intraclass correlation coefficients were used to examine statistically significant differences and measurement agreement across six testing sessions. The findings of the present study revealed no significant differences in algorithm-based motion health screening scores across multiple testing sessions. Moreover, excellent measurement reliability was found for readiness scores (ICC, 95% CI; 0.957, 0.914-0.980), good-to-excellent for functionality (0.905, 0.821-0.959) and explosiveness scores (0.906, 0.822-0.959), and moderate-to-excellent for dysfunction (0.829, 0.675-0.925) and quality scores (0.808, 0.635-0.915).

The Use of Force Plate Vertical Jump Scans to Identify Special Warfare Trainees at Risk for Musculoskeletal Injury: A Large Cohort Study

BACKGROUND

Vertical jump scans from commercially available force plate systems are increasingly used in military settings to screen for musculoskeletal injury (MSKI) risk. However, to date, no studies have determined the ability of these tools to identify tactical athletes at elevated risk for MSKI.

PURPOSE

To (1) determine associations between scores from a force plate vertical jump test and the likelihood of experiencing an MSKI and to (2) establish the test-retest reliability of the output scores from the force plate system used.

STUDY DESIGN

Cohort study; Level of evidence, 3.

METHODS

A total of 823 male Air Force Special Warfare trainees underwent force plate vertical jump screenings before entering an 8-week training course at US Air Force Special Warfare Training Wing. MSKI data were collected for the 8-week surveillance period for each trainee. Logistic regression analyses were used to identify associations between baseline force plate jump scores and the likelihood of MSKI (any region) or a lower extremity MSKI (significance level, P = .05). The test-retest portion of the study collected force plate output scores from 12 trainees performing 3 trials of the standard test procedures. The reliability of 5 output scores was assessed with intraclass correlation coefficients (ICCs) using a single rater.

RESULTS

All force plate output scores demonstrated excellent test-retest reliability (ICC >0.90). Overall 308 (36.4%) trainees had an MSKI during the surveillance period. However, no significant associations were found between the proprietary force plate vertical jump scan output scores and the likelihood of experiencing either an MSKI or a lower extremity MSKI.

CONCLUSION

Output scores from this commercially available force plate system did not identify Air Force Special Warfare trainees at elevated risk of experiencing an MSKI.