INTRODUCTION:Measuring shoulder mobility is essential for assessing function, especially in occupational settings like the military, where movement tasks in the frontal and sagittal planes are involved. Markerless motion capture systems like the HumanTrak may provide an expedient field platform to quantify upper body kinematics in occupational settings because of their portability. Further validation of these systems against established methodologies, such as marker-based motion capture, is required before upscaling their use. MATERIALS AND METHODS:Seventeen participants (7 males and 10 females; age, 25 ± 7 years; stature, 1.70 ± 0.08 m; mass, 72.26 ± 15.09 kg) completed standardized fixed-range shoulder flexion, extension, abduction, and adduction tasks with and without body armor for 3 systems: HumanTrak, 2D video capture, and 3D marker-based motion capture. Joint angles were calculated using planar and Euler algorithms. The HumanTrak's relative and absolute validity was compared against these established methodologies. RESULTS:Generally, valid relative and absolute results were found, with Pearson correlations (r) ranging from 0.56 to 0.93 and root mean square errors ranging from 2.51° to 7.35° for shoulder flexion, extension, and abduction with and without body armor. Shoulder adduction measures were generally invalid, as r values ranged from -0.24 to 0.77, and with root mean square errors ranging from 5.27° to 8.42°. CONCLUSIONS:The HumanTrak's validity is comparable to that of existing field expedient markerless motion capture systems in estimating shoulder joint angles in abduction and the sagittal plane. When movements are standardized to a singular plane of motion and a neutral spine is assumed, valid results can be measured for shoulder flexion, extension, and abduction with and without body armor. Shoulder adduction was generally invalid for both body armor and no body armor conditions, likely because of its multi-planar nature and axial trunk rotation.

Firefighting involves physically demanding tasks performed under high heat and time pressure. While previous research reports the physical load involved, the extent to which physical fatigue impedes firefighting performance, especially in shipboard environments remains underexplored. Using a laboratory-based shipboard firefighting simulation, this study investigated how physical fatigue and heat influences time-to-completion (TTC), perceived workload, and muscular strength. Thirty participants completed the simulation in Fresh, Fatigue, and Fatigue + Heat conditions, followed by physical performance testing. Compared to Fresh, simulation TTC increased by 7.2% and 8.5% under Fatigue and Fatigue + Heat conditions respectively (p < 0.001; d = 0.62 - 0.69), with RPE increasing by 32% (Fatigue) and 46% (Fatigue + Heat) (p < 0.001; d = 1.31 - 2.39). Further, pre-simulation fatigue reduced both isometric mid-thigh pull and push-up peak forces (measured post-simulation) compared to control strength measures (p < 0.05; d = 0.18 - 0.27). This study highlights how physical fatigue hinders physical capabilities in a firefighting context.

ABSTRACT:Kirk, BJC, Wills, JA, Glen, B, and Doyle, TLA. Isometric floor press: A valid, reliable, and practical field-based assessment of upper-body strength. J Strength Cond Res XX(X): 000-000, 2026-There is currently no standardized method for assessing upper-body isometric strength using portable field-based equipment, limiting practitioners' ability to monitor upper-body strength in applied environments. This study evaluated the validity and reliability of 4 novel tests performed using only a force plate system and isometric midthigh pull rack: the isometric push-up (IPU) on knees and feet, and the isometric floor press at 90° (IFP90) and 135° (IFP135) elbow angles. Twenty recreationally trained adults (16 men, 4 women) completed a 1 repetition maximum bench press and familiarization session, followed by 2 isometric testing sessions, each separated by 7 days. Validity was assessed using Pearson correlation with 1 repetition maximum bench press. Within-day and between-day reliability were evaluated using intraclass correlation coefficients (ICC) and coefficient of variation (CV%). IFP90 showed the strongest validity (r = 0.887), followed by IFP135 (r = 0.724), IPU on knees (r = 0.711), and IPU on feet (r = 0.692). All tests demonstrated excellent within-day reliability (ICC = 0.923-0.983; CV% = 5.3-7.7%) and between-day reliability (ICC = 0.912-0.955; CV% = 6.4-12.3%). Supine configurations (IFP) generally showed greater measurement stability than prone push-up variations (IPU), with lower variability and higher ICCs. Results were consistent across a broad strength range (bench press = 65-140 kg), supporting their applicability to both athletic and general populations. These findings suggest that IFP90 offers a valid, reliable, and practical field-based alternative to traditional upper-body strength testing. These tests may be especially useful in settings where safety, measurement sensitivity, and fatigue minimization are priorities.

Firefighting requires sustained attention in extremely physically and cognitively demanding conditions. While previous research has examined the effects of physical load, there remains scope to assess how increased cognitive demand influences firefighting performance, especially in shipboard environments where sailors are not occupational firefighters. This study used a laboratory-based shipboard firefighting simulation to investigate whether a cognitively demanding task (45-minute 2-back) affected simulation time-to-completion (TTC) and perceived workload, alongside post-simulation cognitive ability and perceived mental fatigue. Twenty-eight healthy adults with no firefighting experience completed the simulation under two conditions: Fresh and Cognitive Demand (CogDemand), with cognitive testing and subjective scales of fatigue, motivation and sleepiness completed prior to, and after, the firefighting simulation in both sessions. The 2-back task successfully induced cognitive load, evidenced by increased perceived mental fatigue and decreased vigour ( p < 0.01). However, despite significantly increased perceived cognitive workload in the CogDemand simulation, simulation TTC (Fresh, 411.5 s; CogDemand, 412.5 s) and ratings of perceived exertion (Fresh, 71.7; CogDemand, 74.5) were not significantly different between conditions ( p > 0.05). Following the simulation, perceived mental fatigue and effort to concentrate were significantly higher in the CogDemand condition compared to Fresh ( p < 0.05). However, cognitive test performance was not significantly different between conditions ( p > 0.05). These findings suggest that physical and cognitive performance are maintained relative to a fresh state, despite prior cognitive loading, with positive implications for occupational contexts requiring rapid task switching, such as shipboard firefighting.

Understanding shipboard firefighting performance is critical for improving crew safety and vessel preservation during damage control events. While prior research has been conducted in naval spaces, controlled simulations that assess performance without requiring naval vessels, personnel or specialised equipment are lacking. This study was designed to both develop and test a laboratory-based shipboard firefighting simulation. Consistent with shipboard firefighting activities, the simulation included walking, stair climbing, hose dragging, simulated boundary cooling, extinguisher carrying and casualty dragging tasks, completed within 8 min. Twenty-seven participants (22 males, 5 females) performed the simulation twice, with good test-retest reliability (ICC = 0.78; SEM = 17.6 s). Compared to Session 1, time-to-completion was 2.6% faster, RPE was 12.2% higher, HR was 5% lower, and core temperature estimate was 0.8% lower in Session 2 (all p < 0.05). This simulation provides a practical, low-cost solution for conducting shipboard firefighting research using minimal space, equipment, and untrained subjects.

PURPOSE:Combat maneuverability is critical for soldier survivability. Military organizations ensure effective combat maneuverability through routine assessments. Advanced statistical analyses may improve combat movement efficiency practices. This study grouped physical qualities (e.g., strength, power, mobility) via an exploratory factor analysis (EFA) and extracted factors to compare high and low performers and develop predictive models. METHODS:Thirty-four participants completed two sessions assessing physical qualities and combat movement performance. Participants were classified as either "high" or "low" performers (i.e., completed 50 laps of the assessment or completed less than 50 laps, respectively). An EFA was conducted to reduce physical quality dataset dimensions into specific factors. T -test and effect size compared factors between high and low performers. Logistic regression, multilayer perceptron, and random forest models were trained and tested to classify performers based on factor values. Feature importance scores determined factors most influential in classifying participants. RESULTS:EFA resulted in four factors (81.46% variance explained). Factor 1 represented isometric strength, jumping, and drop landing ability. Factors 2-4 represent isometric strength and rate of force development in the lower and upper body, and overhead squat ability, respectively. All factors significantly differed between groups, with high performers demonstrating higher mean values than low performers ( P < 0.05). Factor 1 demonstrated a very large effect size ( d = 2.15), whereas factors 2-4 were moderate-large ( d = 0.72-0.81). The logistic regression model had 100% accuracy in the testing phase, whereas other models achieved 86%. Factor 1 was the most influential factor across models (approximately six times more than other factors). CONCLUSIONS:Utilized models show military applicability in classifying high or low performers for combat maneuverability. Physical interventions optimizing factor 1 may enhance combat maneuverability.

This investigation for the first time observed an association between the traditional measurement of allostatic load, the allostatic load index, and wearable-assessed physiological responses to strenuous military training stress. We found a novel digital phenotype of allostatic load characterized by chronically elevated and variable cardiometabolic activity with blunted variation in heart rate during sleep. This phenotype may serve as an at-risk profile of high allostatic load and prompt in-training modifications to enhance posttraining readiness.

This study investigated the feasibility of a field-based gait retraining program using real-time axial peak tibial acceleration (PTA) feedback in high-impact recreational runners and explored the effects on running biomechanics and economy. We recruited eight recreational runners with high landing impacts to undertake eight field-based sessions with real-time axial PTA feedback. Feasibility outcomes were assessed through program retention rates, retraining session adherence, and perceived difficulty of the gait retraining program. Adverse events and pain outcomes were also recorded. Running biomechanics were assessed during field and laboratory testing at baseline, following retraining, and one-month post-retraining. Running economy was evaluated during laboratory testing sessions. Seven participants completed the retraining program, with one participant withdrawing due to illness before commencing retraining. An additional participant withdrew due to a foot injury after retraining. Adherence to retraining sessions was 100%. The mean (SD) perceived difficulty of the program was 4.3/10 (2.2). Following retraining, the mean axial PTA decreased in field (−29%) and laboratory (−33%) testing. The mean instantaneous vertical loading rate (IVLR) reduced by 36% post-retraining. At one-month follow-up, the mean axial PTA remained lower for field (−24%) and laboratory (−34%) testing, and the IVLR remained 36% lower than baseline measures. Submaximal oxygen consumption increased following gait retraining (+5.6%) but reverted to baseline at one month. This feasibility study supports the use of field-based gait retraining to reduce axial PTA and vertical loading rates in recreational runners without adversely affecting the running economy.

Measuring lower extremity impact acceleration is a common strategy to identify runners with increased injury risk. However, existing axial peak tibial acceleration (PTA) thresholds for determining high-impact runners typically rely on small samples or fixed running speeds. This study aimed to describe the distribution of axial PTA among runners at their preferred running speed, determine an appropriate adjustment for investigating impact magnitude at different speeds, and compare biomechanics between runners classified by impact magnitude. A total of 171 runners ran on an instrumented treadmill at their preferred running speed during 3D motion capture. Axial PTA was collected at the distal tibia. The relationship between axial PTA and running speed was investigated using linear regression. Runners were categorized into impact sub-groups, with high- and low-impact runners identified if their axial PTA was ±1 standard deviation of the model predicted value. Differences in demographics, training, and running biomechanics between impact sub-groups were compared. Mean axial PTA was 7.8 g across all running speeds. Axial PTA increased with running speed, with a 1.7 g increase for every 1.0 m/s increase. There were no differences in axial PTA between males and females (p = 0.214) and lower limbs (p = 0.312). High-impact runners had higher vertical loading rates (p < 0.001) and greater ankle dorsiflexion at initial contact (p < 0.001) compared to low-impact runners. No differences in age, body mass, height, or weekly running distances were observed across impact sub-groups. This study proposes a method to identify the impact classification of runners based on their axial PTA for screening, monitoring, or gait retraining.

PURPOSE:Load carriage and tactical mobility are military tasks that pose significant risks for musculoskeletal injuries (MSKI) in military personnel. This investigation compared biomechanical and physiological demands of a load carriage and tactical mobility task and examined their differences between sexes using reliable and validated wearables among United States Marine officer candidates. METHODS:Forty-one candidates (16 women) performed a 15.8-km loaded ruck march and a 4.0-km endurance course that assessed load carriage and tactical mobility performance, respectively. Inertial measurement units on the distal tibia and wrist-worn watches collected biomechanical (total step count, impact load, bone stimulus, average intensity, low-/medium-/high-g step count) and physiological (heart rate (HR mean , HR min , HR max ), physical activity energy expenditure (PAEE), and metabolic equivalent (MET mean )) data. Paired sample t -tests compared metrics between events. Principal component (PC) analyses interpreted event demands. Independent samples t -tests analyzed sex differences between PCs ( α = 0.05). RESULTS:Impact load (+1259.70 g ·min -1 , P < 0.001), average intensity (+7.20 g , P < 0.001), bone stimulus (+126.73 AU, P < 0.001), high- g steps (+559.34 g , P < 0.001), HR min (+13.15 bpm, P < 0.001), HR mean (+28.79 bpm, P < 0.001), HR max (+16.95 bpm, P < 0.001), and MET mean (-1.93 kcal·kg -1 ·h -1 , P < 0.001) were higher during the endurance course than the ruck; step count (-14,934, P < 0.001) and PAEE (-713 kcal, P < 0.001) were lower. Three PCs explained 84.3% and 81.5% of variance for the ruck and endurance course. PC1 represented biomechanical variables, PC2 physiological variables, and PC3 g step count. Sex differences were found in PC2 ( P = 0.039) and PC3 ( P = 0.002) for the ruck, and PC3 ( P < 0.01) for the endurance course revealing greater demands on women. CONCLUSIONS:Tactical mobility requires greater biomechanical and physiological demands than load carriage and places greater demands on women. Task and sex-specific training strategies may improve performance and mitigate MSKI risk.

PURPOSE:Optimal performance in military tasks is crucial for operational success. These tasks are often simulated in training, assessing personnel performance within a military environment. However, these assessments are time-consuming and a potential injury risk. Physical characteristics such as muscular strength, power, aerobic endurance, and circumferences can be used to predict these dynamic and demanding tasks. Utilizing machine learning models to predict assessment outcomes may lead to optimized management of personnel, time, and interventions in the military. METHODS:This study recruited 35 participants to complete two physical sessions assessing multiple physical characteristics and lift-to-place and jerry-can-carry assessments. Machine learning models were developed to predict assessment outcomes based on a down-selection of physical characteristics metrics. Root mean square error (RMSE), normalized root mean square error (NRMSE), and coefficient of variation of the root mean square error (CVRMSE) were used to evaluate the models' predictive capabilities. RESULTS:The support vector regression (SVR) and ridge models could predict the lift-to-place outcome to an RMSE of ±1.77 kg (NRMSE = 4.44%, CVRMSE = 0.18) and ±2.33 kg (NRMSE = 5.84%; CVRMSE = 0.24) with four and three physical tests, respectively. The multilayer perceptron and SVR models predicted the jerry-can-carry outcome to ±3.36 laps (NRMSE = 23.06%, CVRMSE = 0.39) and ±3.67 laps (NRMSE = 25.20%, CVRMSE = 0.42) with 12 and 8 physical tests, respectively. CONCLUSIONS:The lift-to-place outcome can be accurately predicted, showing potential military implementation. The jerry-can-carry outcome shows promise; however, further model optimization and training metrics are required to reduce error. Machine learning models demonstrate their applicability to optimize occupational selection pathways and training interventions for desirable performance in military settings.

ABSTRACT:Rosenblum, LJ, Lovalekar, M, Martin, BJ, Feigel, ED, Mroz, KH, McCarthy, AM, Koltun, KJ, Stefl, TJ, Forse, JN, Doyle, TLA, and Nindl, BC. Assessing agreement in lower body joint inter-limb asymmetries in isometric, dynamic, and loaded conditions. J Strength Cond Res 40(3): 283-292, 2026-Interlimb asymmetry (ILA) for static and dynamic movements can indicate aberrant musculoskeletal and neuromuscular function. The purpose of this analysis was to measure ILA agreement in different isometric, dynamic, and loaded conditions at the ankle, knee, and hip, for single-joint and lower-body ILA; to assess the effect of a load on kinetic and kinematic ILA during jumps; and to evaluate the effect of physiological fatigue on gait ILA. Twenty-two men (30.2 ± 5.0 years, 1.8 ± 0.08 m, 85.6 ± 10.0 kg, 16.9 ± 5.4% body fat) participated in ankle, knee, hip, and lower-body assessments of relative (N·kg-1) and peak isometric strength (N); dynamic peak range of motion (º) and dynamic peak forces (N) without and with load (9.7 kg); and tibial impact (g) during aerobic capacity tests (pre- and at-fatigue). Agreements between ILA (≥10% vs. <10%) were calculated using different variables and assessed across different formulae through Kappa coefficients (κ). The difference in ILA with and without load, and pre- and at-fatigue, was analyzed using paired t-tests (α = 0.05). An analysis of single-joint ILA showed good agreement between the formulae (κ range: 0.412-1.00, p values: 0.045-<0.001), but poor agreement with lower-body ILA. Load increased ILA in both countermovement and drop jumps, whereas physiological fatigue did not. This research estimated normative baseline ILAs for military personnel and showed that ILA is a task-, metric-, and joint-specific measurement.

Introduction Assessing kinematic information within military populations can assist in optimizing physical performance and identifying inefficient movement patterns patterns as part of a regular health screening. The HumanTrak is a portable markerless motion capture system capable of quantifying lower body kinematics within field-based settings. The literature to support HumanTrak validity is novel and has not been assessed in a military context. Valid data under specific military conditions are required to support the use of the HumanTrak device within a military setting in order to validate the findings in this unique population. Material and Methods The validity of the HumanTrak was examined in 17 individuals who completed lower body frontal and sagittal plane tasks at the hip and knee (Protocol Number: 52022787737978). Tasks were performed with and without body armor being worn. All tasks were assessed for peak angles and range of motion outputs from 3 repetitions in a laboratory. HumanTrak outputs were compared to a gold-standard methodology (marker-based motion capture). Standard error of measurement, intraclass correlations, Bland-Altman Plots, and Pearson Correlations of each system’s lower body kinematic outputs were calculated. Results The results generally showed good validity between the systems’ outputs for most movement tasks. Overall, low absolute measures of error for all tasks were observed, indicating that the HumanTrak can accurately measure lower body kinematics with minimal error. Besides hip flexion, minimal validity differences were seen between the body armor and no body armor conditions. Conclusion The HumanTrak’s validity results suggest it provides a valid and accurate representation of lower body kinematics, making it useful for military and sports science applications. Practitioners can confidently use the HumanTrak to quantify lower body kinematics without requiring a sterile laboratory environment, like a gymnasium setting.

This investigation assessed the effect of gradient and duration on the gait variability exponent, DFA-α, in military personnel affixed with dual inertial measurement units performing a load carriage time-trial. Gait data (N = 14) were partitioned into 256 stride time segments by gradient (uphill, downhill) using a gait event algorithm. Detrended fluctuation analysis calculated DFA-α per segment, which was averaged across one-third durations (phases 1-3) per gradient. Two-way repeated measures ANOVA examined effects of gradient, duration, and interaction on DFA-α, with Bonferroni-adjusted post-hoc comparisons. There was a significant main effect of duration (phase 1: 0.593 ± 0.021; phase 2: 0.563 ± 0.031; phase 3: 0.493 ± 0.021; F = 3.833, p = 0.035, ηp2 = 0.228), but not gradient (uphill: 0.486 ± 0.031; downhill: 0.614 ± 0.035; F = 4.252, p = 0.060, ηp2 = 0.246), or interaction (F = 0.019, p = 0.981, ηp2 = 0.001). Pairwise comparisons revealed significantly lower DFA-α during phase 3 than phase 1 (p = 0.016). Elapsed duration and uphill gradient, despite a large, but non-significant effect, may represent factors altering gait variability for injury risk.

The ability to estimate lower-extremity mechanics in real-world scenarios may untether biomechanics research from a laboratory environment. This is particularly important for military populations where outdoor ruck marches over variable terrain and the addition of external load are cited as leading causes of musculoskeletal injury As such, this study aimed to examine (1) the validity of a minimal IMU sensor system for quantifying lower-extremity kinematics during treadmill walking and running compared with optical motion capture (OMC) and (2) the sensitivity of this IMU system to kinematic changes induced by load, grade, or a combination of the two. The IMU system was able to estimate hip and knee range of motion (ROM) with moderate accuracy during walking but not running. However, SPM analyses revealed IMU and OMC kinematic waveforms were significantly different at most gait phases. The IMU system was capable of detecting kinematic differences in knee kinematic waveforms that occur with added load but was not sensitive to changes in grade that influence lower-extremity kinematics when measured with OMC. While IMUs may be able to identify hip and knee ROM during gait, they are not suitable for replicating lab-level kinematic waveforms.

Objective The purpose of this meta-analytic review is to examine the relationship between increased psychological pressure and Use of Force (UOF) behaviours, identifying current training methodologies and effectiveness of transfer of training interventions in high threat-simulated scenarios. Background Data from UOF performance within Law Enforcement indicates a low transfer of marksmanship training into real-world UOF, resulting in unnecessary damage to property, personal injury and increased risk to loss of life. This meta-analysis examines both the impact of increased pressure and current training interventions. Method A meta-analysis was conducted across a wide range of published research to answer the primary research questions. Results Increased levels of perceived pressure demonstrated an average decrease in marksmanship accuracy of 14.8%, together with a small increase in incorrect Decision Making (DM) and faster reaction Times (RT). Experience demonstrated a mitigating effect for pressure for marksmanship with a 1.1% increase for every one year of service but no effect on DM or RT. Training interventions utilizing a variety of early contextually relevant exposures to increased pressure improved performance over traditional training on average by 10.6%. Conclusion The outcomes illustrate the negative effect of pressure on marksmanship and UOF behaviours, and that early exposure to contextually relevant pressure may increase the transfer of training to real-world performance. Application Occupational experience is an important component in reducing the impact of pressure on UOF performance, and transfer of training may be enhanced through training methodologies that combine early exposure to contextually relevant pressure, that may replicate the benefits of experience.

This study investigated the relationships between inertial measurement unit (IMU) acceleration at multiple body locations and 3D motion capture impact landing measures in runners. Thirty healthy runners ran on an instrumented treadmill at five running speeds (9-17 km/h) during 3D motion capture. Axial and resultant acceleration were collected from IMUs at the distal and proximal tibia, distal femur and sacrum. Relationships between peak acceleration from each IMU location and patellofemoral joint (PFJ) peak force and loading rate, impact peak and instantaneous vertical loading rate (IVLR) were investigated using linear mixed models. Acceleration was positively related to IVLR at all lower limb locations (p < 0.01). Models predicted a 1.9-3.2 g peak acceleration change at the tibia and distal femur, corresponding with a 10% IVLR change. Impact peak was positively related to acceleration at the distal femur only (p < 0.01). PFJ peak force was positively related to acceleration at the distal (p = 0.03) and proximal tibia (p = 0.03). PFJ loading rate was positively related to the tibia and femur acceleration in males only (p < 0.01). These findings suggest multiple IMU lower limb locations are viable for measuring peak acceleration during running as a meaningful indicator of IVLR.