Validation of a commercially available markerless motion-capture system for trunk and lower extremity kinematics during a jump-landing assessment

Context: Field-based, portable motion-capture systems can be used to help identify individuals at greater risk of lower extremity injury. Microsoft Kinect-based markerless motion-capture systems meet these requirements; however, until recently, these systems were generally not automated, required substantial data postprocessing, and were not commercially available. Objective: To validate the kinematic measures of a commercially available markerless motion-capture system. Design: Descriptive laboratory study. Setting: Laboratory. Patients or Other Participants: A total of 20 healthy, physically active university students (10 males, 10 females; age ¼ 20.50 6 2.78 years, height ¼ 170.36 6 9.82 cm, mass ¼ 68.38 6 10.07 kg, body mass index ¼ 23.50 6 2.40 kg/m2). Intervention(s): Participants completed 5 jump-landing trials. Kinematic data were simultaneously recorded using Kinect-based markerless and stereophotogrammetric motion-capture systems. Main Outcome Measure(s): Sagittal- and frontal-plane trunk, hip-joint, and knee-joint angles were identified at initial ground contact of the jump landing (IC), for the maximum joint angle during the landing phase of the initial landing (MAX), and for the joint-angle displacement from IC to MAX (DSP). Outliers were removed, and data were averaged across trials. We used intraclass correlation coefficients (ICCs [2,1]) to assess intersystem reliability and the paired-samples t test to examine mean differences (a < .05). Results: Agreement existed between the systems (ICC range ¼1.52 to 0.96; ICC average ¼ 0.58), with 75.00% (n ¼ 24/ 32) of the measures being validated (P < .05). Agreement was better for sagittal- (ICC average ¼ 0.84) than frontal- (ICC average ¼ 0.35) plane measures. Agreement was best for MAX (ICC average ¼ 0.77) compared with IC (ICC average ¼ 0.56) and DSP (ICC average ¼ 0.41) measures. Pairwise comparisons identified differences for 18.75% (6/32) of the measures. Fewer differences were observed for sagittal- (0.00%; 0/15) than for frontal- (35.29%; 6/17) plane measures. Between-systems differences were equivalent for MAX (18.18%; 2/11), DSP (18.18%; 2/11), and IC (20.00%; 2/10) measures. The markerless system underestimated sagittal-plane measures (86.67%; 13/15) and overestimated frontal-plane measures (76.47%; 13/ 17). No trends were observed for overestimating or underestimating IC, MAX, or DSP measures. Conclusions: Moderate agreement existed between markerless and stereophotogrammetric motion-capture systems. Better agreement existed for larger (eg, sagittal-plane, MAX) than for smaller (eg, frontal-plane, IC) joint angles. The DSP angles had the worst agreement. Markerless motion-capture systems may help clinicians identify individuals at greater risk of lower extremity injury

Solar-Cycle Characteristics Examined in Separate Hemispheres: Phase, Gnevyshev Gap, and Length of Minimum

Research results from solar-dynamo models show the northern and southern hemispheres may evolve separately throughout the solar cycle. The observed phase lag between the hemispheres provides information regarding the strength of hemispheric coupling. Using hemispheric sunspot-area and sunspot-number data from Cycles 12 - 23, we determine how out of phase the separate hemispheres are during the rising, maximum, and declining period of each solar cycle. Hemispheric phase differences range from 0 - 11, 0 - 14, and 2 - 19 months for the rising, maximum, and declining periods, respectively. The phases appear randomly distributed between zero months (in phase) and half of the rise (or decline) time of the solar cycle. An analysis of the Gnevyshev gap is conducted to determine if the double-peak is caused by the averaging of two hemispheres that are out of phase. We confirm previous findings that the Gnevyshev gap is a phenomenon that occurs in the separate hemispheres and is not due to a superposition of sunspot indices from hemispheres slightly out of phase. Cross hemispheric coupling could be strongest at solar minimum, when there are large quantities of magnetic flux at the Equator. We search for a correlation between the hemispheric phase difference near the end of the solar cycle and the length of solar-cycle minimum, but found none. Because magnetic flux diffusion across the Equator is a mechanism by which the hemispheres couple, we measured the magnetic flux crossing the Equator by examining magnetograms for Solar Cycles 21 - 23. We find, on average, a surplus of northern hemisphere magnetic flux crossing during the mid-declining phase of each solar cycle. However, we find no correlation between magnitude of magnetic flux crossing the Equator, length of solar minima, and phase lag between the hemispheres.Comment: 15 pages, 7 figure

Trunk and lower extremity movement patterns, stress fracture risk factors, and biomarkers of bone turnover in military trainees

Context: Military service members commonly sustain lower extremity stress fractures (SFx). How SFx risk factors influence bone metabolism is unknown. Understanding how SFx risk factors influence bone metabolism may help to optimize risk-mitigation strategies. Objective: To determine how SFx risk factors influence bone metabolism. Design: Cross-sectional study. Setting: Military service academy. Patients or Other Participants: Forty-five men (agepre ¼ 18.56 6 1.39 years, heightpre ¼ 176.95 6 7.29 cm, masspre ¼ 77.20 6 9.40 kg; body mass indexpre ¼ 24.68 6 2.87) who completed Cadet Basic Training (CBT). Individuals with neurologic or metabolic disorders were excluded. Intervention(s): We assessed SFx risk factors (independent variables) with (1) the Landing Error Scoring System (LESS), (2) self-reported injury and physical activity questionnaires, and (3) physical fitness tests. We assessed bone biomarkers (dependent variables; procollagen type I amino-terminal propeptide [PINP] and cross-linked collagen telopeptide [CTx-1]) via serum. Main Outcome Measure(s): A markerless motion-capture system was used to analyze trunk and lower extremity biomechanics via the LESS. Serum samples were collected post-CBT; enzyme-linked immunosorbent assays determined PINP and CTx-1 concentrations, and PINP: CTx-1 ratios were calculated. Linear regression models demonstrated associations between SFx risk factors and PINP and CTx-1 concentrations and PINP: CTx-1 ratio. Biomarker concentration mean differences with 95% confidence intervals were calculated. Significance was set a priori using a ≤ .10 for simple and a ≤ .05 for multiple regression analyses. Results: The multiple regression models incorporating LESS and SFx risk factor data predicted the PINP concentration (R2 ¼ 0.47, P ¼ .02) and PINP: CTx-1 ratio (R2 ¼ 0.66, P ¼ .01). The PINP concentration was increased by foot internal rotation, trunk flexion, CBT injury, sit-up score, and pre- to post-CBT mass changes. The CTx-1 concentration was increased by heel-to-toe landing and post-CBT mass. The PINP: CTx-1 ratio was increased by foot internal rotation, lower extremity sagittal-plane displacement (inversely), CBT injury, sit-up score, and pre- to post-CBT mass changes. Conclusions: Stress fracture risk factors accounted for 66% of the PINP: CTx-1 ratio variability, a potential surrogate for bone health. Our findings provide insight into how SFx risk factors influence bone health. This information can help guide SFx risk-mitigation strategies

Biomechanical risk factors for lower extremity stress fracture

Objectives: Stress fracture injuries disproportionately affect athletes and military service members and little is known about the modifiable biomechanical risk factors associated with these injuries. The purpose of this study was to prospectively examine the association between neuromuscular and biomechanical factors upon entry to military service and the subsequent incidence of lower-extremity stress fracture injury during four years of follow-up. Methods: We analyzed data from the JUMP-ACL cohort, an existing prospective cohort study of military cadets. JUMP-ACL conducted detailed motion analysis during a jump landing task at the initiation of each subject’s military career. We limited our analyses to the class years 2009-2013 (i.e., subjects who completed baseline testing in 2005-2008). There were 1895 subjects available for analysis. Fifty-two subjects reported a history of stress fracture at baseline and were excluded from further analysis leaving 1843 subjects. Incident lower extremity-stress fracture cases were identified through the Defense Medical Surveillance System and the Cadet Injury and Illness Tracking System during the follow-up period. The electronic medical records of each potential incident case were reviewed and each case was confirmed by an adjudication committee consisting of two sports medicine fellowship trained orthopaedic surgeons. The primary outcome of interest was the incidence rate of lower-extremity stress fracture during the follow-up period. The association between incident stress fracture and sagittal, frontal, and transverse plane hip and knee kinematics during the jump-landing task were examined at initial contact (IC), 15%(T15), 50%(T50), 85%(T85) and 100%(T100) of stance phase. Descriptive plots of all biomechanical variables along with 95% confidence intervals (CI) were generated during the stance phase of the jump landing task. Univariate and multivariable Poisson regression models were used to estimate the association between baseline biomechanical factors and the incidence rate of lower-extremity stress fracture during follow-up. Results: Overall, 94 (5.1%, 95%CI: 4.14, 6.21) subjects sustained an incident stress fracture during the follow-up period. The incidence rate for stress fracture injuries among females was nearly three times greater when compared to males (IRR=2.86, 95%CI: 1.88, 4.34, p<0.001). Compared to those with greater than 5° of knee valgus, subjects with neutral or varus knee alignment experienced incidence rates for stress fracture that were 43%-53% lower at IC (IRR=0.57, 95%CI: 0.29, 1.11, p=0.10), T50 (IRR=0.47, 95%CI=0.23, 1.00, p=0.05), and T85 (IRR=0.53, 95%CI: 0.29, 0.98, p=0.04). Subjects with greater than 5° of internal knee rotation exhibited rates for stress fracture that were 2-4 times higher at T15 (IRR=2.31, 95%CI: 1.01, 5.27, p=0.05), T50 (IRR=3.98, 95%CI: 0.99, 16.00, p=0.05), and T85 (IRR=2.31, 95%CI: 0.86, 6.23, p=0.10), when compared to those with neutral or external knee rotation alignment. Conclusion: Several potentially modifiable biomechanical factors at the time of entry into military service appear to be associated with the subsequent rate of stress fracture. It is possible that injury prevention programs targeted to address these biomechanical movement patterns may reduce the risk of stress fracture injury in athletes and military service members

Automated Landing Error Scoring System Performance and the Risk of Bone Stress Injury in Military Trainees

Context: Lower extremity bone stress injuries (BSIs) place a significant burden on the health and readiness of the US Armed Forces. Objective: To determine if preinjury baseline performance on an expanded and automated 22-item version of the Landing Error Scoring System (LESS-22) was associated with the incidence of BSIs in a military training population. Design: Prospective cohort study. Setting: US Military Academy at West Point, NY. Patients or Other Participants: A total of 2235 incoming cadets (510 females [22.8%]). Main Outcome Measure(s): Multivariable Poisson regression models were used to produce adjusted incidence rate ratios (IRRs) to quantify the association between preinjury LESS scores and BSI incidence rate during follow-up and were adjusted for pertinent risk factors. Risk factors were included as covariates in the final model if the 95% CI for the crude IRR did not contain 1.00. Results: A total of 54 BSIs occurred during the study period, resulting in an overall incidence rate of 0.07 BSI per 1000 person-days (95% CI = 0.05, 0.09). The mean number of exposure days was 345.4 6 61.12 (range = 3–368 days). The final model was adjusted for sex and body mass index and yielded an adjusted IRR for a LESS-22 score of 1.06 (95% CI = 1.002, 1.13; P = .04), indicating that each additional LESS error documented at baseline was associated with a 6.0% increase in the incidence rate of BSI during the follow-up period. In addition, 6 individual LESS-22 items, including 2 newly added items, were significantly associated with the BSI incidence. Conclusions: We provided evidence that performance on the expanded and automated version of the LESS was associated with the BSI incidence in a military training population. The automated LESS-22 may be a scalable solution for screening military training populations for BSI risk

Influence of Concussion Education Exposure on Concussion-Related Educational Targets and Self-Reported Concussion Disclosure among First-Year Service Academy Cadets

Concussion disclosure is often essential for military personnel to receive appropriate care following concussive injury. Concussion-related education and training may play a role in improving disclosure and recognition among peers, allowing for more timely concussion identification and treatment. The objectives of this study were to: (1) describe concussion education exposure among first-year service academy cadets and (2) examine the association between exposure to concussion education sources (multiple vs. only one) and concussion-related knowledge, attitudes, perceived social norms, intention to disclose symptoms, and disclosure behaviors. Materials and Methods: First-year service academy cadets completed a cross-sectional survey to assess perceptions of concussion disclosure during preseason concussion baseline testing sessions. Associations between key cadet characteristics and exposure to multiple concussion education sources were examined using odds ratios and 95% confidence intervals. Linear regression was used to model the continuous measures of concussion-related knowledge, attitudes, and perceived social norms. Log-binomial regression was used to model the categorical outcomes of high perceived control over concussion disclosure (higher vs. lower), intention to disclose (higher vs. lower), and disclosure of all possible concussive events at the time of injury (yes vs. no). The primary predictor for all models was exposure to multiple sources of concussion education (video, coach, medical professional, or other) vs. exposure to only one educational source. All models were adjusted for gender, high school contact sport participation, and previous concussion history. Results: Of the 972 first-year cadets (85% response; age = 18.4 ± 0.9 years; 21.7% female, 29.0% NCAA student-athlete), 695 (71.5%) reported receiving some type of previous concussion education and 229 (23.6%) reported a previous concussion history (206/229 reported the actual number they experienced). Of those reporting previous concussion-related education (n = 695), 542 (78.0%) watched a video, 514 (74.0%) talked with a coach about concussion, 433 (62.3%) talked with a medical professional, and 61 (8.8%) reported other sources of education ranging from anatomy teachers to brochures. Overall, 527 (75.8%) reported receiving more than one source of concussion education. Having played a contact sport in high school and having a history of concussion were associated with having multiple concussion education exposures. Being female was associated with lower odds of multiple exposures. Exposure to multiple sources of concussion education was not associated with knowledge, attitudes, perceived norms, or higher intention to disclose concussion symptoms. However, among those with a concussion history, exposure to multiple sources of concussion education was associated with a nearly 40% higher prevalence of disclosing all concussions at the time of injury compared to only one source of educational exposure (67.1% vs. 48.3%; prevalence ratio = 1.4; 95% confidence interval: 0.9, 2.1). Thus, although multiple sources of education may not influence intermediate variables of knowledge, attitudes, perceived norms and intentions, exposure to multiple sources of concussion education may influence actual decision-making around concussion disclosure among first-year service academy cadets. Conclusion: These data suggest disparities in concussion education exposure that can be addressed in first-year cadets. Additionally, findings support the importance and use of multiple sources of concussion education in improving cadet's concussion-related decision-making