Dataset Information

Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward Lunge.

ABSTRACT: Purpose:Modern statistics and higher computational power have opened novel possibilities to complex data analysis. While gait has been the utmost described motion in quantitative human motion analysis, descriptions of more challenging movements like the squat or lunge are currently lacking in the literature. The hip and knee joints are exposed to high forces and cause high morbidity and costs. Pre-surgical kinetic data acquisition on a patient-specific anatomy is also scarce in the literature. Studying the normal inter-patient kinetic variability may lead to other comparable studies to initiate more personalized therapies within the orthopedics. Methods:Trials are performed by 50 healthy young males who were not overweight and approximately of the same age and activity level. Spatial marker trajectories and ground reaction force registrations are imported into the Anybody Modeling System based on subject-specific geometry and the state-of-the-art TLEM 2.0 dataset. Hip and knee joint reaction forces were obtained by a simulation with an inverse dynamics approach. With these forces, a statistical model that accounts for inter-subject variability was created. For this, we applied a principal component analysis in order to enable variance decomposition. This way, noise can be rejected and we still contemplate all waveform data, instead of using deduced spatiotemporal parameters like peak flexion or stride length as done in many gait analyses. In addition, this current paper is, to the authors' knowledge, the first to investigate the generalization of a kinetic model data toward the population. Results:Average knee reaction forces range up to 7.16 times body weight for the forwarded leg during lunge. Conversely, during squat, the load is evenly distributed. For both motions, a reliable and compact statistical model was created. In the lunge model, the first 12 modes accounts for 95.26% of inter-individual population variance. For the maximal-depth squat, this was 95.69% for the first 14 modes. Model accuracies will increase when including more principal components. Conclusion:Our model design was proved to be compact, accurate, and reliable. For models aimed at populations covering descriptive studies, the sample size must be at least 50.

SUBMITTER: De Roeck J

PROVIDER: S-EPMC7142215 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward Lunge.

De Roeck Joris J Van Houcke J J Almeida D D Galibarov P P De Roeck L L Audenaert Emmanuel A EA

Frontiers in bioengineering and biotechnology 20200402

<h4>Purpose</h4>Modern statistics and higher computational power have opened novel possibilities to complex data analysis. While gait has been the utmost described motion in quantitative human motion analysis, descriptions of more challenging movements like the squat or lunge are currently lacking in the literature. The hip and knee joints are exposed to high forces and cause high morbidity and costs. Pre-surgical kinetic data acquisition on a patient-specific anatomy is also scarce in the liter ...[more]

PMID: 32300586

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Project description:Static lower extremity alignment (LEA) during normal stance has been used clinically as a tool to determine the presence of known anterior cruciate ligament (ACL) risk factors during dynamic tasks. Previous work investigating the relationship between static LEA during normal stance and risk factors for ACL injury is limited by the use of imprecise methods or because it focuses on knee valgus only and no other potentially important variables. The aim of this investigation was to determine the relationships between static LEA and the corresponding LEA during drop landings. Forty-one female athletes were recruited for the study (age: 19.8 ± 2.5 years, height: 1.73 ± 0.06 m, mass: 64.03 ± 6.66 kg). Lower limb kinematic data were collected using a 10 camera infrared motion capture system (500 Hz) with retro-reflective markers placed over key anatomical landmarks. This system was linked to two force platforms (1000 Hz) with subsequent three-dimensional kinematic and kinetic data developed using standard software (Visual3D). Following an appropriate warm-up, data collection involved participants standing with their arms partially abducted to record static LEA. This was following by a series of drop landings from a 0.4 m box onto the force platforms. Maximum LEA data during drop landings were then compared with static LEA. Analyses showed that in comparison to static stance, during landings the anterior tilt of the pelvis decreased while hip abduction and knee internal rotation increased. At best, static LEA variables were moderately correlated (r = -0.51 to 0.58) with peak values measured during drop landings. Additionally, regression analysis did not yield any significant predictors of any key peak hip or knee variables measured during drop landings (p = 0.15 to 0.89). When combined, the poor relationships observed between kinematics during static LEA and LEA during drop landings calls into question the practice of using static measures to predict LEA during even simple landing tasks. These findings suggest static assessments of LEA may have minimal value as an ACL injury screening tool.

Project description:BackgroundSymmetry during lifting is considered critical for allowing balanced power production and avoidance of injury. This investigation assessed the influence of elevating the heels on bilateral lower limb symmetry during loaded (50% of body weight) high-bar back squats.MethodsTen novice (mass 67.6 ± 12.4 kg, height 1.73 ± 0.10 m) and ten regular weight trainers (mass 66.0 ± 10.7 kg, height 1.71 ± 0.09 m) were assessed while standing on both the flat level floor and on an inclined board. Data collection used infra-red motion capture procedures and two force platforms to record bilateral vertical ground reaction force (GRFvert) and ankle, knee and hip joint kinematic and kinetic data. Paired t-tests and statistical parametric mapping (SPM1D) procedures were used to assess differences in discrete and continuous bilateral symmetry data across conditions.ResultsAlthough discrete joint kinematic and joint moment symmetry data were largely unaffected by raising the heels, the regular weight trainers presented greater bilateral asymmetry in these data than the novices. The one significant finding in these discrete data showed that raising the heels significantly reduced maximum knee extension moment asymmetry (P = 0.02), but in the novice group only. Time-series analyses indicated significant bilateral asymmetries in both GRFvert and knee extension moments mid-way though the eccentric phase for the novice group, with the latter unaffected by heel lift condition. There were no significant bilateral asymmetries in time series data within the regular weight training group.ConclusionsThis investigation highlights that although a degree of bilateral lower limb asymmetry is common in individuals performing back squats, the degree of this symmetry is largely unaffected by raising the heels. Differences in results for discrete and time-series symmetry analyses also highlight a key issue associated with relying solely on discrete data techniques to assess bilateral symmetry during tasks such as the back squat.

Project description:BackgroundRegarding their skill levels, badminton players present different movement patterns during front and right lunging. The main objective of this study was to compare the mechanical energy transfers attributable to right-forward lunges between amateur and professional badminton players to study variations in mechanical efficiency at various skill levels.MethodIn this cross-sectional study, twenty female badminton players were recruited (Professional group n = 10 and Amateur group n = 10). The kinematics and kinetics of the lower extremities were recorded while performing right-forward lunges using Vicon motion capture and Kistler force plates. Mechanical energy expenditures (MEE) were extracted in eccentric transfer, concentric transfer, and no-transfer phases for the hip, knee, and ankle joints. At each joint, mechanical energy compensations (MEC) were also determined. Independent samples t-tests were used to analyze data at a significance level of α = 0.05.ResultRegards to mechanical energy expenditures at the initial heel contact phase, the professional players demonstrated statistically significant more ankle no-transfer (p < 0.003), less knee concentric transfer (p < 0.026), more knee eccentric transfer (p < 0.001), and less hip no-transfer (p < 0.001). At the same time, the amateur athletes showed significantly more ankle eccentric transfer (p < 0.042) at maximal knee flexion angle time point. Analyzing mechanical energy compensation coefficients showed that the professional athletes had significantly less ankle concentric transfer (p < 0.001), more knee concentric transfer (p < 0.001), more knee eccentric transfer (p < 0.001), and more hip eccentric transfer (p < 0.001) at initial contact phase. While they found to have significantly more ankle eccentric transfer (p < 0.007), less knee concentric transfer (p < 0.001), less knee eccentric transfer (p < 0.001), more hip concentric transfer (p < 0.001), and more hip eccentric transfer (p < 0.001) at maximal knee flexion angle.Conclusionit is shown that the mechanical energy efficiency of the right-forward lunge is skill-related. It seems that altered lunge landing biomechanics may increase the risk of ankle and knee injuries and muscular damages in amateur athletes. It is recommended for amateur players to follow a injury prevention training program that promotes proper lunging technique.

Dataset Information

Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward Lunge.

Publications

Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward Lunge.

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