The Components of Lumbar Motor Control Are Not Inter-related.

OBJECTIVES: To verify the relationship between the indicators of components of lumbar motor control and determine the factors related to the indicators to each of these components. METHODS: Twenty-five healthy university students were included in the study. The lumbar spine and hip kinematic parameters of posterior/anterior pelvic tilt (mobility and smoothness), ball catching (reactivity), and forward/backward rocking (adaptive stability) were measured as indicators of lumbar motor control. Lumbar proprioception, trunk muscle strength, and lower trunk muscle thickness were also measured. Kinematic parameters of the lumbar spine and hip were measured using a small accelerometer. The data verified the relevance of indicators of lumbar motor control and the relationship with relevant factors. RESULTS: No significant correlations were found for most lumbar motor control indicators. Lumbar proprioception and rectus abdominis muscle thickness were identified as relevant indicators of lumbar motor control. CONCLUSIONS: Each component of lumbar motor control is independent and must be evaluated for the component whose function is required. Additionally, some components of lumbar motor control are associated with lumbar proprioception and rectus abdominis muscle thickness; thus, evaluation of these components is necessary when evaluating lumbar motor control.

Force Production Measurements During a Supine Medicine Ball Throw: a Reliability and Correlation Study.

OBJECTIVES: This study aimed to examine the reliability of supine medicine ball throw peak force and rate of force development (RFD) measurements. A secondary aim was to investigate the correlations between these measurements and vertical jump height. METHODS: Twenty young women (21±3 years) reported for experimental testing on two different occasions. Supine medicine ball throw assessments were performed during each testing session to assess peak force, RFDmax, and RFD at specific percentages of peak force (RFD30% and RFD40-80%). Vertical jumps were performed on a jump mat. The jump mat measured vertical jump height based on flight time. RESULTS: Good intraclass correlation coefficients (≥0.82) and coefficients of variation (≤14.0%) were observed between sessions for peak force, RFDmax, and RFD40-80%, but not for RFD30% (0.55, 27.2%). There were significant correlations between jump height and peak force (r=0.483, P=0.031), RFDmax (r=0.484, P=0.031), and RFD40-80% (r=0.491, P=0.028). There was no significant correlation between jump height and RFD30% (r=0.359, P=0.120). CONCLUSIONS: Our results showed that supine medicine ball throw peak force, RFDmax, and RFD40-80% were reliable measures for assessing upper-body explosive strength in young adults. These measurements were significantly associated with vertical jump height and therefore, may be effective predictors of one's athletic ability.

A comprehensive dataset on biomechanics and motor control during human walking with discrete mechanical perturbations.

Background: Humans have a remarkable capability to maintain balance while walking. There is, however, a lack of publicly available research data on reactive responses to destabilizing perturbations during gait. Methods: Here, we share a comprehensive dataset collected from 10 participants who experienced random perturbations while walking on an instrumented treadmill. Each participant performed six 5-min walking trials at a rate of 1.2 m/s, during which rapid belt speed perturbations could occur during the participant's stance phase. Each gait cycle had a 17% probability of being perturbed. The perturbations consisted of an increase of belt speed by 0.75 m/s, delivered with equal probability at 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% of the stance phase. Data were recorded using motion capture with 25 markers, eight inertial measurement units (IMUs), and electromyography (EMG) from the tibialis anterior (TA), soleus (SOL), lateral gastrocnemius (LG), rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), and gluteus maximus (GM). The full protocol is described in detail. Results: We provide marker trajectories, force plate data, EMG data, and belt speed information for all trials and participants. IMU data is provided for most participants. This data can be useful for identifying neural feedback control in human gait, biologically inspired control systems for robots, and the development of clinical applications.

Compositional, Structural, and Biomechanical Properties of Three Different Soft Tissue-Hard Tissue Insertions: A Comparative Review.

Connective tissue attaches to bone across an insertion with spatial gradients in components, microstructure, and biomechanics. Due to regional stress concentrations between two mechanically dissimilar materials, the insertion is vulnerable to mechanical damage during joint movements and difficult to repair completely, which remains a significant clinical challenge. Despite interface stress concentrations, the native insertion physiologically functions as the effective load-transfer device between soft tissue and bone. This review summarizes tendon, ligament, and meniscus insertions cross-sectionally, which is novel in this field. Herein, the similarities and differences between the three kinds of insertions in terms of components, microstructure, and biomechanics are compared in great detail. This review begins with describing the basic components existing in the four zones (original soft tissue, uncalcified fibrocartilage, calcified fibrocartilage, and bone) of each kind of insertion, respectively. It then discusses the microstructure constructed from collagen, glycosaminoglycans (GAGs), minerals and others, which provides key support for the biomechanical properties and affects its physiological functions. Finally, the review continues by describing variations in mechanical properties at the millimeter, micrometer, and nanometer scale, which minimize stress concentrations and control stretch at the insertion. In summary, investigating the contrasts between the three has enlightening significance for future directions of repair strategies of insertion diseases and for bioinspired approaches to effective soft-hard interfaces and other tough and robust materials in medicine and engineering.

Optimizing shoulder elevation assist rate in exoskeletal rehabilitation based on muscular activity indices: a clinical feasibility study.

BACKGROUND: Restoring shoulder function is critical for upper-extremity rehabilitation following a stroke. The complex musculoskeletal anatomy of the shoulder presents a challenge for safely assisting elevation movements through robotic interventions. The level of shoulder elevation assistance in rehabilitation is often based on clinical judgment. There is no standardized method for deriving an optimal level of assistance, underscoring the importance of addressing abnormal movements during shoulder elevation, such as abnormal synergies and compensatory actions. This study aimed to investigate the effectiveness and safety of a newly developed shoulder elevation exoskeleton robot by applying a novel optimization technique derived from the muscle synergy index. METHODS: Twelve chronic stroke participants underwent an intervention consisting of 100 robot-assisted shoulder elevation exercises (10 × 10 times, approximately 40 min) for 10 days (4-5 times/week). The optimal robot assist rate was derived by detecting the change points using the co-contraction index, calculated from electromyogram (EMG) data obtained from the anterior deltoid and biceps brachii muscles during shoulder elevation at the initial evaluation. The primary outcomes were the Fugl-Meyer assessment-upper extremity (FMA-UE) shoulder/elbow/forearm score, kinematic outcomes (maximum angle of voluntary shoulder flexion and elbow flexion ratio during shoulder elevation), and shoulder pain outcomes (pain-free passive shoulder flexion range of motion [ROM] and visual analogue scale for pain severity during shoulder flexion). The effectiveness and safety of robotic therapy were examined using the Wilcoxon signed-rank sum test. RESULTS: All 12 patients completed the procedure without any adverse events. Two participants were excluded from the analysis because the EMG of the biceps brachii was not obtained. Ten participants (five men and five women; mean age: 57.0 [5.5] years; mean FMA-UE total score: 18.7 [10.5] points) showed significant improvement in the FMA-UE shoulder/elbow/forearm score, kinematic outcomes, and pain-free passive shoulder flexion ROM (P < 0.05). The shoulder pain outcomes remained unchanged or improved in all patients. CONCLUSIONS: The study presents a method for deriving the optimal robotic assist rate. Rehabilitation using a shoulder robot based on this derived optimal assist rate showed the possibility of safely improving the upper-extremity function in patients with severe stroke in the chronic phase.

Prediction of specific structural damage to the knee joint using qualitative isokinetic analysis.

BACKGROUND: An isokinetic moment curve (IMC) pattern-damaged structure prediction model may be of considerable value in assisting the diagnosis of knee injuries in clinical scenarios. This study aimed to explore the association between irregular IMC patterns and specific structural damages in the knee, including anterior cruciate ligament (ACL) rupture, meniscus (MS) injury, and patellofemoral joint (PFJ) lesions, and to develop an IMC pattern-damaged structure prediction model. METHODS: A total of 94 subjects were enrolled in this study and underwent isokinetic testing of the knee joint (5 consecutive flexion-extension movements within the range of motion of 90°-10°, 60°/s). Qualitative analysis of the IMCs for all subjects was completed by two blinded examiners. A multinomial logistic regression analysis was used to investigate whether a specific abnormal curve pattern was associated with specific knee structural injuries and to test the predictive effectiveness of IMC patterns for specific structural damage in the knee. RESULTS: The results of the multinomial logistic regression revealed a significant association between the irregular IMC patterns of the knee extensors and specific structural damages ("Valley" - ACL, PFJ, and ACL + MS, "Drop" - ACL, and ACL + MS, "Shaking" - ACL, MS, PFJ, and ACL + MS). The accuracy and Macro-averaged F1 score of the predicting model were 56.1% and 0.426, respectively. CONCLUSION: The associations between irregular IMC patterns and specific knee structural injuries were identified. However, the accuracy and Macro-averaged F1 score of the established predictive model indicated its relatively low predictive efficacy. For the development of a more accurate predictive model, it may be essential to incorporate angle-specific and/or speed-specific analyses of qualitative and quantitative data in isokinetic testing. Furthermore, the utilization of artificial intelligence image recognition technology may prove beneficial for analyzing large datasets in the future.

Relevant Biomechanical Variables in Skateboarding: A Literature Review.

Skateboarding, once regarded primarily as a means of transportation and entertainment for youth, has become a recognized professional sport, gaining global popularity. With its recent inclusion in the Olympics, a growing imperative exists to comprehensively understand biomechanics explaining skateboarding performance. This literature review seeks to consolidate knowledge within this domain, focusing on experimental and modeling studies about skateboard riding and tricks. The criteria for study selection encompassed content relevance and publication year, spanning from the last two decades and extending further back to 1980 following cross-referencing of seminal works. Peer-reviewed journal articles, conference proceedings, and books were considered, with comprehensive searches conducted on electronic databases, including SCOPUS, PubMed, Scielo, and Taylor & Francis. Comprehending the biomechanical facets of skateboarding is essential in promoting its use and ensuring safety among all practitioners. Insights into factors such as body kinetics, kinematics, and muscle activation represent a foundational step toward understanding the nuances of this sport with implications for both clinical and biomechanical research. Modern data collection systems such as inertial measurement units (IMU) and electromyography (EMG) offer unprecedented insights into human performance during skateboarding, such as joint range of motion, coordination, and muscle activation, whether in casual riding or executing complex tricks and maneuvers. Developing robust modeling approaches also holds promise for enhancing skateboarding training and performance. Crucially, these models can serve as the initial framework for understanding injury mechanisms and implementing strategies to improve performance and mitigate injury risks.

Extending the intermedullary nail will not reduce the potential risk of femoral head varus in PFNA patients biomechanically: a clinical review and corresponding numerical simulation.

Femoral head varus is an important complication in intertrochanteric fracture patients treated with proximal femoral nail anti-rotation (PFNA) fixation. Theoretically, extending the length of the intramedullary nail could optimize fixation stability by lengthening the force arm. However, whether extending the nail length can optimize patient prognosis is unclear. In this study, a review of imaging data from intertrochanteric fracture patients with PFNA fixation was performed, and the length of the intramedullary nail in the femoral trunk and the distance between the lesser trochanter and the distal locking screw were measured. The femoral neck varus status was judged at the 6-month follow-up. The correlation coefficients between nail length and femoral neck varus angle were computed, and linear regression analysis was used to determine whether a change in nail length was an independent risk factor for femoral neck varus. Moreover, the biomechanical effects of different nail lengths on PFNA fixation stability and local stress distribution have also been verified by numerical mechanical simulations. Clinical review revealed that changes in nail length were not significantly correlated with femoral head varus and were also not an independent risk factor for this complication. In addition, only slight biomechanical changes can be observed in the numerical simulation results. Therefore, commonly used intramedullary nails should be able to meet the needs of PFNA-fixed patients, and additional procedures for longer nail insertion may be unnecessary.

Effect of using a kinetic wedge during the hallux dorsiflexion resistance test in asymptomatic individuals.

BACKGROUND: The hallux dorsiflexion resistance test is a frequently employed clinical maneuver for assessing the initiation of the windlass mechanism This maneuver involves dorsiflexion of the phalanx of the hallux, thereby evaluating plantarflexion of the first metatarsal, elevation of the medial longitudinal arch, and supination of the rearfoot. The windlass mechanism plays a crucial role in gait, and orthopedic devices, such as a kinetic wedge, which aims to facilitate its activation by increasing the hallux dorsiflexion. Although it is believed that facilitating the windlass mechanism with the kinetic wedge should be directly correlated with a decrease in hallux dorsiflexion resistance, its effects have yet to be characterized. Thus, this study aimed to determine the influence of a kinetic wedge on hallux dorsiflexion resistance in asymptomatic individuals. METHODS: The sample comprised thirty participants (14 women and 16 men). A digital force gauge measured the force required to perform the hallux dorsiflexion resistance test during two conditions: barefoot and with a kinetic wedge. The Wilcoxon signed-rank test was used to compare the hallux dorsiflexion resistance between conditions. RESULTS: A statistically significant reduction in force (10.54 ± 3.16N vs. 19.62 ± 5.18N, p < 0.001) was observed when using the kinetic wedge compared to the barefoot condition during the hallux dorsiflexion resistance test. CONCLUSION: The use of a kinetic wedge reduces the required force for performing the passive hallux dorsiflexion resistance test in asymptomatic individuals. Future studies should determine to what extent the kinetic wedge can attenuate the required force to dorsiflex the hallux in individuals with musculoskeletal disorders such as plantar fasciopathy and functional hallux limitus.

Structural characteristics, biomechanics and clinical significance of calcar femorale: A review.

The calcar femorale, first identified by Merkel in 1874, plays a pivotal role in the weight-bearing capacity of the proximal femur, and its structural integrity is crucial for the efficient distribution of mechanical loads. Originating at the vertical ridge where the pubofemoral ligament anchors, this bony prominence extends laterally behind the neutral axis from the medial to lateral aspects. Its presence is not merely an anatomical curiosity but significantly influences the biomechanics of the hip joint by providing additional strength and support against compressive forces encountered during activities such as walking or jumping. Despite its clear description in orthopedic texts, misconceptions persist about its exact function and importance. This article delves into the nuanced anatomy and biomechanical properties of the calcar femorale, offering a detailed literature-based examination that demonstrates its relevance in clinical practice. The review highlights how the robustness of the calcar femorale contributes to the prevention of femoral neck fractures as well as the stabilization of hip prostheses. Furthermore, the indispensable role of the calcar femorale in surgical outcomes is discussed, especially in the context of fracture repair and joint replacement, thus illustrating its enduring significance in contemporary medical applications.

What is the influence of biomechanical variables on the Y balance test performance in recreational runners?

BACKGROUND: Asymmetries and poor Y balance test (YBT) performance are associated with an increased risk of injuries in athletes. The aim of this study was to investigate the association between YBT performance with biomechanical variables in runners. METHODS: The runners underwent the YBT, followed by the assessment of center of pressure, plank position, muscle strength (MS) of hip flexors, extensors, abductors, and external rotators, knee extensors, ankle dorsiflexion range of motion (ROM), Q angle, forefoot alignment, and passive hip internal rotation. Associations between variables were examined using multiple linear regression models with the Bayesian Information Criterion. RESULTS: 122 cases were analyzed. The R2 values were 0.38; 0.05; 0.06; and 0.15 for the anterior, posteromedial, posterolateral and composite directions models, respectively. The anterior reach in the YBT was associated with ankle dorsiflexion ROM [Sß 95%IC: 0.43 (0.32-0.55)], passive hip internal rotation [Sß 95%IC: 0.35 (0.24-0.47)], MS of the hip extensors [Sß 95%IC: 0.19 (0.07-0.31)] and forefoot alignment [Sß 95%IC: 0.14 (-0.25-0.02)]. The posteromedial and posterolateral reach were associated with MS of the hip flexors [Sß 95%IC: 0.23 (0.09-0.37) and 0.24 (0.11-0.38)], respectively. The composite score was associated with MS of the hip flexors [Sß 95%IC: 0.31 (0.18-0.45)], ankle dorsiflexion ROM [Sß 95%IC: 0.24 (0.10-0.37)] and Q angle [Sß 95%IC: 0.18 (0.04-0.31)]. CONCLUSION: YBT performance in different directions demonstrated specific associations with key biomechanical factors.

Post-error adjustments occur in both reaching and grasping.

Post-error slowing (PES), the tendency to slow down a behavioral response after a previous error, has typically been investigated during simple cognitive tasks using response time as a measure of PES magnitude. More recently, PES was investigated during a single reach-to-grasp task to determine where post-error adjustments are employed in a more ecological setting. Kinematic analyses in the previous study detected PES during pre-movement planning and within the grasping component of movement execution. In the current study (N = 22), we increased the cognitive demands of a reach-to-grasp task by adding a choice between target and distractor locations to further explore PES, and other post-error adjustments, under different task conditions. We observed a significant main effect of task condition on overall reaction time (RT); however, it did not significantly impact PES or other post-error adjustments. Nonetheless, the results of this study suggest post-error adjustment is a flexible process that can be observed during pre-movement planning and within the onset and magnitude of the reaching component, as well as in the magnitudes of the grasping component. Considering the sum of the results in the context of existing literature, we conclude that the findings add support to a functional account of error reactivity, such that post-error adjustments are implemented intentionally to improve performance.

Study on Gesture Recognition Method with Two-Stream Residual Network Fusing sEMG Signals and Acceleration Signals.

Currently, surface EMG signals have a wide range of applications in human-computer interaction systems. However, selecting features for gesture recognition models based on traditional machine learning can be challenging and may not yield satisfactory results. Considering the strong nonlinear generalization ability of neural networks, this paper proposes a two-stream residual network model with an attention mechanism for gesture recognition. One branch processes surface EMG signals, while the other processes hand acceleration signals. Segmented networks are utilized to fully extract the physiological and kinematic features of the hand. To enhance the model's capacity to learn crucial information, we introduce an attention mechanism after global average pooling. This mechanism strengthens relevant features and weakens irrelevant ones. Finally, the deep features obtained from the two branches of learning are fused to further improve the accuracy of multi-gesture recognition. The experiments conducted on the NinaPro DB2 public dataset resulted in a recognition accuracy of 88.25% for 49 gestures. This demonstrates that our network model can effectively capture gesture features, enhancing accuracy and robustness across various gestures. This approach to multi-source information fusion is expected to provide more accurate and real-time commands for exoskeleton robots and myoelectric prosthetic control systems, thereby enhancing the user experience and the naturalness of robot operation.

Estimation of Ground Reaction Forces during Sports Movements by Sensor Fusion from Inertial Measurement Units with 3D Forward Dynamics Model.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), a constituting component of jumps, through a biomechanical model-based approach allows for analysis, even in environments where force plates or machine learning training data would be impossible. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs), and GRFs and body loads were estimated using a 3D forward dynamics model. Our forward dynamics and optimization calculation-based estimation method generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of dynamic acceleration in the optimization calculation, we estimated the 3D orientation using sensor fusion, comprising acceleration and angular velocity data from IMUs and an extended Kalman filter. As a result, by generating cost function-based movements, we could calculate biomechanically valid GRFs while following the measured movements, even if not all joints were covered by IMUs. The estimation approach we developed in this study allows for measurement condition- or training data-independent 3D motion analysis.

Are Gait Patterns during In-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study.

Biomechanical assessments of running typically take place inside motion capture laboratories. However, it is unclear whether data from these in-lab gait assessments are representative of gait during real-world running. This study sought to test how well real-world gait patterns are represented by in-lab gait data in two cohorts of runners equipped with consumer-grade wearable sensors measuring speed, step length, vertical oscillation, stance time, and leg stiffness. Cohort 1 (N = 49) completed an in-lab treadmill run plus five real-world runs of self-selected distances on self-selected courses. Cohort 2 (N = 19) completed a 2.4 km outdoor run on a known course plus five real-world runs of self-selected distances on self-selected courses. The degree to which in-lab gait reflected real-world gait was quantified using univariate overlap and multivariate depth overlap statistics, both for all real-world running and for real-world running on flat, straight segments only. When comparing in-lab and real-world data from the same subject, univariate overlap ranged from 65.7% (leg stiffness) to 95.2% (speed). When considering all gait metrics together, only 32.5% of real-world data were well-represented by in-lab data from the same subject. Pooling in-lab gait data across multiple subjects led to greater distributional overlap between in-lab and real-world data (depth overlap 89.3-90.3%) due to the broader variability in gait seen across (as opposed to within) subjects. Stratifying real-world running to only include flat, straight segments did not meaningfully increase the overlap between in-lab and real-world running (changes of <1%). Individual gait patterns during real-world running, as characterized by consumer-grade wearable sensors, are not well-represented by the same runner's in-lab data. Researchers and clinicians should consider "borrowing" information from a pool of many runners to predict individual gait behavior when using biomechanical data to make clinical or sports performance decisions.

Research on a Calculation Model of Ankle-Joint-Torque-Based sEMG.

The purpose of this article is to establish a prediction model of joint movements and realize the prediction of joint movemenst, and the research results are of reference value for the development of the rehabilitation equipment. This will be carried out by analyzing the impact of surface electromyography (sEMG) on ankle movements and using the Hill model as a framework for calculating ankle joint torque. The table and scheme used in the experiments were based on physiological parameters obtained through the model. Data analysis was performed on ankle joint angle signal, movement signal, and sEMG data from nine subjects during dorsiflexion/flexion, varus, and internal/external rotation. The Hill model was employed to determine 16 physiological parameters which were optimized using a genetic algorithm. Three experiments were carried out to identify the optimal model to calculate torque and root mean square error. The optimized model precisely calculated torque and had a root mean square error of under 1.4 in comparison to the measured torque. Ankle movement models predict torque patterns with accuracy, thereby providing a solid theoretical basis for ankle rehabilitation control. The optimized model provides a theoretical foundation for precise ankle torque forecasts, thereby improving the efficacy of rehabilitation robots for the ankle.

Assessment of Surgeons' Stress Levels with Digital Sensors during Robot-Assisted Surgery: An Experimental Study.

Robot-Assisted Minimally Invasive Surgery (RAMIS) marks a paradigm shift in surgical procedures, enhancing precision and ergonomics. Concurrently it introduces complex stress dynamics and ergonomic challenges regarding the human-robot interface and interaction. This study explores the stress-related aspects of RAMIS, using the da Vinci XI Surgical System and the Sea Spikes model as a standard skill training phantom to establish a link between technological advancement and human factors in RAMIS environments. By employing different physiological and kinematic sensors for heart rate variability, hand movement tracking, and posture analysis, this research aims to develop a framework for quantifying the stress and ergonomic loads applied to surgeons. Preliminary findings reveal significant correlations between stress levels and several of the skill-related metrics measured by external sensors or the SURG-TLX questionnaire. Furthermore, early analysis of this preliminary dataset suggests the potential benefits of applying machine learning for surgeon skill classification and stress analysis. This paper presents the initial findings, identified correlations, and the lessons learned from the clinical setup, aiming to lay down the cornerstones for wider studies in the fields of clinical situation awareness and attention computing.

Anthropomorphic Tendon-Based Hands Controlled by Agonist-Antagonist Corticospinal Neural Network.

This article presents a study on the neurobiological control of voluntary movements for anthropomorphic robotic systems. A corticospinal neural network model has been developed to control joint trajectories in multi-fingered robotic hands. The proposed neural network simulates cortical and spinal areas, as well as the connectivity between them, during the execution of voluntary movements similar to those performed by humans or monkeys. Furthermore, this neural connection allows for the interpretation of functional roles in the motor areas of the brain. The proposed neural control system is tested on the fingers of a robotic hand, which is driven by agonist-antagonist tendons and actuators designed to accurately emulate complex muscular functionality. The experimental results show that the corticospinal controller produces key properties of biological movement control, such as bell-shaped asymmetric velocity profiles and the ability to compensate for disturbances. Movements are dynamically compensated for through sensory feedback. Based on the experimental results, it is concluded that the proposed biologically inspired adaptive neural control system is robust, reliable, and adaptable to robotic platforms with diverse biomechanics and degrees of freedom. The corticospinal network successfully integrates biological concepts with engineering control theory for the generation of functional movement. This research significantly contributes to improving our understanding of neuromotor control in both animals and humans, thus paving the way towards a new frontier in the field of neurobiological control of anthropomorphic robotic systems.

Biomechanical Posture Analysis in Healthy Adults with Machine Learning: Applicability and Reliability.

Posture analysis is important in musculoskeletal disorder prevention but relies on subjective assessment. This study investigates the applicability and reliability of a machine learning (ML) pose estimation model for the human posture assessment, while also exploring the underlying structure of the data through principal component and cluster analyses. A cohort of 200 healthy individuals with a mean age of 24.4 ± 4.2 years was photographed from the frontal, dorsal, and lateral views. We used Student's t-test and Cohen's effect size (d) to identify gender-specific postural differences and used the Intraclass Correlation Coefficient (ICC) to assess the reliability of this method. Our findings demonstrate distinct sex differences in shoulder adduction angle (men: 16.1° ± 1.9°, women: 14.1° ± 1.5°, d = 1.14) and hip adduction angle (men: 9.9° ± 2.2°, women: 6.7° ± 1.5°, d = 1.67), with no significant differences in horizontal inclinations. ICC analysis, with the highest value of 0.95, confirms the reliability of the approach. Principal component and clustering analyses revealed potential new patterns in postural analysis such as significant differences in shoulder-hip distance, highlighting the potential of unsupervised ML for objective posture analysis, offering a promising non-invasive method for rapid, reliable screening in physical therapy, ergonomics, and sports.

Restricting lumbar spine flexion redistributes and changes total mechanical energy expenditure during lifting.

Minimizing lumbar spine flexion during lifting requires greater lower extremity joint motion. However, the effects of these kinematic changes on lumbar and lower extremity joint kinetics are unknown. Further, it is unclear whether the distribution of biomechanical demands throughout the lumbar spine and lower extremity during lumbar spine flexion restricted lifting are modulated by task factors like lift origin height and object mass. This study examined the influence of restricting lumbar spine flexion during lifting on the distribution of biomechanical demands, operationalized as mechanical energy expenditure (MEE), across the lumbar spine and lower extremity joints during lifting tasks. Twenty participants performed a series of lifting tasks that varied by lift origin height, object mass and presence or absence of lumbar spine motion restricting harness. MEE was quantified for the lumbar spine and lower extremity joints and summed across all joints to represent the total MEE. Distributions of MEE were compared across combinations of the three task factors. Total MEE was greater when lifting with restricted spine motion (p < 0.001). MEE was redistributed away from the lumbar spine and predominantly to the hips in the spine restricted conditions (p < 0.001). The nature and magnitude of this effect was modulated by lift origin height for the lumbar spine (p < 0.001) and hips (p < 0.001). Findings demonstrated that biomechanical demands can be shifted from the lumbar spine to the lower extremity when lifting with restricted spine flexion, which might help mitigate overuse injuries through coordinative variability.