Search Results (386)

Objectives: The aim of this study was to evaluate the impact of four working heights on lumbar biomechanics during wall construction tasks, focusing on work-related musculoskeletal disorders (WMSDs). Methods: Fifteen young male participants performed simulated mortar-spreading and bricklaying tasks while actual body movements were recorded using Inertial Measurement Unit (IMU) sensors. Muscle activities of the lumbar erector spinae (ES), quadratus lumborum (QL), multifidus (MF), gluteus maximus (GM), and iliopsoas (IL) were estimated using a 3D musculoskeletal (MSK) model and measured via surface electromyography (sEMG). The analysis of variance (ANOVA) test was conducted to identify the significant differences in muscle activities across four working heights (i.e., foot, knee, waist, and shoulder). Results: Findings showed that working at foot-level height resulted in the highest muscle activity (7.6% to 40.6% increase), particularly in the ES and QL muscles, indicating an increased risk of WMSDs. The activities of the ES, MF, and GM muscles were statistically significant across both tasks and all working heights (p < 0.01). Conclusions: Both MSK and sEMG analyses indicated significantly lower muscle activities at knee and waist heights, suggesting these as the best working positions (47 cm to 107 cm) for minimizing the risk of WMSDs. Conversely, working at foot and shoulder heights was identified as a significant risk factor for WMSDs. Additionally, the similar trends observed between MSK simulations and sEMG data suggest that MSK modeling can effectively substitute for sEMG in future studies. These findings provide valuable insights into ergonomic work positioning to reduce WMSD risks among wall construction workers. Full article

Operatic singing, traditionally taught through empirical and subjective methods, demands innovative approaches to enhance its pedagogical effectiveness today. This paper introduces a novel integration of advanced skeletal tracking technology into a prototype framework for operatic singing pedagogy research. Using the Microsoft Kinect Azure DK sensor, this prototype extracts detailed data on spinal, cervical, and shoulder alignment and movement data, with the aim of quantifying biomechanical movements during vocal performance. Preliminary results confirmed high face validity and biomechanical relevance. The incorporation of skeletal-tracking technology into vocal pedagogy research could help clarify certain technical aspects of singing and enhance sensorimotor feedback for the training of operatic singers. Full article

Accurate estimation of upper-limb joint angles is essential in biomechanics, rehabilitation, and wearable robotics. While inertial measurement units (IMUs) offer portability and flexibility, systems requiring multiple inertial sensors can be intrusive and complex to deploy. In contrast, optical motion capture (MoCap) systems provide precise tracking but are constrained to controlled laboratory environments. This study presents a deep learning-based approach for estimating shoulder and elbow joint angles using only three IMU sensors positioned on the chest and both wrists, validated against reference angles obtained from a MoCap system. The input data includes Euler angles, accelerometer, and gyroscope data, synchronized and segmented into sliding windows. Two recurrent neural network architectures, Convolutional Neural Network with Long-short Term Memory (CNN-LSTM) and Bidirectional LSTM (BLSTM), were trained and evaluated using identical conditions. The CNN component enabled the LSTM to extract spatial features that enhance sequential pattern learning, improving angle reconstruction. Both models achieved accurate estimation performance: CNN-LSTM yielded lower Mean Absolute Error (MAE) in smooth trajectories, while BLSTM provided smoother predictions but underestimated some peak movements, especially in the primary axes of rotation. These findings support the development of scalable, deep learning-based wearable systems and contribute to future applications in clinical assessment, sports performance analysis, and human motion research. Full article

Background and Objectives: CrossFit is a discipline involving a wide range of overhead movements performed at high intensity and under accumulated fatigue that predispose to a high risk of shoulder complex injuries. This study aimed to compare ultrasonographic findings between symptomatic and asymptomatic shoulders in CrossFit athletes. Materials and Methods: A cross-sectional study was conducted to compare ultrasound parameters between the painful and non-painful shoulders in CrossFit athletes with unilateral subacromial shoulder pain. Assessed variables included subacromial subdeltoid bursa thickness, supraspinatus tendon thickness, the acromiohumeral distance, the coracoacromial ligament distance, the bicipital groove angle, cross-sectional area of the biceps brachii longus head tendon, as well as the serratus anterior and lower trapezius muscle thickness. Results: Twenty male CrossFit athletes (forty shoulders) with an average age of 25.70 ± 4.03 years participated in the study. A statistically significant increase was observed (p < 0.05) in the subacromial subdeltoid bursa thickness in the painful shoulder compared to the asymptomatic side. All other ultrasound parameters did not show statistically significant differences. Conclusions: Only subacromial subdeltoid bursa thickness differed significantly between sides. This isolated finding may not fully explain shoulder pain, which cannot be solely attributed to morphological changes. Further research is needed to determine the relationship between shoulder pain and ultrasound features in CrossFit athletes, as well as the role of ultrasound in predicting structural changes in pain conditions. Full article

In an era defined by rapid technological advancements, the intersection of artificial intelligence and industrial innovation has garnered significant attention from both academic and industry stakeholders. The emergence of Industry 4.0, characterized by the integration of cyber–physical systems, the Internet of Things, and smart manufacturing, demands the evolution of operational methodologies to ensure processes’ sustainability. One area of focus is the development of wearable systems that utilize artificial intelligence for the estimation of arm movements, which can enhance the ergonomics and efficiency of labor-intensive tasks. This study proposes a Random Forest-based regression model to estimate upper arm kinematics using only shoulder orientation data, reducing the need for multiple sensors and thereby lowering hardware complexity and energy demands. The model was trained on biomechanical data collected via a minimal three-IMU wearable configuration and demonstrated high predictive performance across all motion axes, achieving R² > 0.99 and low RMSE scores on training (1.14, 0.71, and 0.73), test (3.37, 1.97, and 2.04), and unseen datasets (2.77, 0.78, and 0.63). Statistical analysis confirmed strong biomechanical coupling between shoulder and upper arm motion, justifying the feasibility of a simplified sensor approach. The findings highlight the relevance of our method for sustainable wearable technology design and its potential applications in rehabilitation robotics, industrial exoskeletons, and human–robot collaboration systems. Full article

Accurate range of motion (ROM) assessment is essential for evaluating musculoskeletal function and guiding rehabilitation, particularly in pediatric populations. Traditional methods, such as optical motion capture and handheld goniometry, are often limited by cost, accessibility, and inter-rater variability. This study evaluated the feasibility and accuracy of the Microsoft Azure Kinect-powered Monitored Augmented Rehabilitation System (MARS) compared to Kinovea. Sixty-five pediatric participants (ages 5–18) performed standardized shoulder and elbow movements in the frontal and sagittal planes. ROM data were recorded using MARS and compared to Kinovea. Measurement reliability was evaluated using intraclass correlation coefficients (ICC3k), and accuracy was evaluated using root mean squared error (RMSE) analysis. MARS demonstrated excellent reliability with an average ICC3k of 0.993 and met the predefined accuracy threshold (RMSE ≤ 8°) for most movements, with the exception of sagittal elbow flexion. These findings suggest that MARS is a reliable, accurate, and cost-effective alternative for clinical ROM assessment, offering a markerless solution that enhances measurement precision and accessibility in pediatric rehabilitation. Future studies should enhance accuracy in sagittal plane movements and further validate MARS against gold-standard systems. Full article

Background/Objectives: Overhead athletes, including swimmers, are prone to shoulder adaptations and pathologies, such as scapular dyskinesis (SD) and glenohumeral internal rotation deficit (GIRD). While SD has been extensively studied in various overhead sports, its prevalence and clinical implications in swimmers remain unclear. This study aims to evaluate static scapular asymmetries (SAs), defined as differences in the observed position of the scapulae at rest or in a fixed position, in young elite swimmers and compare these findings with functional scapular dyskinesis (SD) tests, which assess alterations in scapular motion patterns during arm movement. It also assesses potential relationships between SA and SD. Methods: A cohort of 661 young elite swimmers (344 males, 317 females) was assessed during the National Young Swimming Championships. Scapular asymmetries were measured in two positions: at rest and at 90° abduction with internal rotation. The measurements included the following: (1) dHeight: Difference in superomedial scapular angle height from the C7 spinal process; (2) dDistance: Difference in the distance of the superomedial scapular angle from the body midline; (3) dAngle: Angular deviation of the medial scapular border from the plumb line, assessed using a goniometer. The presence of scapular dyskinesis (SD) was determined using a functional test, and SA findings were compared with SD results. Statistical analyses included ANOVA and chi-square tests, with significance set at p < 0.05. Results: Scapular asymmetries were observed in 3.63% to 15.43% of swimmers, with no significant associations with age, gender, BMI, training years, or swimming characteristics (p > 0.05). A significant difference was observed between dominant limb and scapular height in abduction (p < 0.05). In position 1 (resting position), SA was significantly more prevalent in swimmers without SD (p < 0.001 for dHeight, p = 0.016 for dDistance). In position 2 (abduction), SA was significantly associated with SD-negative subjects in dAngle (p = 0.014) and dDistance (p = 0.02), while dHeight was not significant (p > 0.05). These findings suggest that static scapular asymmetries do not necessarily correlate with dynamic scapular dysfunction (SD), and, indeed, a negative correlation was observed where SA was significantly more prevalent in swimmers without SD in several measures (position 1, p < 0.001 for dHeight and p = 0.016 for dDistance; position 2, p = 0.014 for dAngle and p = 0.02 for dDistance). Conclusions: Young elite swimmers exhibit a relatively symmetrical scapular positioning, with scapular asymmetries potentially representing normal adaptations rather than pathological findings. The lack of positive correlation between SA and SD, and the higher prevalence of SA in SD-negative subjects, suggests the need for caution when interpreting static scapular assessments in swimmers as SA may reflect sport-specific adaptations rather than pathology. Full article

Background and Objectives: Lymphedema is one of the most important morbid complications of modified radical mastectomy (MRM) surgery. It can cause limb movement restriction and psychosocial deformities in some patients. This study aimed to determine and compare the physiological and pathological changes that develop in the axillary venous structures in patients who underwent axillary lymph node dissection (ALND) and sentinel lymph node biopsy (SLNB). Materials and Methods: Patients diagnosed with breast cancer who underwent MRM and breast-conserving surgery (BCS) plus SLNB between 2017 and 2022 were retrospectively examined. The patients’ operation side and contralateral axillary vein diameter and the difference between them, axillary vein flow rate and the difference between them, axillary vein wall thickness and the difference between them, severity of lymphedema, extremity joint restriction examination, and the Nottingham Health Profile (NHP) data were recorded. The relationship of these parameters with the lymph node dissection width and radiotherapy was analyzed. Results: Fifty-eight patients in total were included in the study. In the distribution of lymphedema and lymphedema severity according to ALND groups, there is a statistically significant difference (p < 0.001). A statistically significant difference was determined in the distribution of the difference in the axillary vein blood flow rate and axillary vein diameter difference between the two arms according to the lymph node dissection groups. In the distribution of physical therapy and rehabilitation scales according to the lymph node dissection groups, a significant difference was found in the disabilities of the arm, shoulder, and hand (DASH), shoulder flexion restriction variables, and NHP sleep variables (all p < 0.001). Conclusions: This study demonstrated that ALND leads to more pronounced physiological and pathological changes in axillary venous structures—including increased vein wall thickness, altered flow rates, and diameter differences—compared to SLNB combined with breast-conserving surgery. These changes may be attributed to lymphovenous disruption and postoperative edema. Furthermore, radiotherapy appears to contribute to these changes, though to a lesser extent than ALND. Therefore, SLNB followed by radiotherapy may be preferable in eligible patients to reduce postoperative complications such as lymphedema, joint restriction, and sleep disturbances. Full article

Background/Objectives: Scapular adaptations have been associated with shoulder pain. However, conflicting findings have been reported after scapular-focused interventions. The present study aims to evaluate scapula-related outcomes before and after a scapular therapeutic exercise program. Methods: Eighteen adult volunteers with chronic shoulder pain participated in an 8-week scapular therapeutic exercise program that was personalized according to their pain condition and the presence of scapular dyskinesis. This program included preparation and warm-up, scapular neuromotor control, and strengthening and stretching exercises. Both self-reported (shoulder pain and function, psychosocial factors, and self-impression of change) and performance-based outcomes (scapular muscular stiffness and activity level, tridimensional motion, rhythm, and movement quality, measured while participants drank a bottle of water) were used for analysis. Results: After the intervention, participants presented reduced shoulder pain (p < 0.0001) and pain catastrophizing (p = 0.004) and increased shoulder function (p < 0.0001). Additionally, the participants presented changes in scapular winging (p < 0.0001 to p = 0.043), increased scapular downward rotation (p < 0.0001) and depression (p = 0.038), and decreased global movement smoothness (p = 0.003). These were associated with changes in serratus anterior activity (p = 0.016 to p = 0.035), decreased middle (p < 0.0001 to p = 0.002) and lower trapezius (p < 0.0001) and levator scapulae (p = 0.048) activity levels, and decreased middle trapezius muscle stiffness (p = 0.014). Patients’ self-perception of change was rated favorably. Conclusions: After a scapular therapeutic exercise program, changes were observed in both self-reported and performance-based outcomes. These results need to be confirmed by a randomized controlled trial. Full article

Background: Suprascapular neuropathy is a known cause of shoulder pain. Although neurodynamic techniques are widely used to treat peripheral neuropathies, the mechanical behavior of the suprascapular nerve in the shoulder region remains poorly understood. Objectives: This study aimed to analyze the mechanical behavior of the suprascapular nerve during a contralateral cervical glide and an infraspinatus muscle contraction. Methods: The study was conducted in two phases. First, nerve movement was analyzed in 12 cryopreserved cadaveric shoulders using anatomical dissection. Second, suprascapular nerve displacement was assessed in 34 shoulders from 17 healthy volunteers using ultrasound imaging. Results: In cadaveric dissections, the contralateral cervical glide produced a proximal nerve displacement of 1.85 mm at the suprascapular notch. In the ultrasound study, this maneuver resulted in horizontal and vertical displacements of 1.18 mm and 0.39 mm, respectively. In contrast, infraspinatus muscle contraction caused a distal displacement of 3.21 mm in the cadaveric study, and ultrasound imaging showed horizontal and vertical displacements of 1.34 mm and 0.75 mm, respectively. All reported displacements were statistically significant (p < 0.05). Conclusions: The findings of both phases of the study contribute to a better understanding of suprascapular nerve biomechanics and may inform clinical neurodynamic interventions. Full article

Spinal cord injury (SCI) often necessitates the use of a manual wheelchair, which can overload the shoulders and contribute to upper extremity (UE) pain. Currently, no standardized methods exist to assess UE kinematics during wheelchair propulsion. This study aimed to develop and evaluate a marker-based motion capture model for analyzing UE movement during wheelchair use, with a secondary goal of assessing test–retest reliability. The study was conducted in two phases: (1) development of the motion analysis model and (2) reliability testing. Eleven participants with SCI were included. Reliability was assessed using intraclass correlation coefficients (ICCs) across 15 movement parameters, including total range of motion and minimum and maximum movement values. The model demonstrated good test–retest reliability. For minimum movement, 12 of 15 parameters were significant (ICC = 0.681–0.965). For maximum movement, 13 of 15 were significant (ICC = 0.726–0.981). For total range of motion, 12 of 15 showed significant reliability (ICC = 0.596–0.952). In conclusion, the motion capture model showed promising reliability for assessing UE kinematics during wheelchair maneuvering in individuals with SCI. However, due to the small sample size, further research is needed to validate and refine the model. Full article

Introduction: Musculoskeletal disorders (MSDs) are a significant occupational health concern worldwide, particularly among healthcare professionals such as laboratory technicians. MSDs lead to chronic pain, decreased productivity, and reduced quality of life. This study aimed to investigate the prevalence of MSDs and associated ergonomics risk factors among Saudi clinical laboratory technicians. Methodology: This cross-sectional study was conducted on 167 clinical laboratory technicians in Taif city, Saudi Arabia. Data were collected through an online self-administered questionnaire, distributed via Google Forms. The questionnaire collected demographics information, assessed the prevalence of musculoskeletal pain using the Nordic Musculoskeletal Questionnaire (NMQ), and evaluated ergonomics risk factors using the Dutch Musculoskeletal Questionnaire (DMQ). Results: In total, 77.3% of the sample exhibited musculoskeletal issues in the last 12 months, with lower back (52.1%), neck (48.5%), and shoulders (40.7%) being the most frequent muscular complaints among laboratory technicians. Experience and nationality showed significant associations with MSDs (p ≤ 0.05). Lower back and neck complaints were commonly recorded with multiple laboratory tasks, including sustained sitting and standing and repetitive movement, whereas lower back and shoulder pain were notably prevalent with pipetting work. Conclusions: Work-related musculoskeletal disorders were highly apparent in laboratory practice. Periodic ergonomic training is mandated among laboratory personnel to limit occupational disability. Full article

Snowboard Big Air (SBA), recognized as an Olympic discipline since 2018, emphasizes maneuver difficulty as a key scoring criterion, requiring athletes to integrate technical skill with adaptive responses to dynamic environments in order to perform complex aerial rotations. The takeoff phase is critical, determining both flight trajectory and rotational performance through coordinated lower limb extension and upper body movements. Despite advances in motion analysis technology, quantitative assessment of key takeoff parameters remains limited. This study investigates parameters related to performance, joint kinematics, and rotational kinetics during the SBA takeoff phase to identify key factors for success and provide practical guidance to athletes and coaches. Eleven athletes from the Chinese national snowboard team performed multiple backside tricks (720°, 1080°, 1440°, and 1800°) at an outdoor dry slope with airbag landings. Three-dimensional motion capture with synchronized cameras was used to collect data on performance, joint motion, and rotational kinetics during takeoff. The results showed significant increases in most measured metrics with rising trick difficulty from 720° to 1800°. The findings reveal that elite SBA athletes optimize performance in high-difficulty maneuvers by increasing the moment of inertia, maximizing propulsion, and refining joint kinematics to enhance rotational energy and speed. These results suggest that training should emphasize lower limb power, core and shoulder strength, flexibility, and coordination to maximize performance in advanced maneuvers. Full article

This study aimed to investigate the influence of different walking speeds on shoulder and elbow joint kinematics, specifically focusing on range of motion, angular velocity, and angular acceleration during arm swing. The natural rhythm of human gait was studied to develop an effective mechanical interface, particularly with respect to joint impedance and force controllability. The independent variable in this study was walking speed, operationalized at four levels—3.6 km/h (slow), 4.2 km/h (preferred walking speed, PWS), 5.4 km/h (normal), and 7.2 km/h (fast)—and defined as a within-subject factor. The dependent variables consisted of quantitative kinematic parameters, including joint range of motion (ROM, in degrees), peak and minimum joint angular velocity (deg/s), and peak and minimum joint angular acceleration (deg/s²). For each subject, data from twenty gait cycles were extracted for analysis. The kinematic variables of the shoulder and elbow were analyzed, showing increasing trends as the walking speed increased. As walking speed increases, adequate arm swing contributes to gait stability and energy efficiency. Notably, the ROM of shoulder was slightly reduced at the PWS compared to the slowest speed (3.6 km/h), which may reflect more natural and coordinated limb movements at the PWS. Dynamic covariation of torque patterns in the shoulder and elbow joints was observed, reflecting a synergistic coordination between these joints in response to human body movement. Full article

This paper describes ongoing work surrounding the creation of a recognition system for Mexican Sign Language (LSM). We propose a general sign decomposition that is divided into three parts, i.e., hand configuration (HC), arm movement (AM), and non-hand gestures (NHGs). This paper focuses on the AM features and reports the approach created to analyze visual patterns in arm joint movements (wrists, shoulders, and elbows). For this research, a proprietary dataset—one that does not limit the recognition of arm movements—was developed, with active participation from the deaf community and LSM experts. We analyzed two case studies involving three sign subsets. For each sign, the pose was extracted to generate shapes of the joint paths during the arm movements and fed to a CNN classifier. YOLOv8 was used for pose estimation and visual pattern classification purposes. The proposed approach, based on pose estimation, shows promising results for constructing CNN models to classify a wide range of signs. Full article