Biomechanical and viscoelastic behaviour of skeletal muscles is increasingly investigated using non-invasive techniques such as myotonometry, which provide indirect estimates of tissue mechanical characteristics derived from the oscillatory response of the muscle-superficial tissue complex to a brief mechanical impulse. However, the interpretation of these measurements may be influenced by body composition, particularly subcutaneous adipose tissue, which can alter mechanical signal propagation. This study aimed to determine whether adiposity influences the interpretation of myotonometric measurements of muscle mechanical properties and to identify the most relevant adiposity-related factors affecting these measurements. A total of 133 healthy adults (63 females, 70 males; mean age 35.16 ± 8.29 years) were included. Body mass index (BMI), percentage body fat (%BF) estimated from skinfold measurements and the sum of four skinfold thickness (SFT) sites were assessed. Muscle mechanical properties (tone, stiffness, decrement, relaxation, and creep) of the biceps brachii, triceps brachii, rectus femoris, gastrocnemius medialis, and rectus abdominis were measured using the MyotonPRO device. Associations were analyzed using Spearman's rank correlation, while predictive value was evaluated using linear regression models adjusted for age and sex. Model fit was compared using the Akaike Information Criterion (AIC). %BF and SFT showed strong and consistent associations with muscle properties, including negative correlations with tone and stiffness (up to ρ = -0.821) and positive correlations with viscoelastic parameters (up to ρ = 0.847; all p < 0.001), whereas BMI showed weak and mostly non-significant relationships. Regression analyses identified %BF as the most robust predictor (β up to 0.83; R2 up to 0.69), particularly for viscoelastic parameters. SFT demonstrated lower and more variable predictive value, while BMI showed minimal explanatory power. The magnitude and consistency of these associations suggest that adiposity substantially affects the mechanical response captured by myotonometry. Subcutaneous adiposity significantly influences myotonometric measurements and may affect the interpretation of muscle mechanical properties. These findings highlight the need to consider body composition when using myotonometry as a tool for muscle assessment.
Manual wheelchair users are at high risk of developing shoulder pathologies due to the repetitive demands of propulsion. Understanding individual muscle contributions is essential to improve rehabilitation strategies and prevent overuse injuries. This study applied a modeling approach to evaluate the individual muscle contributions, particularly the rotator cuff muscles, to mechanical work during the push and recovery phases of wheelchair propulsion in individuals with a spinal cord injury. We used a thoracoscapular shoulder model in OpenSim, which incorporated accurate scapular kinematics and muscles often omitted in previous models, such as the serratus anterior, trapezius, and rhomboids. Experimental data from five individuals with paraplegia were analysed to estimate muscle work. During the push phase, significant contributors were the anterior deltoid, pectoralis major, infraspinatus, and serratus anterior. The recovery phase mainly involved the subscapularis, teres major, trapezius, posterior deltoid, middle deltoid and rhomboids. The supraspinatus showed no mechanical work, and overall rotator cuff contributions were lower than previously reported. Model outputs were verified using reserve actuator contributions and power ratios, and validated by comparing computed with measured muscle activations. Moreover, our findings support the importance of incorporating scapula-driving muscles like the serratus anterior, trapezius, and rhomboids into upper-extremity musculoskeletal models.
Frequent falls in ambulatory people with spinal cord injury (SCI) makes balance an area of research priority. To assess dynamic stability, we investigated center of mass (CoM) acceleration during stance phase of people with SCI (n = 34) who did not use an assistive device (n = 18) and those who used a rolling walker (n = 16). Comparison data was collected from neurologically intact (NI) individuals (n = 15). CoM acceleration was analyzed as a discrete metric using the root mean square (RMS) and as a continuous metric using statistical non-parametric mapping (SnPM). Stance phase was assessed as a whole and as its subphases. Analyzing RMS of CoM acceleration revealed that people with SCI who walk at similar speeds to NI demonstrated greater RMS of CoM acceleration, but those walking at slower speeds differed depending on assistive device use and functional level. Analyzing speed-normalized RMS of CoM acceleration showed that all people with SCI, regardless of phase, demonstrated greater CoM acceleration compared to NI. SnPM analysis elucidated that each subphase contained sections wherein CoM acceleration differed in magnitude and/or direction with results differing by grouping. This analysis may offer insight towards dynamic stability during walking in people with SCI, aiding clinicians in creating targeted interventions to improve balance.
Neuromuscular fatigue (NMF) is an inherent consequence of strenuous training and competition. It arises from complex interactions between the central nervous system and peripheral skeletal muscle. Despite decades of research, the interaction between central and peripheral mechanisms of neuromuscular fatigue and their influence on sports performance remains a contentious topic. In addition, translating mechanistic insights into practical strategies for monitoring, training, and recovery in athletes is an ongoing challenge. This review synthesizes contemporary literature to build a central-peripheral integrative model of NMF and proposes an applied framework for athlete monitoring and training design. The review first summarizes central and peripheral fatigue mechanisms, highlighting the bidirectional influence of descending motor drive and afferent feedback, and discusses controversies such as the central-governor theory. It then assesses monitoring tools (subjective ratings, neuromuscular tests, electromyography, heart-rate variability, biochemical and neurochemical markers) and recovery strategies. Finally, the review translates mechanistic knowledge into evidence-based training and recovery recommendations. A conceptual model illustrating the interactions between central and peripheral mechanisms and their monitoring is included. The aim is to inform sports scientists and practitioners about the physiological bases of fatigue and provide guidance for individualized athlete management.
Rotator cuff fatty infiltration (FI) can lead to poor post-operative outcomes in rotator cuff tear patients. While higher magnitudes of FI are associated with aging and pathology, anthropometric variables may also influence FI. This research investigated the effect of sex and body mass index (BMI) on supraspinatus (SS) and infraspinatus (IS) FI among young adults without shoulder pathology. Magnetic resonance imaging (MRI) and ultrasound (US) were captured from 40 adult males and females with varying BMI. US images were captured using different participant positioning, and transducer techniques. Upper limb static strength assessments were also performed. Regression analysis revealed that both sex and BMI explained significant variance in MRI FI for SS (p < 0.0001, R2 = 0.51), and BMI for IS (p < 0.0001, R2 = 0.54). Further, US echogenicity generally showed excellent reliability, and explained significant variance in MRI Fat Fraction (FF) across techniques and participant positions, while SS had more varied results. Significant relationships between strength and FI were only demonstrated for SS MRI FI (range, r = -0.21 to -0.33). This study showed that sex and BMI are significantly related to rotator cuff FI. Future research should continue to explore FI among an aging population, with and without rotator cuff pathology.
This study evaluated whether participant characteristics, literature-derived regression equations, and a generic musculoskeletal model developed for nonimpaired populations could accurately predict maximal shoulder and elbow strength in children and adults with paraplegia. Thirty individuals with paraplegia (22 adults, 8 children) completed maximal voluntary isometric contractions (MVICs) in seven upper extremity postures. Predicted MVICs were generated using a scaled OpenSim upper extremity model with three muscle activation inputs (Full, Separated, and EMG-informed). Linear mixed-effects models evaluated relationships between predicted and experimentally measured MVICs across postures. Model performance was assessed using marginal and conditional R2, root mean square error (RMSE), mean absolute error (MAE), Lin's concordance correlation coefficient (CCC), and repeated-measures Bland-Altman analyses. Agreement between measured and height-predicted upper extremity segment lengths was also evaluated. Joint posture significantly influenced measured MVIC, and significant posture-by-predicted MVIC interactions demonstrated that prediction accuracy was posture dependent (all p < 0.001). The Full activation input explained the greatest proportion of variance in measured MVIC (marginal R2 = 0.770; conditional R2 = 0.931), whereas the EMG-informed activation input produced the lowest prediction error (RMSE = 22.38% MVIC; MAE = 17.14% MVIC). However, agreement between predicted and measured MVIC remained modest across all activation inputs (CCC = 0.259-0.312), with systematic bias evident in Bland-Altman analyses. Height-based anthropometric scaling overestimated forearm and humerus lengths by 1.25 and 4.96 cm, respectively, with greater error for the humerus (RMSE = 5.82 cm). Regression-based scaling and generic musculoskeletal models derived from nonimpaired populations provided only modest estimates of maximal upper extremity strength in individuals with paraplegia. Improving strength prediction will require innovative scaling approaches that incorporate participant-specific anthropometry, population-specific muscle properties, and individualized neuromuscular activation while balancing model accuracy with practical clinical feasibility.
This retrospective study aimed to examine age-related differences in functional mobility across narrowly defined age groups of community-dwelling older adults using the instrumented Timed Up and Go (iTUG) test. Specifically, we sought to identify which iTUG subtasks and sensor-derived parameters showed the most pronounced differences across age strata and to characterize phase-specific temporal and kinematic features from 65 years onward using a single-sensor approach. We hypothesized that age-related differences would not affect all iTUG components uniformly, with walking and turning-related parameters showing clearer differences across age groups than trunk excursion measures. Data from 212 healthy adults aged over 65 years were retrospectively analyzed and stratified into four age groups. Functional mobility was assessed using a single lumbar-mounted inertial measurement unit (IMU) during the iTUG. Primary outcomes included total and sub-phase durations (sit-to-stand, walking, turning, stand-to-sit), turning velocities, and trunk flexion/extension angles during postural transitions. Between-group differences were assessed using MANOVA followed by Bonferroni-adjusted ANOVAs. A significant main effect of age group was found for iTUG parameters (p < 0.001, η2 = 0.13). Total duration and most sub-phase durations increased across age groups, whereas no significant age-group differences were observed in trunk flexion or extension angles. These findings indicate that temporal and velocity-based iTUG parameters, especially those related to walking and turning, showed clearer age-stratified differences than trunk angular measures. Overall, the study provides descriptive age-stratified data on phase-specific iTUG features in community-dwelling older adults and supports the value of subtask-level analysis for characterizing functional mobility beyond total TUG duration alone.
BACKGROUND:This study aims to investigate how alterations in the spatial distribution of motor unit (MU) density, such as those resulting from neuromuscular disorders, affect the accuracy of muscle fiber conduction velocity (MFCV) estimation, and to examine whether different levels of MU recruitment can mitigate these effects. METHODS:We used the Fuglevand model to simulate three different MU densities across the muscle: edge-clustered, center-clustered, and a uniform distribution. MFCV was estimated from simulated double differential surface electromyography (sEMG) signals at four MU recruitment levels using a cross-correlation method. RESULTS:MU density spatial distribution influenced MFCV estimation accuracy. The highest estimation accuracy was achieved in regions of high MU density and lowest in regions of low MU density. Level of MU recruitment influenced MFCV estimation accuracy, with higher recruitment partially compensating for estimation errors. A lower number of MUs reduced overall estimation accuracy. CONCLUSIONS:The spatial distribution of MU density is an important factor in MFCV estimation. This study provides quantitative benchmarks for how spatial variations in MU density affect MFCV estimation accuracy. The finding highlights the importance of MU density, recruitment level, and total number of MUs in estimating MFCV, all of which may be altered in patients with neuromuscular disorders.
Sensory-stimulating insoles that deliver a single-sensory stimulus (texture or vibration) can improve standing balance. Vibrotexture insoles combine both stimuli, but their effects on anticipatory postural adjustments (APAs) during internal perturbation tasks remain unclear. The aim was to investigate the effects of vibrotexture insoles on APAs during bilateral rapid arm-raises in healthy younger and older adults. Thirty healthy younger (16 males, 23.6 ± 3.9 years) and thirty healthy older (14 males; 69.8 ± 5.8 years) adults performed rapid, bilateral arm-raises wearing four different insoles (vibrotexture, vibrating, textured, and control). Balance outcomes included time to onset and peak centre of pressure (COP) displacement, and COP displacement and position on the force platform. Surface electromyography of the deltoid, gluteus medius, biceps femoris, and medial gastrocnemius were recorded to determine onset of muscle activity. COP and electromyography outcomes were analysed using a linear mixed model, with Bonferroni adjustment. There were no differences in balance or electromyography outcomes between the vibrotexture and other insole conditions. An isolated difference in onset of biceps femoris activity was observed between vibrating and textured insoles in younger adults (p = 0.001); however, no other COP or muscle activity outcomes differed between insoles. Vibrotexture insoles may not alter APAs during rapid bilateral arm-raises in healthy adults.
In children with cerebral palsy (CP), gait impairments originate from altered neuromuscular control and result in abnormal biomechanical outcomes. Muscle synergy analysis has been used to investigate modular motor control, but it relies exclusively on electromyographic (EMG) data. Kinematic-muscular synergies integrate EMG signals and kinematic variables, associating the neural commands with the biomechanics of the movement. This study examined kinematic-muscular synergies during gait in children with CP to identify alterations in both synergy structure and temporal activation. Seventeen children with CP were stratified based on their age (children, adolescents, and young adults). Twenty-two typically developed (TD) children served as the reference. Mixed-matrix factorization was used to extract kinematic-muscular synergies from 8 lower limb muscles and four joint accelerations in the sagittal plane. Spatial synergy structures were more consistent in TD and children than in adolescents (p = 0.04) and young adults (p = 0.001), while consistency of temporal coefficients was higher in TD (p < 0.001). Comparisons of patients with TD children revealed generally moderate preservation of spatial synergy structure, but temporal recruitment patterns diverged with age. Kinematic-muscular synergy analysis provides a quantitative link between impaired muscle coordination and altered biomechanics in CP gait, offering a promising tool for enhanced gait assessment and personalized rehabilitation planning.
BACKGROUND:Non-specific chronic low back pain (NSCLBP) is a complex condition influenced by physical, psychological, and social factors. Conservative treatments, including manual therapy, exercise and other non-invasive approaches (e.g., patient education, lifestyle modifications), are recommended, however, their impact on objective neuromuscular biomarkers remains unclear. The flexion relaxation phenomenon (FRP), commonly assessed using the flexion relaxation ratio (FRR), has been proposed as a potential biomarker for NSCLBP. OBJECTIVE:This systematic review evaluates the effects of conservative treatments on FRP in individuals with NSCLBP. METHODS:A comprehensive systematic search was conducted across four databases (PubMed, EMBASE, Cochrane, and PEDro) up to March 31, 2025, following PRISMA guidelines. Randomized controlled trials (RCTs) examining the effects of conservative treatments on FRP in NSCLBP were included. Risk of bias was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool. The review protocol was registered in PROSPERO (CRD42020162576). RESULTS:Twelve RCTs, including 480 participants, met the inclusion criteria. Most studies were assessed as having a high risk of bias. Several studies reported within-group improvements in FRR following manual therapies; however, the short- and mid-term effects of exercise-based interventions were inconsistent. Only a minority of studies adhered to standardized electromyography (sEMG) electrode placement guidelines, contributing to substantial heterogeneity in FRP assessment. CONCLUSION:Manual therapies may be associated with immediate changes in FRP; however, these findings should be interpreted with caution due to methodological limitations, including the lack of consistent between-group comparisons. The effects of exercise-based interventions remain unclear. Heterogeneity in FRP recording and analyzis methods further limits the interpretation of results. Further high-quality studies using standardized methodologies are needed to validate FRP as a biomarker for NSCLBP and to clarify its relationship with clinically meaningful outcomes.
The purpose of this investigation was to determine the effect of common trunk exercises (bird-dog, back extension, glute bridge, and reverse hyperextension), loading, (unloaded and 10% bodyweight), and exercise phases (concentric, isometric, eccentric) on deep lumbar multifidus (DLM) activation. Repeated measures analyses of variance were used to compare DLM amplitude and relative contribution between exercises, loads, and phases. Multifidus activation from 34 healthy adults was collected with indwelling electrodes and normalized to a maximum voluntary isometric contraction (MVIC). DLM activation was greater during the reverse hyperextension compared to bird-dog (+13.5% MVIC), glute bridge (+14.3% MVIC), and trunk extension (+5.3% MVIC). A 10% bodyweight load resulted in a negligible DLM activation increase (+3.8% MVIC) across all exercises. Relative DLM contribution was greater during the bird-dog compared to all other exercises (range: 12.2 to 14.5%). Relative contribution was greater in unloaded exercises compared to loaded (0.9%), and greatest during the isometric and concentric phases (range: 16.3% to 19.4% versus eccentric). The greatest activation of the DLM occurs during large trunk extension-based exercises, but the bird-dog best activates the DLM with minimal synergistic activation (superficial multifidus and erector spinae).
Biomechanical biofeedback has the potential to enhance rehabilitation by providing clinicians with objective evaluation of patient performances. As feedback systems often depend on expensive and sophisticated motion capture technologies, researchers explore computer vision-based alternatives. Existing methods suffer from substantial joint angle errors, particularly in the upper limb, and neglect the scapular movements. In this paper, we present a method based on a single front-facing RGB-D camera that automatically detects 3D anatomical landmark locations using depth information. We also use a 3D-printed acromial cluster to provide scapular motion. Together, these landmarks and the acromial cluster are used to provide comprehensive estimation of shoulder joint kinematics through inverse kinematics. Annotated images from eight participants were used to fine-tune a convolutional neural network, which was subsequently evaluated on a hand-cycling motion. Our method showed a strong agreement with a reference marker-based system, with 3D anatomical landmark detection errors averaging 5 mm. The resulting kinematics closely aligned with the reference system, maintaining acceptable joint angle errors (∼6.3°). Furthermore, the algorithm could provide real-time anatomical landmark positions and joint kinematics at a rate of 50Hz. This study highlights the potential of using a single consumer-grade depth-sensing camera combined with a 3D-printed acromial cluster to accurately estimate upper-limb kinematics through anatomical landmark detection, paving the way for more accessible clinical assessments.
Surface electromyography (sEMG) signals are characterized by low amplitude, nonlinearity, non-stationarity, and susceptibility to various types of noise during acquisition. Although signal decomposition-based preprocessing methods are widely used, the performance of existing algorithms heavily depends on mode selection strategies, leading to suboptimal denoising outcomes under low signal-to-noise ratio(SNR) conditions. These limitations significantly restrict the broader application of sEMG. In this paper, a hybrid denoising framework integrating variational mode decomposition (VMD) and refined composite multiscale dispersion entropy (RCMDE) is proposed. Based on the variational mode functions(VMFs) derived from VMD, an RCMDE-weighted VMF screening mechanism is established to effectively identify noise-dominant components and suppress spectral leakage. Subsequently, local mean decomposition(LMD) and wavelet thresholding(WT) are combined to achieve superior denoising performance. Simulations on synthetic sEMG and real sEMG signals, along with gesture classification experiments, demonstrate that the proposed algorithm outperforms conventional VMD and other mode selection methods, such as those based on correlation coefficient or multiscale dispersion entropy, in terms of SNR and root mean square error(RMSE), particularly under low-SNR scenarios. This method contributes to improving gesture classification accuracy and provides an efficient preprocessing solution for sEMG signals, which lays a foundation for its applications in medical diagnosis and human-computer interaction.
Purpose To investigate the effects of spinal manipulation (SM) on neuromuscular activation patterns during single-leg vertical drop landing (VDL) in individuals with anterior cruciate ligament reconstruction (ACLR). Methods A single-blind, randomized controlled trial was conducted. Twenty individuals with ACLR were randomly assigned to a SM group (SMG, n = 10) or a control group (CG, n = 10). Kinematic, kinetic, and electromyographic data were collected during VDL at baseline and 10 min post-intervention. Statistical analyses were conducted at a significance level of 0.05. Results Significant group × time × phase interactions were found for semitendinosus muscle activity and vastus medialis:semitendinosus co-contraction (p < 0.05). Post hoc analyses revealed reduced preparatory-phase muscle activity and co-contraction in the SMG compared with the CG following the intervention. Additional differences in muscle activity and co-contraction were observed (p < 0.05), although no significant interactions were identified. The SMG also exhibited greater knee flexion and increased knee abduction compared with the CG (p < 0.05). No additional significant between-group differences were identified (p > 0.05). Conclusion A single session of SM was associated with neuromuscular and biomechanical changes during landing in individuals with ACLR, supporting its potential as a complementary approach in rehabilitation.ClinicalTrials.gov Identifier: NCT07032623
Chronic neck pain is prevalent and disabling, and routine examinations offer limited insight into vertebral-level motion abnormalities. This study aimed to quantify intervertebral cervical kinematics in chronic neck pain using biplane videoradiography and to compare them with asymptomatic controls. Twenty-three adults (13 with chronic neck pain, 10 controls) completed three trials of flexion-extension, lateral bending, and axial rotation while seated in a custom biplane videoradiography system integrated with optical motion capture. Vertebral kinematics from C4-C7 were derived from computed-tomography-based models using semi-automated shape-matching. Nonparametric bootstrapping produced 90% confidence intervals for total range of motion, the percent contribution to global head-to-torso motion, and trial-to-trial variability. Compared with controls, participants with chronic neck pain showed reduced axial-rotation motion and contribution at C5-6 with increased contribution of head motion relative to C4. During flexion-extension, there was a greater contribution from C4-5 and greater trial-to-trial variability in the percent contribution of head-relative-to-C4. No group differences were observed for lateral bending. These findings identified localized deficits at C5-6 and altered motion distribution at other levels, suggesting segment-specific biomechanical changes with compensatory mobility in chronic neck pain. Intervertebral kinematic analysis may improve biomechanical assessment and inform individualized management strategies.
The purpose of this study was to assess reliability of performance, knee functionality and movement quality parameters in agility T-test using markerless motion capture. Seventeen healthy participants performed two sessions of agility T-test with a one-week interval. Performance, knee functionality and movement quality parameters were evaluated for absolute reliability between sessions for discrete metrics. Test-retest reliability was evaluated using intraclass correlation coefficient (ICC (2,1), absolute agreement), standard error of measurement (SEM), and minimal detectable change (MDC). The between-session ICC values of performance, knee functionality and movement quality parameters showed moderate to good reliability (ICC range performance parameters: 0.65-0.96; ICC range knee functionality parameters: 0.74-0.94; ICC range movement quality parameters: 0.59-0.90). SEM and MDC provided insights into precision and minimal clinically significant changes for each parameter. Overall, these findings support the potential of markerless motion capture for reliably quantifying the evaluated biomechanical parameters during the agility T-test, demonstrating consistent test-retest reliability across sessions.
