BACKGROUND: Muscles play a critical role in supporting joints during activities of daily living, owing, in part, to the phenomenon of short-range stiffness. Briefly, when an active muscle is lengthened, bound cross-bridges are stretched, yielding forces greater than what is predicted from the force length relationship. For this reason, short-range stiffness has been proposed as an attractive mechanism for providing joint stability. However, there has yet to be a forward dynamic simulation employing a cross-bridge model, that demonstrates this stabilizing role. Therefore, the purpose of this investigation was to test whether Huxley-type muscle elements, which exhibit short-range stiffness, can stabilize a joint while at constant activation.
METHODS: We analyzed the stability of an inverted pendulum (moment of inertia: 2.7 kg m2) supported by Huxley-type muscle models that reproduce the short-range stiffness phenomenon. We calculated the muscle forces that would provide sufficient short-range stiffness to stabilize the system based in minimizing the potential energy. Simulations consisted of a 50 ms long, 5 Nm square-wave perturbation, with numerical simulations carried out in ArtiSynth.
RESULTS: Despite the initial analysis predicting shared activity of antagonist and agonist muscles to maintain stable equilibrium, the inverted pendulum model was not stable, and did not maintain an upright posture even with fully activated muscles.
CONCLUSIONS: Our simulations suggested that short-range stiffness cannot be solely responsible for joint stability, even for modest perturbations. We argue that short-range stiffness cannot achieve stability because its dynamics do not behave like a typical spring. Instead, an alternative conceptual model for short-range stiffness is that of a Maxwell element (spring and damper in series), which can be obtained as a first-order approximation to the Huxley model. We postulate that the damping that results from short-range stiffness slows down the mechanical response and allows the central nervous system time to react and stabilize the joint. We speculate that other mechanisms, like reflexes or residual force enhancement/depression, may also play a role in joint stability. Joint stability is due to a combination of factors, and further research is needed to fully understand this complex system.

BACKGROUND: Step width is a spatial variable in the frontal plane, defined as the mediolateral distance between the heel (forefoot during sprinting) of bilateral feet at initial contact. Variations in step width may impact the lower limb biomechanics. This systematic review aimed to synthesize the published findings to determine the influence of acute changes in step width on locomotion biomechanics and provide implications for injury prevention and enhanced sports performance.
METHODS: Literature was identified, selected, and appraised in accordance with the methods of a systematic review. Four electronic databases (Web of Science, MEDLINE via PubMed, Scopus, and ScienceDirect) were searched up until May 2023 with the development of inclusion criteria based on the PICO model. Study quality was assessed using the Downs and Black checklist and the measured parameters were summarized.
RESULTS: Twenty-three articles and 399 participants were included in the systematic review. The average quality score of the 23 studies included was 9.39 (out of 14). Step width changed the kinematics and kinetics in the sagittal, frontal, and transverse planes of the lower limb, such as peak rearfoot eversion angle and moment, peak hip adduction angle and moment, knee flexion moment, peak knee internal rotation angle, as well as knee external rotation moment. Alteration of step width has the potential to change the stability and posture during locomotion, and evidence exists for the immediate biomechanical effects of variations in step width to alter proximal kinematics and cues to impact loading variables.
CONCLUSIONS: Short-term changes in step width during walking, running, and sprinting influenced multiple lower extremity biomechanics. Narrower step width may result in poor balance and higher impact loading on the lower extremities during walking and running and may limit an athlete\'s sprint performance. Increasing step width may be beneficial for injury rehabilitation, i.e., for patients with patellofemoral pain syndrome, iliotibial band syndrome or tibial bone stress injury. Wider steps increase the supporting base and typically enhance balance control, which in turn could reduce the risks of falling during daily activities. Altering the step width is thus proposed as a simple and non-invasive treatment method in clinical practice.

(1) Background: Traditional gait assessment methods have limitations like time-consuming procedures, the requirement of skilled personnel, soft tissue artifacts, and high costs. Various 3D time scanning techniques are emerging to overcome these issues. This study compares a 3D temporal scanning system (Move4D) with an inertial motion capture system (Xsens) to evaluate their reliability and accuracy in assessing gait spatiotemporal parameters and joint kinematics. (2) Methods: This study included 13 healthy people and one hemiplegic patient, and it examined stance time, swing time, cycle time, and stride length. Statistical analysis included paired samples t-test, Bland-Altman plot, and the intraclass correlation coefficient (ICC). (3) Results: A high degree of agreement and no significant difference (p > 0.05) between the two measurement systems have been found for stance time, swing time, and cycle time. Evaluation of stride length shows a significant difference (p < 0.05) between Xsens and Move4D. The highest root-mean-square error (RMSE) was found in hip flexion/extension (RMSE = 10.99°); (4) Conclusions: The present work demonstrated that the system Move4D can estimate gait spatiotemporal parameters (gait phases duration and cycle time) and joint angles with reliability and accuracy comparable to Xsens. This study allows further innovative research using 4D (3D over time) scanning for quantitative gait assessment in clinical practice.

BACKGROUND: In physiotherapy, the classic muscle-bone concept is used to translate basic and clinical anatomy. By defining the anatomical structures from superficial to deeper layers which frame the ArthroMyoFascial complex, our aim is to offer clinicians a comprehensive concept of within the muscle-bone concept.
METHODS: This study is a narrative review and ultrasound observation.
RESULTS: Based on the literature and ultrasound skeletonization, the ArthroMyoFascial complex is defined. This model clarifies fascial continuity at the joint level, describing anatomical structures from skin to deeper layers, including superficial fascia, deep fascia, myofascia including skeletal muscle fibers, and arthrofascia all connected via connective tissue linkages. This model enhances the understanding of the muscle-bone concept within the larger ArthroMyoFascial complex.
CONCLUSIONS: The ArthroMyoFascial complex consists of multiple anatomical structures from superficial to deeper layers, namely the skin, superficial fascia, deep fascia, myofascia including muscle fibers, and arthrofascia, all linked within a connective tissue matrix. This model indicates that it is a force-transmitting system between the skin and the bone. This information is crucial for manual therapists, including physiotherapists, osteopaths, chiropractors, and massage therapists, as they all work with fascial tissues within the musculoskeletal domain. Understanding fascia within the muscle-bone concept enhances clinical practice, aiding in therapeutic testing, treatment, reporting, and multidisciplinary communication, which is vital for musculoskeletal and orthopedic rehabilitation.

BACKGROUND: Generalized Joint Hyper-mobility (GJH) can aid in the diagnosis of Ehlers-Danlos Syndrome (EDS), a complex genetic connective tissue disorder with clinical features that can mimic other disease processes. Our study focuses on developing a unique image-based goniometry system, the HybridPoseNet, which utilizes a hybrid deep learning model.
OBJECTIVE: The proposed model is designed to provide the most accurate joint angle measurements in EDS appraisals. Using a hybrid of CNNs and HyperLSTMs in the pose estimation module of HybridPoseNet offers superior generalization and time consistency properties, setting it apart from existing complex libraries.
METHODS: HybridPoseNet integrates the spatial pattern recognition prowess of MobileNet-V2 with the sequential data processing capability of HyperLSTM units. The system captures the dynamic nature of joint motion by creating a model that learns from individual frames and the sequence of movements. The CNN module of HybridPoseNet was trained on a large and diverse data set before the fine-tuning of video data involving 50 individuals visiting the EDS clinic, focusing on joints that can hyperextend. HyperLSTMs have been incorporated in video frames to avoid any time breakage in joint angle estimation in consecutive frames. The model performance was evaluated using Spearman\'s coefficient correlation versus manual goniometry measurements, as well as by the human labeling of joint position, the second validation step.
RESULTS: Preliminary findings demonstrate HybridPoseNet achieving a remarkable correlation with manual Goniometric measurements: thumb (rho = 0.847), elbows (rho = 0.822), knees (rho = 0.839), and fifth fingers (rho = 0.896), indicating that the newest model is considerably better. The model manifested a consistent performance in all joint assessments, hence not requiring selecting a variety of pose-measuring libraries for every joint. The presentation of HybridPoseNet contributes to achieving a combined and normalized approach to reviewing the mobility of joints, which has an overall enhancement of approximately 20% in accuracy compared to the regular pose estimation libraries. This innovation is very valuable to the field of medical diagnostics of connective tissue diseases and a vast improvement to its understanding.

BACKGROUND: How the joints exactly move and interact and how this reflects PD-related gait abnormalities and the response to dopaminergic treatment is poorly understood. A detailed understanding of these kinematics can inform clinical management and treatment decisions. The aim of the study was to investigate the influence of different gait speeds and medication on/off conditions on inter-joint coordination, as well as kinematic differences throughout the whole gait cycle in well characterized pwPD.
METHODS: 29 controls and 29 PD patients during medication on, 8 of them also during medication off walked a straight walking path in slow, preferred and fast walking speeds. Gait data was collected using optical motion capture system. Kinematics of the hip and knee and coordinated hip-knee kinematics were evaluated using Statistical Parametric Mapping (SPM) and cyclograms (angle-angle plots). Values derived from cyclograms were compared using repeated-measures ANOVA for within group, and ttest for between group comparisons.
RESULTS: PD gait differed from controls mainly by lower knee range of motion (ROM). Adaptation to gait speed in PD was mainly achieved by increasing hip ROM. Regularity of gait was worse in PD but only during preferred speed. The ratios of different speed cyclograms were smaller in the PD groups. SPM analyses revealed that PD participants had smaller hip and knee angles during the swing phase, and PD participants reached peak hip flexion later than controls. Withdrawal of medication showed an exacerbation of only a few parameters.
CONCLUSIONS: Our findings demonstrate the potential of granular kinematic analyses, including > 1 joint, for disease and treatment monitoring in PD. Our approach can be extended to further mobility-limiting conditions and other joint combinations.
BACKGROUND: The study is registered in the German Clinical Trials Register (DRKS00022998, registered on 04 Sep 2020).

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The human body constantly experiences mechanical loading. However, quantifying internal loads within the musculoskeletal system remains challenging, especially during unconstrained dynamic activities. Conventional measures are constrained to laboratory settings, and existing wearable approaches lack muscle specificity or validation during dynamic movement. Here, we present a strategy for estimating corresponding joint torque from muscles with different architectures during various dynamic activities using wearable A-mode ultrasound. We first introduce a method to track changes in muscle thickness using single-element ultrasonic transducers. We then estimate elbow and knee torque with errors less than 7.6% and coefficients of determination (R2) greater than 0.92 during controlled isokinetic contractions. Finally, we demonstrate wearable joint torque estimation during dynamic real-world tasks, including weightlifting, cycling, and both treadmill and outdoor locomotion. The capability to assess joint torque during unconstrained real-world activities can provide new insights into muscle function and movement biomechanics, with potential applications in injury prevention and rehabilitation.

Mallards inhabit soft grounds such as mudflats, marshes, and beaches, demonstrating remarkable proficiency in traversing these grounds. This adeptness is closely linked to the adjustments in the operation of their hindlimbs. This study employs high-speed videography to observe postural adjustments during locomotion across mudflats. Analysis of spatiotemporal parameters of the hindlimbs reveals transient and continuous changes in joints (tarsometatarso-phalangeal joint (TMTPJ), intertarsal joint (ITJ), knee, and hip) during movement on different ground hardness and slope (horizontal and uphill). The results indicate that as the stride length of the mallard increases, its speed also increases. Additionally, the stance phase duration decreases, leading to a decrease in the duty factor. Reduced ground hardness and increased slope lead to delayed adjustment of the TMTPJ, ITJ, and knee. Mallards adjust their stride length by augmenting ITJ flexion on steeper slopes, while reduced hardness prompts a decrease in TMTPJ flexion at touch-down. Additionally, the hip undergoes two brief extensions during the stance phase, indicating its crucial role in posture adjustment and propulsion on uphill grounds. Overall, the hindlimb joints of the mallard function as a whole musculoskeletal system, with each joint employing a distinct strategy for adjusting to adapt to various ground conditions.

Computational models of musculoskeletal systems are essential tools for understanding how muscles, tendons, bones, and actuation signals generate motion. In particular, the OpenSim family of models has facilitated a wide range of studies on diverse human motions, clinical studies of gait, and even non-human locomotion. However, biological structures with many joints, such as fingers, necks, tails, and spines, have been a longstanding challenge to the OpenSim modeling community, especially because these structures comprise numerous bones and are frequently actuated by extrinsic muscles that span multiple joints-often more than three-and act through a complex network of branching tendons. Existing model building software, typically optimized for limb structures, makes it difficult to build OpenSim models that accurately reflect these intricacies. Here, we introduce ArborSim, customized software that efficiently creates musculoskeletal models of highly jointed structures and can build branched muscle-tendon architectures. We used ArborSim to construct toy models of articulated structures to determine which morphological features make a structure most sensitive to branching. By comparing the joint kinematics of models constructed with branched and parallel muscle-tendon units, we found that among various parameters-the number of tendon branches, the number of joints between branches, and the ratio of muscle fiber length to muscle tendon unit length-the number of tendon branches and the number of joints between branches are most sensitive to branching modeling method. Notably, the differences between these models showed no predictable pattern with increased complexity. As the proportion of muscle increased, the kinematic differences between branched and parallel models units also increased. Our findings suggest that stress and strain interactions between distal tendon branches and proximal tendon and muscle greatly affect the overall kinematics of a musculoskeletal system. By incorporating complex muscle-tendon branching into OpenSim models using ArborSim, we can gain deeper insight into the interactions between the axial and appendicular skeleton, model the evolution and function of diverse animal tails, and understand the mechanics of more complex motions and tasks.