Search Results (288)

Real-time fatigue classification on resource-constrained edge devices faces three unresolved computational challenges: just-in-time compilation latency spikes that violate the 50 ms inference budget, statistical moment features insensitive to temporal complexity signatures of fatigue, and binary anomaly outputs insufficient for actionable coaching decisions. A synthetic IMU dataset (9 subjects, 540,000 samples, 6 channels at 100 Hz) was generated as a reproducible computational benchmark, with fatigue signatures calibrated to published biomechanical effect sizes (sample entropy $d=+0.77$; permutation entropy $d=+0.38$). We present Safari (Stochastic Adaptive Fitness-Aware Real-time Inference), an end-to-end computational pipeline integrating: a dual-pathway entropy triplet (SampEn, PermEn, SpEn) replacing statistical moments; 16 pre-compiled polyhedral anchor kernels eliminating JIT latency; $O\left({(\Delta W)}^2\right)$-bounded runtime interpolation; subject-specific MaxEnt free-energy anomaly scoring; and a Banister fitness–fatigue adaptive threshold. Safari achieves AUC-ROC = 0.9820 (Monte Carlo 95% CI: 0.9726–0.9886), F1 = 0.8835, four-state accuracy = 83.3%, and worst-case latency = 7.2 ms on a Raspberry Pi 4. Entropy features achieve 1.55× higher discriminability than statistical moments. Safari is a computational framework for real-time fatigue monitoring, contributing a reproducible algorithmic benchmark for edge AI in movement analysis, with real-athlete validation as the recommended next step. Full article

Background: The Mercer Universal Prosthesis (MUP), designed with a default “neutral” (vertical) socket alignment, was developed to simplify transtibial prosthetic fitting, reduce labor costs, and improve access to prosthetic care in low-resource settings. Methods: This present longitudinal study evaluated biomechanical and functional outcomes at baseline, 6 months, and 12 months in 20 transtibial amputees fitted with the MUP. Results: Functional outcomes, assessed using the SF-36, showed significant improvement in overall health scores at 12 months (p < 0.001), while physical function and energy/fatigue domains remained unchanged (p = 0.686 and p = 0.211, respectively). Biomechanically, sagittal kinematics, measured using inertial motion capture, revealed significant limb × time interactions for hip flexion, knee flexion, and ankle plantarflexion. At 6 months, maximum hip flexion (−7°, p = 0.008) and knee flexion (−11°, p = 0.005) of the prosthetic limb were decreased versus baseline. At 12 months, the only observed difference was increased maximum ankle plantarflexion of the intact limb (+5° vs. baseline, p = 0.016). Muscle effort, quantified via the integral of EMG throughout the gait cycle, did not differ significantly between prosthetic and intact limbs across time points. Gait symmetry index (GSI) scores for hip, knee, and ankle range of motion trended toward gradual improvement but without statistical significance (p > 0.05). Conclusions: The MUP performance was maintained over 12 months, with stable biomechanical performance and meaningful quality-of-life gains. These findings support its potential as a cost-effective solution to expand prosthetic accessibility in low- and middle-income countries. Full article

Background/Objectives: Ankylosing Spinal Disorders (ASDs) encompass a heterogeneous group of rheumatic diseases characterized by progressive ankylosis of the axial skeleton, including Ankylosing Spondylitis (AS), Diffuse Idiopathic Skeletal Hyperostosis (DISH), and Non-Radiographic Axial Spondyloarthritis (nr-AxSpA). Spinal ankylosis profoundly alters the biomechanical properties of the vertebral column, transforming it into a rigid long-bone equivalent and dramatically increasing fracture risk even after low-energy trauma. Once a fracture occurs, the long lever arm created by the ankylosed segments generates enormous mechanical stress at the fracture site, making surgical stabilization mandatory in the vast majority of cases. Long posterior instrumentation is the treatment of choice; however, no consensus exists regarding the optimal number of instrumented levels. The aim of this study is to clinically and radiologically evaluate long posterior instrumentation in the 3 + 3 (3 proximal and 3 caudal screws), 3 + 2 (3 proximal and 2 caudal screws), or 2 + 2 (2 proximal and 2 caudal screws) configuration for the treatment of traumatic ASD thoracolumbar vertebral fractures, in terms of implant failure, infection rate, and mortality. Methods: Between 2018 and 2023, 65 consecutive patients with ASD-related thoracolumbar vertebral fractures were treated at our institution. After applying pre-defined inclusion and exclusion criteria, 37 patients were enrolled. Patients were retrospectively divided into three groups according to the posterior arthrodesis configuration (notation indicates number of instrumented vertebral levels proximal + distal to the fracture: 3 + 3, 3 + 2, or 2 + 2). Radiological outcomes were assessed for loosening, screw cut-out, and implant breakage. Infection and mortality rates within 3 months from surgery were evaluated as secondary endpoints. Statistical analysis was performed using the Fisher exact test (significance set at p < 0.05). Results: Thirty-seven patients (28 males and 9 females; mean age 77 ± 7.3 years) were included, with a mean follow-up of 30 ± 5.3 months. Instrumentation configurations were as follows: 23 (3 + 3), 5 (3 + 2), and 9 (2 + 2). Three implant failures (8.1%) and four infections (10.8%) were recorded. Eleven patients died within 3 months of surgery. A statistically significant difference was found between instrumentation length and mechanical complications (p = 0.0468), while no significant difference was observed for infection (p = 1) or mortality rate (p = 0.137). Conclusions: In this exploratory retrospective cohort, the 3 + 3 configuration was associated with the lowest observed rate of implant failure in ASD thoracolumbar fractures, suggesting a potential mechanical advantage over shorter constructs that warrants confirmation in larger prospective studies. No significant correlation was found between instrumentation length and infection rate or early mortality. Prospective, multicentre studies with larger cohorts are warranted to establish definitive guidelines for instrumentation length in this challenging patient population. Full article

Sodium hypochlorite (NaOCl) remains the gold standard irrigant in endodontics due to its proteolytic and antimicrobial properties, whereas hydrogen peroxide (HP) is widely used for internal bleaching because of its oxidative capacity. Both agents have been associated with chemical and structural alterations in dentin; however, the impact of their sequential application on the organic–mineral balance has not been fully elucidated. Objective: To evaluate whether the isolated and sequential application of 5.25% NaOCl and 37.5% HP induces chemical alterations in dentin by analyzing changes in the organic matrix and mineral phase using Fourier-transform infrared spectroscopy (FTIR) and Energy-dispersive X-ray spectroscopy (EDX). Methods: Twenty-four independent dentin sections (n = 6 per group) from six human third molars were distributed using a tooth-balanced allocation into four groups: Control, NaOCl (5.25%, 15 min), HP (37.5%, 30 min), and sequential NaOCl+HP. FTIR assessed organic (amide I, II, III, CH₂) and inorganic (phosphate, carbonate) components through baseline-corrected integrated areas, Full Width at Half Maximum (FWHM), and molecular ratios. Surface elemental composition and the calculated Ca/P atomic ratio were determined by EDX. Multiple sub-measurements per specimen were averaged before statistical analysis. Data were analyzed using Kruskal–Wallis and Mann–Whitney U tests with Bonferroni correction (p < 0.05). Results: FTIR revealed treatment-dependent modifications. NaOCl reduced absorbance in organic-associated bands, indicating collagen degradation, whereas HP altered the mineral phase. The NaOCl+HP group exhibited increased numerical values for integrated band areas, with differences detected in carbonate, phosphate, and amide III bands (p < 0.05), reflecting structural disorganization and modified spectral signal rather than tissue preservation. No differences were detected across the calculated infrared ratios (p > 0.05). EDX showed decreased absolute atomic percentages of Ca, P, and O in the NaOCl+HP group (p < 0.05), indicating structural demineralization, while its stoichiometric Ca/P ratio remained at 1.56. Isolated HP shifted the mineral stoichiometry to the highest numerical Ca/P ratio (1.69; range 1.58–1.80). Fluorine decreased across all treated groups (p < 0.001). Conclusions: Sequential NaOCl and HP application triggers distinct chemical alterations compared to individual treatments, inducing severe structural disorganization of the organic network and absolute mineral depletion of Ca and P. This multi-agent sequence alters dentin stoichiometry, which may compromise the biomechanical integrity of the tissue. Full article

Integrating neural and muscular signals into wearable robotics enables adaptive assistance during real-world tasks. This study proposes a multimodal neural interface for passive exoskeletons that combines electroencephalography (EEG) and electromyography (EMG) signals to classify motor gestures and estimate real-time cognitive and muscular effort, supported by finite-element-based biomechanical modeling. The system was implemented on the Ottobock Shoulder X passive exoskeleton© and validated using synchronous EEG–EMG acquisition via the LiveAmp platform©, a commercially available platform that was not developed specifically for this study. A hybrid CNN–LSTM architecture with deep fusion was employed to enhance robustness and responsiveness under realistic operating conditions. This study proposes a multimodal neural interface for the software-level adaptive assistance of passive upper-limb exoskeletons. While the physical device maintains a static mechanical profile, the proposed digital framework achieves adaptation by interpreting the user’s physiological and motor states. Ten healthy participants performed three functional tasks (screwing, moving the box, and lifting the box) under five assistive conditions. Finite element modeling (FEM) was used to characterize the torque–angle relationship of the passive exoskeleton and to support the interpretation of experimentally observed assistive torque profiles. The FEM model, used as an offline biomechanical analysis tool to aid in the interpretation of experimental results, has not been integrated into the real-time control loop. Results showed an average classification accuracy of 90%, an F1-score of 0.85, and inference latency below 180 ms, confirming real-time applicability. Cognitive indices such as the Cognitive Load Index (CLI) and Frontal Asymmetry Index (FAI) enabled adaptive modulation of assistance strategies without requiring active actuation, thereby preserving the device’s intrinsic passive nature. Comparative torque analysis highlighted the ergonomic benefits of passive systems in mid-range postures, while Finite Element Method (FEM) supported analysis clarified their limitations under highly dynamic loads compared to active solutions. These findings advance multimodal brain–machine interfaces for wearable robotics by integrating physiological sensing, deep learning, and biomechanical modeling, offering a safe, energy-efficient, and adaptive approach with potential rehabilitation, occupational ergonomics, and human–robot applications. Full article

Diabetic foot ulcers represent a severe complication of diabetes mellitus, affecting millions of adults worldwide and often leading to hospitalization and amputation. Diabetic neuropathy increases the risk of plantar injuries, while the lack of continuous monitoring and delayed detection contributes to the progression of these lesions. This study presents a low-cost smart insole system for continuous plantar pressure monitoring and screening of plantar pressure patterns associated with diabetic neuropathy. The system integrates piezoresistive sensors distributed across key regions of the foot, connected to a low-power ESP32 microcontroller for data acquisition. Measurements are transmitted via Bluetooth Low Energy to a mobile application that enables real-time visualization, user management, and storage in a MySQL database for historical data consultation. Data processing employs a convolutional neural network configured to classify plantar pressure patterns between non-diabetic individuals and diabetic patients presenting neuropathic alterations. System validation demonstrated 88% accuracy, 88% recall, and 87% F1-score in classifying plantar pressure patterns. The results confirm that the combination of low-cost hardware and open-source software constitutes a viable and scalable solution for screening biomechanical alterations associated with diabetic foot complications. Full article

The objective of this study is to mitigate the bottom-out failure and improve the energy absorption of conventional helmet liners during high-energy impacts, thereby reducing the risk of head injuries. To this end, a locally reinforced Primitive-type triply periodic minimal surface (P-TPMS) energy-absorbing liner is proposed for the helmet forehead region, which facilitates progressive energy dissipation through layer-by-layer buckling deformation. A finite element model of a helmet–head coupling was created based on a previously verified high-fidelity head model and subsequently validated against the ECE 22.06 standard drop-test methodology. Three critical design parameters—outer protective layer thickness, triply periodic minimal surface (TPMS) unit cell size, and wall thickness—were optimized employing the Box–Behnken Design (BBD) response surface methodology, resulting in quadratic regression models for the head injury criteria (HIC) and peak linear acceleration (PLA) with good fit ($R^2$ > 0.97). Optimal parameter combinations were established using multi-objective optimization, with protective efficacy carefully assessed from both head dynamic response and biomechanical response perspectives. The ideal P-TPMS liner possesses an outer protective layer thickness of 14.95 mm, a TPMS unit cell size of 12.23 mm, and a wall thickness of 3.93 mm. Compared to the traditional expanded polystyrene (EPS) liner, the optimized P-TPMS liner significantly reduces HIC (by ∼16%) and PLA (by ∼14%) while extending the impact duration. More critically, it transitions both intracranial pressure and brain tissue strain below their respective clinical injury thresholds, substantially lowering the risks of skull fracture and mild traumatic brain injury (mTBI). The P-TPMS construction facilitates continuous energy dissipation during impacts via incremental layer-by-layer buckling deformation, hence extending impact duration and markedly improving helmet protective efficacy. These findings offer theoretical foundations and technical direction for the creation of localized heterogeneous liner designs in advanced high-performance helmets, although the results are limited to frontal flat-anvil impact conditions. Full article

Trail running imposes highly variable biomechanical demands due to steep, irregular terrain that renders flat-road pacing models inadequate. We present a physics-based digital twin that integrates a terrain-adaptive grade-adjusted pace (GAP) model with individualised physiological calibration to predict finish time across heterogeneous trail-running races. The GAP core applies Minetti’s fifth-degree metabolic cost polynomial to map slope-dependent energy cost across the full range of uphill and downhill gradients encountered in trail racing. Segment-by-segment pace is further modulated by an altitude–VO₂max correction, a Banister TRIMP-based fatigue term, and a progressive pacing-decay factor. Course-elevation profiles are extracted from 1 Hz barometric altimeter data through a five-step normalisation pipeline. Individual parameters (sustainable VT₂ fraction α; pacing-decay slope μ) were calibrated by grid search against 13 race sessions. A sequential validation across four model-complexity stages showed R² increasing from 0.763 to 0.905. Leave-one-out cross-validation (n = 13) yielded R² = 0.864, MAE = 18.2 min, MAPE = 11.1%, and a small positive bias (+2.0 min). The framework demonstrates that integrating biomechanical terrain correction with individual physiological calibration substantially improves race-time prediction for trail running, offering a promising foundation for athlete-specific pre-race simulation. Full article

Shear Thickening Fluid (STF), as a typical intelligent material, offers a novel approach for developing adaptive protective equipment due to its unique “shear thickening” effect. This review examines STF-based composite materials, encompassing both surface coatings (where STF is dispersed in a polymer matrix applied as a layer) and impregnated structures (where STF is integrated into porous fabric or foam substrates via saturation). It elaborates on design principles, preparation methods, mechanical property modulation, and applications in adaptive protectors for knees, elbows, wrists, ankles, and sports equipment. The review emphasizes how composite strategies overcome STF encapsulation and processing challenges, facilitating laboratory-to-market transition. The core mechanisms underlying the “flexible under normal conditions, rigid upon impact” behavior are discussed at molecular and rheological levels. Key limitations—including fluid leakage, long-term aging, and temperature sensitivity—are critically examined alongside future development trends toward multifunctional, intelligent protective systems. Full article

Objectives: Treadmill walking is often employed for tightly controlled gait and energetics research, but growing evidence suggests that treadmill-based metabolic and biomechanical measurements may not directly reflect the ecologically valid mode of overground walking. While many previous studies focused on older adults, much less is known about how treadmill walking influences gait energetics and spatiotemporal parameters in young healthy adults across matched speeds. We investigated energy expenditure, metabolic cost of walking and spatiotemporal gait parameters in healthy young adults walking overground and on a treadmill at three speeds (slow—1.0, comfortable—1.3, fast—1.5 m/s). Our hypothesis was that at the comfortable speed, treadmill and overground energetics and gait parameters would be comparable. However, at slow and fast speeds, there would be a significant energetic penalty, accompanied by significant differences in spatiotemporal parameters. Methods: Twenty young participants (10 males and 10 females) completed a randomized cross-over walking protocol with a minimum of ten minutes treadmill familiarization at 1.3 m/s. Breath-by-breath oxygen consumption ($\dot{V}{O}_2$) and Respiratory Exchange Ratio were measured using a portable indirect calorimetry system and gait parameters were calculated from Inertial Measurement Units. Gross and net energy expenditures, costs of walking, cadence, average step and stride lengths, and walk ratio were calculated. A three-way mixed ANOVA was used for primary statistical analyses. Results: Treadmill walking was characterized by higher gross and net energy expenditures and metabolic costs (p < 0.001, η_p² = 0.6) across all speeds compared to overground. It was also characterized by faster cadence and shorter average step and stride lengths (p < 0.001, η_p² = 0.9). Additionally, there was an effect of sex (p = 0.01, η_p² = 0.3) on the gait parameters, with females exhibiting a faster cadence and shorter average step and stride lengths than males. Conclusions: Our findings show that treadmill walking imposes a medium-to-large metabolic penalty even in healthy young adults, with compensatory gait adaptations, possibly reflecting increased stabilization demands and altered neuromuscular control strategies. These results underscore the limits of generalizing treadmill derived gait data to overground walking and we caution against the uncritical use of treadmills, especially while trying to understand ecologically relevant human walking mechanics and energetics. Full article

Fatal free falls (FFF) represent a distinct form of blunt force trauma and pose a significant challenge in forensic investigations, particularly in estimating fall height and differentiating between accidental and suicidal events. Postmortem computed tomography (PMCT) enables detailed assessment of skeletal injuries, including quantitative evaluation of skull fracture patterns. Total Cranial Fracture Length (TCFL), derived from three-dimensional CT skull fracture scoring (3D-CT-SF), has been proposed as an objective indicator of impact severity; however, available evidence remains limited. This study aimed to assess the relationship between TCFL and fall height in fatal free falls and to evaluate the influence of selected anthropometric and biomechanical variables on cranial fracture severity. A retrospective analysis of 76 fatal free-fall cases examined between 2016 and 2024 was conducted using PMCT and autopsy data. TCFL was measured on three-dimensional volume-rendered CT reconstructions of calvarial fractures. Statistical analyses were performed for the entire cohort and separately for accidental and suicidal falls. No significant correlation between TCFL and fall height was observed in the overall cohort or among suicide cases. In contrast, a significant negative correlation between TCFL and fall height category was identified in accidental falls. TCFL showed significant positive correlations with body mass, body mass index (BMI), and kinetic energy, particularly in the suicide subgroup. TCFL is a promising objective parameter for assessing the severity of cranial injury in fatal free-fall cases. While its utility in estimating fall height appears limited in suicidal falls, TCFL may support forensic interpretation of fall dynamics and contribute to distinguishing the manner of death, especially in accidental cases. Further studies in larger, more diverse populations are warranted. Full article

Against the backdrop of intelligent and precision agriculture, mechanized harvesting of pulses is crucial for improving productivity and addressing the challenges posed by the changing agricultural workforce structure. However, the biological characteristics of pulses—such as susceptibility to grain breakage, pod shattering, and asynchronous maturity—impose far more stringent demands on threshing and cleaning performance than those for cereal crops. Existing grain combines, when directly applied to pulses, commonly cause high grain breakage during threshing, high cleaning losses, and poor adaptability. This paper systematically reviews the current status and development trends of threshing and cleaning technologies in mechanized pulse harvesting. The core challenges are analyzed from three perspectives: crop biology, technical bottlenecks, and external operational factors. Research progress and breakthrough pathways in low-damage threshing are reviewed in terms of physical and biomechanical properties, flexible threshing elements, multi-stage cylinder structures, multi-field coupled simulation, intelligent control, and energy consumption analysis. Key achievements and breakthrough pathways in high-efficiency cleaning are summarized from aspects of airflow–screen coupling optimization, screening system innovation, numerical simulation, and intelligent detection and control. Based on typical machine models, the structural characteristics and operational applicability of general-purpose and specialized combine harvesters are compared and analyzed. Finally, future development directions are discussed from four perspectives: multifunctionality and generalization, simplification and adaptability, intelligence and precision, and greening and energy efficiency. This paper aims to provide a systematic theoretical reference and technical support for the development, improvement, and industrial application of low-damage, high-efficiency pulse harvesting equipment. Full article

Background: Soccer kicking biomechanics has traditionally focused on lower limbs, overlooking whole-body integration. Three-dimensional motion analyses have demonstrated that upper limbs contribute substantially through tension arc formation, counterbalancing, and kinetic chain coordination. The hand–wrist complex may influence performance through proprioceptive pathways, yet this remains untested. Methods: Following PRISMA-ScR guidelines, we searched PubMed/MEDLINE, Web of Science, and SPORTDiscus (inception—February 2026). Peer-reviewed studies examining kicking mechanics, kinetic chains, and joint proprioception were included. Two reviewers independently screened records and extracted data. Narrative synthesis was used to organize findings across four thematic categories: upper limb biomechanics, kinetic chain principles, wrist–hand stability, and proprioceptive enhancement. Results: From 3847 records, 51 studies (1988–2025) were included. Upper limbs are essential for kicking through tension arc formation, energy transfer, and balance maintenance. Kinetic chains operate bidirectionally; available evidence suggests that proximal segment deficits are associated with substantially increased compensatory demands at distal segments. External joint support has been shown to enhance proprioception and force perception. Conclusions: This scoping review identifies a theoretical rationale and a critical research gap: no direct empirical evidence exists that hand–wrist bandaging affects kicking performance. Evidence from adjacent domains (upper limb kicking biomechanics, kinetic chain theory and proprioceptive enhancement with external supports) provides indirect, translational support for the plausibility of a hypothesis that remains entirely untested. Future research should employ within-subject crossover designs in elite soccer players to determine whether this intervention produces any measurable effect. Practical recommendations to athletes or practitioners are premature and are not supported by the current evidence base. Full article

The biomechanics of frog jumping has been a subject of significant interest in both biology and engineering, driven by the high efficiency of their movement. This study presents the dynamic simulation of a frog’s complete jump cycle, from take-off to landing and re-stabilization, to advance the development of bio-inspired jumping robots for irregular terrains. As a primary contribution, and unlike previous studies that focus exclusively on the propulsion phase, this work addresses all stages, using direct servomotor actuation without mechanical energy storage. Biological joint kinematics were mathematically characterized using Cubic Smoothing Splines. By empirically tuning the smoothing parameter ($p$), the trajectories achieved the continuous differentiability required for electromechanical actuation. These curves were implemented into a 3D multibody simulation (Altair Inspire), where a PID-based tracking framework managed the mechanically nonlinear multibody dynamics governing the jump (arising from contact forces, impacts, and time-varying inertial effects) to ensure stabilization during the complex landing phase. Validating the model against previous studies, the simulation successfully achieved a maximum horizontal jump distance of 24.12 cm (4.02 body lengths) and a peak velocity of 1.45 m/s. The kinematic fidelity of the model was mathematically validated, yielding a maximum Normalized Root Mean Square Error (NRMSE) of 4.121% relative to biological reference trajectories. Furthermore, the robustness of the landing and re-stabilization phases was demonstrated through a continuous double jump covering a total distance of 45.83 cm. Finally, a dynamic scaling analysis was performed to evaluate the feasibility of implementing real motors. Ultimately, this study establishes a mathematically robust framework for replicating frog-inspired jumping dynamics, contributing a transferable methodology for the design and control of articulated bio-inspired robotic systems. Full article

The evaluation of biomechanical parameters in four-beat gaited horses remains limited by the subjectiveness and complexity of current standard methods. Through a deep learning approach, we aimed to infer dissociation % using only acoustic signals. A total of 268 audio samples were extracted from publicly available videos featuring three Brazilian horse breeds (Mangalarga Marchador, Campolina, and Piquira) performing marcha batida and marcha picada. Acoustic features, including root mean square energy (RMS), zero-crossing rate (ZCR), and 13 Mel-frequency cepstral coefficients (MFCCs), were extracted and used to train a long short-term memory (LSTM) neural network. The model accurately predicted the time intervals between successive hoof–ground contacts (R² = 0.98; MAE = 0.0071), enabling the calculation of the dissociation %. While no significant differences were found between gait types and dissociation %, breed-related differences in both mean hoof–ground contact interval and dissociation were observed, with 8 acoustic features demonstrating discriminative power. Our results suggest that hoof–ground contact patterns can be quantified objectively from audio alone, offering a practical and non-invasive method for gait analysis. The approach holds potential for applications in breed standardization, selection, and digital locomotion phenotyping of horse populations. Full article