Search Results (2,526)

Background: Frailty is a common finding in elderly subjects with severe aortic stenosis (AoS) and a strong predictor of mortality and disability after aortic valve surgery. The atherogenic index of plasma (AIP) is related to different cardiovascular (CV) risk factors, which in turn are correlated to the progression of frailty as well as of AoS. Aim: to analyze the association of AIP with different CV risk factors and frailty scores and its value as a determinant of mortality in older adults with severe AoS. Methods: The association of AIP with a multidimensional assessment of frailty by using Fried criteria and the following indices; timed up-and-go test (TUG) for gait function; Charlson Index (CI), basic activities of daily living (BADL) and instrumental activities of daily living (IADL) for disability; mini–mental state examination for cognitive function evaluation (MMSE); Geriatric Depression Score for mood disorder (GDS); Mini Nutritional Assessment (MNA) for nutritional status was assessed in 102 elderly AoS patients (33 males; mean age 83 ± 6 yrs). Moreover, the relationship between AIP and demographic, lifestyle, traditional CV risk factors and CV mortality was also evaluated. Results: Significant relationships between AIP and glycemia and inflammatory parameters (CRP, ESR and fibrinogen) as well as with troponin I were found. Moreover, AIP significantly correlates with CI, BADL, IADL and MNA. However, the Kaplan–Meier analysis did not show any significant difference for survival rates according to AIP intervals of risk, whereas ejection fraction remained the only significant determinant after multivariate adjustment for mortality at the Cox proportional hazard models analysis in this patient population. Conclusions: Higher AIP is significantly associated with cardiometabolic risk and increased physical dysfunction risk and frailty in AoS pts, evidencing its potential use as a simple biomarker in this clinical setting, although it did not represent a significant determinant for mortality in this population. 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

Introduction: Although gait alterations associated with excess body weight have been widely studied, most available evidence comes from laboratory-based analyses, which limit ecological validity and the translation of findings into clinical practice. This study addresses this gap by examining gait biomechanics across BMI categories using portable sensor-based insoles that allow gait assessment in real-world conditions. Methods: A cross-sectional study including 96 adults categorized as normal weight (NW), overweight (OW), or obese (OB) was conducted. Gait biomechanics were recorded using PODOSmart^® intelligent insoles, which capture spatiotemporal and angular parameters during natural walking. Foot health, quality of life and comorbildities were evaluated throught valeted questionnarires. Differences between groups were analyzed using ANOVA and chi-square tests. Age and sex, known to influence gait, were comparable across BMI groups and were considered in the interpretation of the results. Results: Overall, the participants in the OB group exhibited reduced stride length, gait speed, and swing time, increased double-support time, and greater pronation–supination and progression angles than OW and NW participants. Partial eta-squared values (η²p) were predominantly medium to large, reinforcing the robustness of these between-group differences (e.g., double-support time, p > 0.001; η²p = 0.19). Individuals with obesity reported poorer general and foot health and more difficulty finding suitable footwear. BMI was also significantly associated with hypertension, dyslipidemia, arthritis, and depression (all p <0.05), whereas diabetes, cardiopathies, knee pain, and fatigue andwalking or social activity limitations showed no significant differences. Conclusions: By using portable gait analysis technology in ecological conditions, this study provides novel evidence of clinically meaningful gait impairments across BMI groups. Higher BMI is associated with clinically relevant gait impairments, poorer perceptions of foot and general health, and a higher prevalence of several comorbidities. Full article

The Chopart amputation is a controversial amputation level and has been described as a relatively non-functional amputation due to the increased risk for stump deformity and subsequent complications. Recent literature has shown that a tibiotalocalcaneal arthrodesis can subjectively increase function in the Chopart amputation. We describe the use of a tibiotalocalcaneal arthrodesis in a 44-year-old diabetic male with a Chopart amputation for the purpose of limb and gait salvage. After 292 days and an uneventful postoperative course, the patient consented to gait analysis. The case allows us to objectively conclude that the tibiotalocalcaneal arthrodesis can quantitatively increase the functionality of the Chopart amputation and, in turn, expand its indication for use within the more functional populations. Full article

Abnormal gait associated with neuromuscular and musculoskeletal disorders represents a growing clinical burden, particularly in aging populations. This study presents a modular, low-cost Smart Rehabilitation Walker (SRW) that integrates multimodal sensing and real-time haptic feedback to enable simultaneous gait monitoring and corrective intervention in both clinical and home environments. The system combines force-sensing resistors for bilateral load symmetry assessment, inertial measurement units for fall detection, and surface electromyography (sEMG) for neuromuscular activity monitoring within a closed-loop assistive feedback architecture. A 15-day pilot study involving ten individuals with rheumatoid arthritis and clinically observed neurological gait abnormalities demonstrated measurable improvements in gait biomechanics. The Force Symmetry Index (FSI), calculated using the Robinson symmetry metric, decreased from an average of 0.9691 to 0.2019, corresponding to a 79.26% average reduction in inter-limb load asymmetry. Concurrently, sEMG measurements showed a substantial increase in neuromuscular activation (ΔEMG = 4.28), with statistical analysis confirming a significant improvement across participants (paired t-test: t(9) = 13.58, p < 0.001). To model rehabilitation trajectories, a nonlinear predictive framework based on Gaussian Process Regression achieved high predictive accuracy (R² ≈ 0.9, with a mean RMSE of 0.0385), while providing uncertainty-aware trend estimation. Validation using an independent amyotrophic lateral sclerosis gait dataset further demonstrated the transferability of the analytical pipeline. These results highlight the potential of sensor-enabled assistive walkers as scalable platforms for quantitative gait rehabilitation, adaptive feedback, and long-term mobility monitoring. Full article

Peripheral nerve injuries often lead to incomplete recovery despite surgical repair. Vitamin B12 and folic acid have been implicated in nerve regeneration, but their comparative effects have not been systematically evaluated. Twenty-four male Wistar rats underwent femoral nerve transection and were assigned to three groups: control, vitamin B12 (2500 µg/kg weekly, subcutaneous), and folic acid (40 mg/L in drinking water). Functional recovery was assessed over eight weeks using foot-base angle (FBA) during beam walking. Histological analysis evaluated axon counts and myelination (g-ratio). Both treatments accelerated early gait recovery compared to controls, with significant FBA improvement at week 4 (p < 0.05). Vitamin B12 produced sustained functional benefits through week 8 and superior myelination (lower g-ratio, p < 0.0001), whereas folic acid increased axon numbers but did not enhance myelin thickness or late-phase recovery. High-dose vitamin B12 significantly improves structural and functional outcomes after femoral nerve injury, while folic acid primarily supports early axonal regrowth. Vitamin B12 represents a promising pharmacological adjunct for peripheral nerve repair. Further research should explore optimal dosing strategies and long-term effects in clinical settings. To our knowledge, no prior study has directly compared the effects of folic acid and vitamin B12 supplementation within the rat femoral-nerve model, providing the rationale for the present head-to-head design. Full article

In-pipe robots must navigate narrow, curved passages where rigid mechanisms often require bulky steering units. Soft crawlers offer better compliance but typically rely on multiple actuators or reconfigurable contacts to achieve multi-directional motion. Drawing inspiration from biological soft crawlers that exploit directional friction and coordinated anchor–slip patterns, this study focuses on locomotion principles observed in caterpillars, water boatmen, and whirligig beetles. Based on these bioinspired concepts, we present a tendon-driven soft in-pipe robot that combines continuum bending–twisting deformation with modular anisotropic friction pads (AFPs), enabling three locomotion modes using only two motors. AFP inclination, curvature, and ridge geometry were optimized through friction tests, constant-curvature modeling, and finite element analysis to enhance directional adhesion on flat and curved surfaces. A deformation-based locomotion framework was developed to couple tendon actuation with friction orientation, achieving longitudinal crawling, transverse translation, in-place rotation, and smooth transitions via programmed twisting. Driving experiments demonstrated repeatable anchor–slip locomotion with average speeds of 28.6 mm/s, 15.7 mm/s, and 11.5°/s for the three modes. Pipe tests in straight, curved, and T-junction sections further validated stable contact and reliable gait transitions. These findings highlight the potential of friction-programmed continuum robots as compact, bioinspired platforms for advanced in-pipe inspection and diagnostic tasks. Full article

This study introduces a novel unsupervised framework, ICR-LLS, for detecting pathological gait patterns using instantaneous center of rotation (ICR) trajectories of the shank in the sagittal plane. ICR trajectories were computed from two-dimensional kinematic data captured at the lateral femoral epicondyle and lateral malleolus for both shanks, producing four-dimensional multivariate time series for each gait trial. Pairwise trajectory dissimilarities were quantified using circularly aligned Dynamic Time Warping (DTW), preserving temporal and spatial structure. The resulting dissimilarity matrix was embedded into a three-dimensional space using a force-directed network layout, enabling intuitive visualization of inter-subject gait relationships. Density-based clustering (DBSCAN), enhanced with a consensus-based ensemble approach, was employed to automatically identify clusters representing typical (healthy) gait patterns and outliers corresponding to pathological deviations. The framework is evaluated on a public dataset comprising individuals with Parkinson’s disease (PD) and healthy controls, achieving a normalized mutual information (NMI) of 0.449 and a Separation-to-Compactness Ratio (SCR) of 6.754, indicating a meaningful cluster structure. In addition, classification-oriented metrics yield an accuracy of 90%, sensitivity of 70%, and specificity of 96.7%, supporting the method’s effectiveness in distinguishing pathological gait. By combining minimal 2D kinematic inputs with unsupervised learning, ICR-LLS provides an interpretable framework for the exploratory analysis of gait variability, and although further validation is required, the findings suggest that ICR trajectories may serve as a meaningful biomechanical descriptor for characterizing pathological locomotion. Full article

Background/Objectives: Older patients with fractures often present with a complex interplay of factors associated with frailty and functional decline. The emerging concept of Orthogeriatric Fracture Syndrome (OFS) aims to characterize these distinct relationships of pathologies and outcomes. Despite increasing recognition of OFS in clinical practice, due to the distributed nature of fragility factors across medical disciplines, it remains poorly defined in the literature. Methods: We used large-scale text mining of 26 million PubMed abstracts to quantify the occurrence and interrelationship of OFS-related concepts across all disciplines in biomedical research. Results: OFS terms were more prevalent in fragility fractures than in other fracture types, particularly osteoporosis (0.52 vs. 0.09, p < 0.05). In pairwise keyword correlation (Pearson φ), the correlations presented between OFS keywords are comparable to the ones in the more established metabolic syndrome (e.g., φ = 0.07 between stroke and hypertension, p < 0.05). For OFS, osteoporosis emerged as the central node linking OFS outcomes and pathologies, correlating with fragility fracture (φ = 0.176, p < 0.05) and sarcopenia (φ = 0.03, p < 0.05). Sarcopenia in turn correlated with gait (φ = 0.04, p < 0.05), malnutrition (φ = 0.05, p < 0.05), and frailty (φ = 0.032, p < 0.05). Old age keywords showed substantially higher association with OFS keywords (e.g., φ = 0.06 for elderl* and hip fracture, p < 0.05) than with metabolic syndrome terms (elderl* and insulin resistance, p > 0.05). Conclusions: Overall, the analysis showed statistically significant associations between keywords representing OFS outcomes, pathologies and old age. The combined occurrence of osteoporosis, sarcopenia, frailty and risk of falls may help conceptually identify older adults at risk and inform preventive measures. This large-scale bibliometric analysis supports OFS as a conceptually coherent, proposed theoretical framework for cross-disciplinary awareness and coordinated care, with a literature-level organizational pattern comparable to metabolic syndrome, however, pending prospective clinical validation. This study reframes fragility fractures as the endpoint of a broader, potentially modifiable risk constellation and underscores the need for further clinical and epidemiological validation. Full article

Cognitive impairment is a prevalent non-motor manifestation of Parkinson’s disease (PD), yet early detection remains limited by the sensitivity of conventional cognitive assessments. Emerging evidence suggests that motor dysfunction, particularly gait and balance abnormalities, reflects underlying cognitive vulnerability. This study examined motor–cognitive associations and evaluated whether motor-derived features can be used to classify low-MoCA status in PD without direct cognitive testing. Data from 102 individuals with PD were analyzed, incorporating clinical assessments, physical function measures, lifestyle factors, and gait-derived biomarkers. Multiple regression identified Unified Parkinson’s Disease Rating Scale Part III, stride length of the more affected side during 360° turning at preferred speed, and maximum ankle jerk on the less affected side during forward walking as independent predictors of Montreal Cognitive Assessment scores, collectively explaining 34.7% of the variance. Network analysis revealed integrative relationships among global motor severity, gait smoothness, and cognitive performance. Using a compact motor-based feature set, logistic regression achieved a mean accuracy of 65.8% and an AUC of 0.737 in classifying low-MoCA status under cross-validation. These findings demonstrate that motor-derived digital biomarkers capture clinically meaningful information about cognitive status in PD and may serve as adjunctive tools for identifying cognitive vulnerability in clinical settings. Full article

Nonlinear analysis provides a framework for understanding the complexity and stability of human locomotion by capturing dynamic patterns beyond linear methods. This study examined the effect of data length on seven nonlinear measures: Sample Entropy (SpEn), Approximate Entropy (ApEn), Lyapunov Exponents using Wolf’s (LyE_W) and Rosenstein’s (LyE_R) algorithms, Detrended Fluctuation Analysis (DFA), Correlation Dimension (CD), and the Hurst–Kolmogorov process (HK). A 3500-frame kinematic dataset from a healthy adult performing motor-assisted elliptical training and treadmill walking was segmented from 100 to 3500 frames in 10-frame increments. Data from treadmill and elliptical conditions were analyzed and presented in a combined manner to highlight general stabilization trends across locomotor tasks. Results revealed that increasing data length significantly affected all nonlinear metrics (p ≤ 0.0005). Stabilization occurred at varying minimum lengths: SpEn at ~4.5–8.8 s (540–1060 frames), ApEn at ~5.4–7.7 s (650–920 frames), LyE_W at ~19.1–29.2 s (2290–3500 frames), LyE_R at ~1.3–1.5 s (150–180 frames), DFA at ~29.2 s (3500 frames), CD at ~1.7–15.9 s (200–1910 frames), and HK at ~9.1–9.8 s (1090–1180 frames). Notably, HK achieved stable estimates in approximately one-third of the time required for DFA and substantially less than LyE_W, supporting its suitability for time-constrained or clinical settings. These findings suggest the need to tailor data collection to each nonlinear metric and to report data length explicitly to improve accuracy, reproducibility, and methodological rigor in gait variability research. However, these findings should be interpreted within the limitations of a single-participant, exploratory design. Full article

Knee joint moment is an important biomechanical parameter for sports assessment, rehabilitation monitoring, and human–machine interaction. However, direct measurement is often restricted to laboratory-based settings. Surface electromyography (sEMG) offers a non-invasive alternative for indirect joint moment estimation, but many existing deep learning models remain too computationally demanding for potential wearable edge deployment. To address this gap, this study proposes Topo2DCNN-LSTM, a lightweight two-dimensional (2D) convolutional neural network model, designed for sagittal-plane knee flexion moment estimation. The model used a feature-based sequential representation, transforming raw sEMG signals into compact Root Mean Square (RMS) feature frames. The input was processed by a lightweight 2D convolutional neural network (CNN) encoder and paired with long short-term memory (LSTM) units. The model was trained on a public walking dataset of healthy subjects with synchronized sEMG and joint kinetics at two treadmill speeds. When compared with selected deep learning baselines, the quantized model achieved a mean RMS Error of 0.088 ± 0.020 Nm/kg at 1.2 m/s and 0.114 ± 0.034 Nm/kg at 1.8 m/s. On a SparkFun Thing Plus–SAMD51, it achieved an average inference latency of 28 ms using 71,316 bytes of random-access memory (RAM) and 257,172 bytes of flash. These results support its use as a proof of concept for personalized unilateral knee moment estimation with isolated on-device inference feasibility under resource-constrained and limited walking conditions. Full article

Background: Aquatic therapy is increasingly used in post-stroke rehabilitation, but its effects on balance and gait in the chronic phase remain variably reported. This systematic review aimed to evaluate the effects of aquatic therapy, alone or combined with land-based rehabilitation, on balance and gait in individuals with chronic stroke. Methods: A systematic search of PubMed, Embase, Scopus, and Web of Science was conducted between February and March 2026. Randomized controlled trials enrolling adults with chronic stroke and evaluating aquatic-containing interventions with quantitative balance and/or gait outcomes were included. Owing to clinical and methodological heterogeneity, the primary synthesis was narrative. An exploratory random-effects meta-analysis was additionally performed for post-intervention Berg Balance Scale (BBS) scores. Results: Thirteen randomized controlled trials involving 468 participants were included. Overall, aquatic therapy was associated with more consistent improvements in balance than in gait, while combined aquatic and land-based programs generally showed broader functional gains than land-based rehabilitation alone. In the exploratory meta-analysis, the primary pooled analysis of four studies favored aquatic-containing interventions for post-intervention BBS scores (MD = 3.69, 95% CI 2.69 to 4.69; p < 0.001), with no observed heterogeneity (I² = 0%). Conclusions: Aquatic therapy may be a useful adjunctive rehabilitation strategy for improving balance in chronic stroke, whereas effects on gait appear more variable. These findings should be interpreted cautiously because the quantitative synthesis was exploratory and the overall evidence base remains heterogeneous and limited by small sample sizes and short follow-up. Full article

Cerebellar Ataxia, Neuropathy and Bilateral Vestibular Areflexia Syndrome (CANVAS) is a progressive multisystem disorder characterized by cerebellar ataxia, sensory neuropathy and bilateral vestibular failure. Although intensive rehabilitation is commonly recommended, the actual effectiveness and the most appropriate physiotherapeutic strategy for CANVAS have not been clearly established. Background/Objectives: To evaluate the effects of an integrated rehabilitation program combining neurocognitive therapeutic exercise and focal muscle vibration (FMV) on clinical and instrumental measures of gait, balance and postural stability in a CANVAS patient. Methods: A structured protocol consisting of neurocognitive therapeutic exercise and FMV was administered. Clinical measures included the Berg Balance Scale, Tinetti, SARA and SF-36. The instrumental evaluations included stabilometry and gait analysis. Results: The intervention produced improvements in balance scores associated with a reduction in fall risk. Stabilometry revealed reduction in oscillation area. Conclusions: FMV combined with neurocognitive therapeutic exercise may promote clinical and biomechanical improvements in CANVAS. Full article

Virtual reality (VR) has been increasingly adopted as a digital tool in rehabilitation for balance training, coordination improvement, and motor recovery, yet the literature remains dispersed across clinical rehabilitation, exercise-based interventions, and broader motor-related applications. This fragmentation makes it difficult to determine how the field has evolved and where research emphasis has shifted. This study mapped the research landscape and thematic evolution of VR for balance, coordination, and motor rehabilitation using bibliometric analysis and topic modeling. A total of 1258 articles indexed in the Web of Science Core Collection from 2011 to 2025 were analyzed. Only English language articles and reviews relevant to VR-based balance, coordination, or motor rehabilitation research were included, yielding a final dataset of 1258 publications. CiteSpace and VOSviewer were used to examine keyword co-occurrence, clustering patterns, and temporal trends, while Latent Dirichlet Allocation (LDA) was applied to identify latent themes and their temporal dynamics. The field has moved beyond early feasibility testing toward a more differentiated landscape shaped by distinct clinical targets, population groups, and training purposes. Seven recurring themes were identified, including vestibular rehabilitation and immersive training, post-stroke upper-limb rehabilitation, efficacy and adverse-effect assessment, balance and gait training interventions, evidence synthesis and review-based evaluation, elderly exercise and cognitive interventions, and skill-oriented virtual task training with recent expansion toward broader population groups and task-specific applications beyond traditional rehabilitation settings. VR research on balance, coordination, and motor rehabilitation has evolved into a more thematically differentiated field rather than remaining a single rehabilitation-oriented domain. By combining bibliometric mapping with topic modeling, this study clarifies where evidence is concentrated and which thematic directions are gaining visibility, providing a clearer basis for future evidence synthesis and more comparable intervention reporting. Full article