Search Results (2,053)

Background: Cemented and cementless fixation techniques in total hip arthroplasty (THA) each present distinct biomechanical properties and perioperative risk profiles. While cementless fixation has gained increasing popularity, large-scale nationally representative comparisons of perioperative outcomes between cemented and cementless elective THA remain limited. This study aimed to compare complication rates, healthcare utilization, and temporal trends between cemented and cementless elective THA using the National Inpatient Sample. Methods: A retrospective cohort study was conducted using the National Inpatient Sample database from 2016 to 2021. Adult patients undergoing elective primary total hip arthroplasty were identified using ICD-10-PCS codes and categorized into cemented and cementless fixation groups. Patient demographics, comorbidities, indications, postoperative complications, length of stay, hospital charges, and in-hospital mortality were compared. Multivariate logistic regression analysis was performed to evaluate the independent association between fixation type and postoperative complications while adjusting for demographic, clinical, and hospital-level variables. Results: A total of 81,668 elective THAs were identified, including 40,290 cemented (49.33%) and 41,378 cementless (50.67%) procedures. Cemented THA was associated with a shorter length of stay (2.09 ± 1.88 vs. 2.26 ± 2.47 days, p < 0.001) and lower total hospital charges ($65,584.53 ± 48,797.21 vs. $72,186.84 ± 49,860.20, p < 0.001). Unadjusted analyses demonstrated higher rates of acute kidney injury and sepsis in the cementless group. After multivariate adjustment, cemented fixation was associated with lower odds of acute kidney injury (OR 0.87, 95% CI 0.79–0.96, p = 0.004). However, cemented THA was associated with higher odds of postoperative delirium (OR 1.20, 95% CI 1.02–1.42, p = 0.030), blood transfusion (OR 1.27, 95% CI 1.17–1.37, p < 0.001), and periprosthetic fracture (OR 1.32, 95% CI 1.02–1.71, p = 0.035). Rates of myocardial infarction, pneumonia, venous thromboembolism, urinary tract infection, and in-hospital mortality were similar between groups. Temporal analysis demonstrated comparable utilization trends, with a decline in elective procedures during 2020–2021. Conclusions: In this nationwide analysis, cemented total hip arthroplasty was associated with lower risk of acute kidney injury, shorter length of stay, and lower hospital charges, but higher odds of postoperative delirium, blood transfusion, and periprosthetic fracture compared with cementless fixation. These findings highlight distinct perioperative risk profiles between fixation strategies and may assist surgeons in individualized decision-making for elective total hip arthroplasty. Full article

Transparent clinical decision-making remains a critical barrier to deploying deep learning in medical diagnosis. Post hoc explanation methods approximate model behaviour after training but cannot guarantee that explanations faithfully reflect the underlying reasoning. This study proposes a Self-Explaining Neural Network (SENN) for Parkinson’s Disease (PD) screening via Ground Reaction Force (GRF) gait analysis, enforcing intrinsic interpretability through learnable basis concepts and input-dependent relevance scores computed jointly with the prediction. The architecture combines a four-block residual CNN backbone with stochastic depth regularisation, a 16-concept encoder with diversity and stability constraints, and temperature-scaled probability calibration for reliable clinical operating points. Evaluated on the PhysioNet Gait in Parkinson’s Disease dataset (306 subjects, 16 GRF sensors per foot), SENN achieves a subject-level ROC-AUC of 0.916 [95% CI: 0.867–0.964], sensitivity of 0.913 [0.862–0.963], specificity of 0.671 [0.485–0.858], and Average Precision of 0.942 [0.918–0.967], reported across five independent random seeds. Comparative evaluation against four deep learning baselines—CNN-Residual, BiLSTM, CNN-LSTM, and CNN-Attention—confirms that the interpretability constraints impose no statistically significant reduction in discriminative performance, with all pairwise ROC-AUC confidence intervals overlapping. Concept-level analysis reveals that the three most discriminative concepts correspond to disrupted midfoot loading patterns, increased step-length variability, and bilateral cadence asymmetry—all established biomechanical hallmarks of parkinsonian gait—providing clinically grounded, patient-specific explanations without post hoc approximation. These findings demonstrate that rigorous intrinsic interpretability and competitive predictive accuracy are simultaneously achievable in deep gait analysis, supporting the clinical adoption of transparent diagnostic AI. Full article

Wheelchair users face significant mobility limitations related to both medical issues (e.g., musculoskeletal strain, pressure ulcers) and urban accessibility challenges. This pilot study introduces a sensor system integrating an inertial measurement unit (IMU), GPS (Global Positioning System), and a pressure-measuring seat to monitor distance travelled, speed, and posture in relation to real-world conditions. Seven participants navigated an approximately 800-metre outdoor course, divided into 13 sections, while real-time data were recorded. The results showed an average speed of 1.24 ± 0.41 m/s with peak speeds of up to 2.67 m/s. The centre of pressure on the seat fluctuated by an average of 25 mm in the x and y directions (left-right: COPx, back-forward: COPy). The data for average speed, COPx, and COPy showed significant differences between most of the 13 sections, with large, very large, and huge effect sizes. Comparing the speed, COPx, and COPy data with respect to distance travelled, and correlating them between the seven participants by applying the rank-sum method to the mean R² and calculating Kendall’s W, revealed that speed, COPx, and COPy were influenced by course conditions (R² medians between 0.013 and 0.499; W = 0.7857, strong agreement; χ²p = 0.0281). Small R² values indicate more individualised participant behaviour, while large R² values highlight the stronger influence of course conditions on the parameters. This non-invasive and cost-effective system provides objective motion data that can be used for future research in wheelchair design and rehabilitation strategies. Despite its advantages, this study was limited to able-bodied participants, so further clinical trials with individuals with mobility impairments are needed. Full article

Lumbosacral and thoracolumbar kinematics are key risk factors for lifting-related low back pain, yet their measurement is typically restricted to motion capture laboratories. Inertial measurement units (IMUs) offer the potential to quantify spine kinematics in more naturalistic settings, but the validity of IMU-based processing pipelines relative to optical motion capture (OMC) remains unclear. Nine healthy participants performed stoop, squat, free, and asymmetric lifting tasks while IMU and OMC data were simultaneously collected to evaluate the concurrent validity of two IMU pipelines: the proprietary MVN Analyze pipeline and an OpenSense pipeline using a validated OpenSim biomechanical model for lifting. Joint angles from both pipelines were compared against OMC-derived joint angles calculated using the same validated OpenSim model with one-way repeated-measures statistical parametric mapping (SPM) (α = 0.05), Bland–Altman analysis with Limits of Agreement (LoA) and 95% Confidence Intervals (CIs), and Concordance Correlation Coefficients (CCCs) with 95% CIs. Xsens MVN Analyze consistently overestimated flexion-extension at both spinal levels across all lift types (lumbosacral: RMSE ≤ 9.8◦, bias ≤ −14.5◦, LoA ≤ ±10◦; thoracolumbar: RMSE ≤ 5.4◦, bias ≤ −8.3◦, LoA ≤ ±5◦), with SPM confirming significant differences during the lifting and lowering phases of all lifting cycles. In contrast, processing Xsens data with OpenSense using the same biomechanical model as the OMC data yielded excellent agreement with OMC (RMSE ≤ 2.9◦, bias ≤ 3◦, LoA ≤ ±10◦). CCC was poor to moderate, specifically in lateral bending and axial rotation planes, likely reflecting limited between-participant ROM variability. These results suggest that discrepancies are driven primarily by biomechanical model differences rather than sensor or sensor fusion limitations. Ultimately, when paired with an appropriate biomechanical model, XSens sensors show promise for practical field-based assessment of lifting biomechanics, potentially requiring only sensors at the chest and pelvis. Full article

Proximal femoral fractures associated with osteoporosis are an important clinical problem, yet how bone quality independently influences stress distribution remains insufficiently understood. This study aimed to quantitatively compare surface stress distribution between normal and osteoporotic proximal femoral models using thermoelastic stress analysis (TSA). Fourth-generation composite femurs with identical external geometries were subjected to cyclic compressive loading at a 9° adduction angle, with different maximum loads applied to avoid structural failure (normal: 1900 N; osteoporotic: 1000 N). TSA was performed using an infrared lock-in system to obtain surface stress maps, and stress values were evaluated across key proximal regions and along the medial and lateral cortices. The osteoporotic group showed higher maximum stress values in the medial neck (−37.79 vs. −11.52 MPa), lateral neck (24.70 vs. 8.75 MPa), and intertrochanteric crest (−17.98 vs. −6.05 MPa), corresponding to approximately 1.8–3.5-fold increases compared with the normal model values normalized to 1000 N. Mean stress values were also higher by approximately 1.9–2.4-fold across regions. These results suggest that reduced bone quality is associated with increased proximal stress concentration. They may also help guide implant and fixation strategies, including stem selection and fixation configuration, by identifying regions susceptible to stress concentration under different bone quality conditions. 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 squat is a fundamental multi-joint movement widely studied in strength training and biomechanics. While numerous experimental and computational studies have examined squat kinematics and joint loading, the mechanisms governing how squat technique adapts to increasing external load remain insufficiently understood. In particular, inverse-dynamics-based approaches often overlook explicit constraints imposed by limited joint moment capacity. This study presents a computational framework for predicting load-dependent adaptations of squat posture. The human body was represented as a multi-segment rigid-body system, with joints modeled as nonlinear rotational elements with bounded moment capacity. A reference squat trajectory was first generated kinematically, and a constrained optimization procedure was then applied at each motion frame to determine a mechanically admissible posture under increasing barbell load. The results show that higher loads lead to systematic posture adaptations, including increased torso inclination and redistribution of rotational demand from the knee toward the hip joint. For the highest load, peak torso pitch increased from 30° to over 40°, while joint utilization exceeded unity, indicating the onset of yielding. These findings identify joint moment capacity as a key constraint governing squat technique and demonstrate the potential of the proposed framework for predictive biomechanical analysis. 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

Apical prolapse, a common form of Pelvic Organ Prolapse (POP), is often linked to weakened support structures such as the uterosacral (USL) and cardinal ligaments (CL), influenced by factors like vaginal childbirth, aging, and obesity. Although surgical mesh use is expected to increase, the Food and Drug Administration (FDA) banned polypropylene mesh for transvaginal anterior compartment prolapse in 2019 due to safety concerns, highlighting the need for alternatives such as biodegradable implants. This study developed four biodegradable mesh implants (square and sinusoidal geometries) mimicking the USL and CL. These were applied within a computational pelvic model to assess biomechanical behavior during the Valsalva maneuver and to explore different fixation methods (continuous, interrupted and simple stitch sutures). Baseline analysis of the healthy model established vaginal displacement under normal conditions. Without implant support, complete CL rupture increased displacement by 34%, and complete USL rupture raised displacement by 69%. Polycaprolactone implants consistently reduced anterior vaginal wall displacement in all impairment scenarios. Square implants mimicking the USL reduced displacement by up to 10% in cases of complete USL rupture with intact CL. Similarly, square implants mimicking the CL reduced displacement by up to 15% with complete CL rupture and healthy USL. Simulations with both ligaments impaired showed that USL contribute to support, while CL play a key role in stabilization. These findings demonstrate the potential of biodegradable implants to enhance POP repair. However, further studies are needed to evaluate long-term degradation and clinical applicability. Full article

Background/Objective: Postoperative recovery after spine surgery varies substantially and cannot be fully explained by structural pathology alone. This study evaluates postoperative outcomes using a structured 2 × 2 Surgical Trauma Gradient integrating exposure-related invasiveness (minimally invasive vs. open) and biomechanical strategy (decompression vs. fusion), and examines the modifying role of Type-D personality. Methods: This observational cohort study included 200 patients undergoing elective spine surgery. Patients were stratified into four surgical subgroups: minimally invasive decompression, open decompression, minimally invasive fusion, and open fusion. Primary outcomes included pain intensity (Visual Analog Scale), functional disability (Oswestry Disability Index), patient satisfaction (Patient Satisfaction Index), and postoperative complications at 12-month follow-up. Surgical invasiveness was modeled both categorically and as an ordinal gradient. Multivariable regression, logistic regression, interaction analysis, and longitudinal mixed-effects models were applied. Results: Postoperative outcomes demonstrated a consistent gradient across increasing surgical burden. In multivariable models, higher surgical invasiveness independently predicted greater residual pain (β = 0.69; 95% CI 0.55–0.82; p < 0.001) and higher functional disability (β = 6.20; 95% CI 5.10–7.30; p < 0.001). Increasing invasiveness was also associated with lower patient satisfaction (β = −0.38; 95% CI −0.47 to −0.29; p < 0.001) and higher complication risk (OR = 1.64; 95% CI 1.12–2.41; p = 0.01). Type-D personality independently predicted worse postoperative pain (β = 0.41; p = 0.008) and significantly modified the association between surgical burden and pain (interaction β = 0.22; p = 0.012). Conclusions: Postoperative outcomes follow a structured Surgical Trauma Gradient influenced by both surgical burden and psychosocial vulnerability, particularly Type-D personality. Integrating these dimensions may improve perioperative risk stratification and support individualized treatment strategies. 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

Objective: Functional training exercises involve complex multi-joint movements that challenge traditional rule-based or data-driven recognition systems. This paper introduces a Movement Description Language (MDL) designed to formally represent, analyze, and evaluate such exercises using camera-based pose estimation and interpretable, composable structures. Methods: The proposed MDL models each exercise as a finite-state machine defined by pose-derived angle proxy transitions, allowing movements to be described in a modular and reusable way. Demonstrated with MediaPipe landmark extraction from monocular video, while the MDL remains compatible with any pose estimation algorithm, the framework focuses on exercise phase detection and repetition counting. Experimental validation was conducted on a dataset of 1513 videos of 12 functional exercises (squats, deadlifts, lunges, shoulder presses, planks, push-ups, pull-ups, bent-over rows, box jumps, thrusters, overhead squats, and burpees) obtained from public pose datasets, competition footage, and recordings of 9 participants in real-world environments. Results: Automated repetition counts were compared against manually annotated ground truth, showing an overall repetition-counting accuracy of 97.2%, with a mean per-exercise accuracy of 98.8% (range 95–100%). The MDL successfully handled both simple and compound exercises, maintaining reliable phase detection despite variations in execution speed, camera perspective, and environmental conditions. Conclusion: The system was implemented using real-time pose estimation to demonstrate the practical execution of the MDL framework. The proposed MDL provides a transparent, extensible, and computationally efficient framework for functional exercise analysis. By bridging human-readable movement semantics with executable motion logic, it enables interpretable automatic repetition counting and phase detection, offering an alternative to black-box recognition approaches. The results support its potential for scalable deployment in training, monitoring and movement analysis applications. The proposed system is not intended for biomechanical measurement or clinical-grade kinematic analysis, but rather for interpretable modeling of exercise structure and repetition detection using approximate pose-derived signals. 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

Titanium and its alloys are used in dental and orthopedic implants. However, long-term stability remains a clinical challenge. To overcome this limitation, surface modification has been investigated to improve surface properties. Our previous study demonstrated that the immobilization of secretory leukocyte protease inhibitor (SLPI) on the titanium surface promotes osteoblast adhesion, proliferation, and differentiation in vitro. The current study demonstrated the first in vivo evaluation of SLPI as a bioactive coating for medical implants. Grade 5 titanium screws were coated with 10 µg/mL of recombinant human SLPI (rhSLPI) for 24 h via simple physical adsorption, and the results were preliminarily validated via FE-SEM and ELISA. These SLPI-coated titanium screws (TiSs) were then placed in the tibia of Sprague–Dawley rats for 4 and 8 weeks. The hematological and biochemical parameters (BUN, Creatinine, AST, and Troponin I) demonstrated no acute systemic alterations within the 8-week period across all groups. Moreover, micro-computed tomography (micro-CT) and histological analysis revealed significantly higher bone volume fraction (%BV/TV) at 4 weeks compared to uncoated controls (20.64% ± 2.452% vs. 11.73% ± 0.524%). Finally, the biomechanical stability of implants, assessed using the removal torque test, showed that TiSs showed higher strength compared to Ti at both 4 and 8 weeks. In conclusion, this study represents a novel approach to transitioning rhSLPI-coated titanium evaluation from in vitro models to an in vivo rat model. rhSLPI surface functionalization enhances early-stage osseointegration and improves implant mechanical stability without acute hematological and biochemical alterations. These proof-of-concept findings suggest the potential of SLPI as a bioactive coating strategy. Full article

Inertial measurement units (IMUs) present promising avenues for performance diagnostics in skateboarding, yet systematic validation of their accuracy and applicability remains limited. This study validates the commercially available Spinnax Freak IMU system in the context of skateboarding, with a focus on selected trick detection and classification, distance measurement, maximal horizontal speed, maximal vertical height of the skateboard and airtime during a jump trick. A total of 23 skateboarders (4 females, 19 males; 27.4 ± 10.9 years) participated in this study. Validation methods included comparisons with established reference systems such as laser ranging for maximal horizontal speed (LAVEG), 2D video analysis for maximal vertical height of the skateboard (Kinovea), light barrier measurements for airtime detection (OptoJump Next), and a fixed metric reference (10 m) for rolling distance measurements. The evaluation was supported by statistical analyses including mean absolute error (MAE), root mean-square error (RMSE), mean absolute percentage error (MAPE), t-tests, Bland–Altman plots, linear regression, and ICC(3,1). The Spinnax Freak system demonstrated high validity in detecting trick events and in providing distance measurements that were statistically equivalent to the reference. Trick classification, maximal horizontal speed, maximal vertical height of the skateboard and airtime showed substantial errors, indicating that these outputs are not reliable for biomechanical interpretation at this point. These findings highlight both the potential and the current constraints of single-sensor setups for field-based motion capture in skateboarding. Future developments should prioritize algorithmic refinement, improved temporal resolution, and optimized event classification to enhance measurement accuracy and expand applicability in biomechanical analysis and automated training documentation in skateboarding. Full article