Search Results (456)

This paper presents a low-cost, modular ankle–foot prosthesis that integrates an S-shaped compliant foot with a parallel spring–short-stroke actuator branch to balance energy return, impact attenuation, and rapid personalization. The design follows an FDM-oriented CAD/CAE workflow using PETG and interchangeable modules (foot, ankle unit, pylon adapter). Finite-element analyses of heel-strike, mid-stance, and toe-off load cases, supported by bench checks, show strain localization in intended flexural regions, a minimum safety factor of 15 for the housing, and peak-stress reduction after geometric refinements (increased transition radii and local ribs). The modular layout simplifies servicing and allows quick tuning of stiffness and damping without redesigning the load-bearing structure. The results indicate an engineeringly realistic path toward accessible prosthetics and provide a basis for subsequent upgrades toward semi-active control and sensor-assisted damping. Full article

Background: Plantar fasciitis is a prevalent musculoskeletal disease characterized by heel pain and functional impairment. Both high-intensity laser therapy (HILT) and extracorporeal shockwave therapy (ESWT) have demonstrated efficacy in managing plantar fasciitis; however, their relative effectiveness remains unclear. Purpose: This systematic review and meta-analysis aimed to compare the effects of HILT and ESWT for treating plantar fasciitis. Methods: A comprehensive literature search of PubMed, the Cochrane Library, EMBASE, and Scopus was conducted from inception to 13 July 2025 to identify randomized controlled trials (RCTs) investigating both interventions. Two reviewers independently extracted data and assessed the methodological quality of the trials using the Physiotherapy Evidence Database (PEDro) scale. The certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. The primary outcomes of this study were pain intensity and foot function. The visual analog scale (VAS) was used for pain assessment. Foot function was evaluated by the total scores of the Foot Function Index (FFI) and American Orthopedic Foot & Ankle Society Scale (AOFAS) and the activities of daily living (ADL) subscale scores of the Foot and Ankle Ability Measure (FAAM). Outcomes were assessed at the end of treatment and during short-, medium-, and long-term follow-ups. The meta-analysis utilized standardized mean differences (SMDs), assessed heterogeneity using the I² test, applied the inverse variance method for pooling continuous variables, and employed a random-effects model because of the variable study methods used across the included articles. Results with p < 0.05 were considered statistically significant. The I² test was used to objectively measure statistical heterogeneity, with I² ≥ 50% indicating significant heterogeneity. Results: Five RCTs met the inclusion criteria, with methodological quality scores ranging from 6 to 7 on the 10-point PEDro scale. In total, 120 participants received HILT and 116 received ESWT. Regarding pain intensity (VAS), no statistically significant differences were detected between HILT and ESWT at any time point, including short-term morning pain (SMD = −0.11, 95% CI −0.42 to 0.19, p = 0.40), resting pain (SMD = 0.01, 95% CI −0.48 to 0.49, p = 0.05), and activity pain (SMD = −0.08, 95% CI −0.41 to 0.26, p = 0.89), as well as medium-term morning, resting, and activity pain (all p > 0.05). For foot function (FFI), the pooled analysis of all studies showed no significant short-term difference (SMD = 0.37, 95% CI −0.22 to 0.95, p = 0.01; I² = 73%); however, a subsequent sensitivity analysis, which excluded one studyreduced heterogeneity to 0% and revealed a significant short-term advantage of ESWT (SMD = 0.64, 95% CI 0.32 to 0.95, p < 0.01). Medium-term FFI also favored ESWT (SMD = 0.53, 95% CI 0.14 to 0.92, p < 0.01). Overall, the certainty of evidence ranged from moderate to low, mainly due to risk of bias and heterogeneity, as assessed by the GRADE approach. Conclusions: While the pooled results suggested a trend toward greater functional improvement with ESWT than with HILT in the short- and medium-term, the effect sizes were small. No significant between-group differences were observed in pain-related outcomes. Given the limited number of available trials and variability in treatment protocols, current evidence remains insufficient to draw definitive conclusions about the comparative efficacy of ESWT and HILT. Further high-quality, large-scale randomized controlled trials with standardized methodologies are needed to better inform clinical decision-making. Full article

Cardiovascular disease (CVD) remains the leading cause of death worldwide, accounting for nearly one-third of global mortality. Arterial stiffening, particularly in the central elastic arteries, impairs the Windkessel (cushioning and pumping) function and contributes to cardiovascular risk beyond traditional factors. Carotid–femoral pulse wave velocity (cfPWV) is established as the gold standard for assessing aortic stiffness and predicting cardiovascular and all-cause mortality; however, its technical complexity and requirement for trained personnel limit its use in routine clinical and community settings. These challenges have driven the development of simplified techniques for population screening, such as brachial–ankle PWV (baPWV). More recently, single-cuff oscillometric devices have emerged as practical alternatives. These methods are simple enough to be implemented in daily healthcare at home, thereby greatly enhancing accessibility, although their accuracy depends on model assumptions and calibration. In this perspective article, we highlight the pathophysiological significance of preserving the central arterial Windkessel function and emphasize the need for its practical assessment. Recent innovations mark a paradigm shift from complex laboratory-based measurements toward simplified, data-driven, and socially feasible screening tools for the early detection and prevention of CVD. Full article

Background/Objectives: Combat trauma involving large joints is associated with a high risk of thromboinflammatory complications. Early identification of laboratory markers for hypercoagulability is essential to optimise perioperative management. This study aimed to evaluate the dynamics of inflammation and haemostasis indicators in patients with combat-related joint trauma and to identify the most informative markers for preoperative risk assessment. Methods: A total of 29 patients with combat injuries to the hip, knee, elbow, or ankle joints were examined. Blood samples were taken 1–3 days prior to surgery and again on the first postoperative day. Parameters of coagulation (e.g., PT, INR, fibrinogen, D-dimer, soluble fibrin complexes, antithrombin III), fibrinolysis, and inflammation (e.g., CRP, haptoglobin, sialic acid, ESR, LSI, LII) were analysed and compared to those of 30 healthy controls. Statistical analysis included Student’s t-test and Pearson’s correlation. Results: At baseline, patients demonstrated significant increases in inflammatory markers (CRP 64.2 ± 7.3 mg/L, ↑738.9%; haptoglobin 3.25 ± 0.4 g/L, ↑164.3%; ESR 46.8 ± 5.2 mm/h, ↑313.8%) and procoagulant activity (D-dimer 1.42 ± 0.18 µg/mL, ↑136.6%; fibrinogen 6.12 ± 0.51 g/L, ↑102.4%; soluble fibrin complexes 38.7 ± 4.9 mg/L, ↑597.3%), together with a reduction in antithrombin III activity (63.5 ± 6.2%, ↓39.5%) and prolonged fibrinolysis time (increase by 197%). Postoperatively, these abnormalities intensified, indicating a sustained thromboinflammatory response. Strong correlations were found between inflammatory and haemostatic markers. Conclusions: Combat trauma of large joints is associated with preoperative thromboinflammatory dysregulation, which is exacerbated by surgery. Monitoring specific biochemical and haematological markers—such as CRP, fibrinogen, D-dimer, and soluble fibrin complexes—may support preoperative risk assessment and postoperative monitoring strategies for hypercoagulable states in this high-risk group. These findings lay the groundwork for future prospective studies aimed at developing stratified therapeutic protocols and predictive models for thromboinflammatory complications in orthopaedic trauma care. Full article

This study presents the clinical trial readiness and optimization of a parallel robotic system developed for early-stage lower limb rehabilitation of bedridden patients using feedback from healthy users and clinicians. The system combines a parallel hip–knee mechanism with a Bowden cable-driven ankle module, both actuated by servomotors and controlled through a PLC platform. Experimental tests were performed in laboratory conditions with twenty healthy participants (aged 25–45) and ten clinicians, focusing on safety, ergonomics, clinical usability, and comfort through structured questionnaires. The responses were quantified and analyzed using a Mamdani-type fuzzy logic model, allowing subjective feedback to be converted into objective redesign priorities. Safety, torque capacity, and adaptability emerged as the key areas that need improvement. Subsequent mechanical and structural refinements resulted in substantial gains in user comfort, perceived safety, and clinician-reported applicability. The optimized robotic system demonstrates enhanced functionality and improved readiness for clinical evaluation, highlighting the benefit of incorporating fuzzy logic-based feedback into the development of rehabilitation robots. Full article

Background: Ankle sprains are one of the most frequent ligament injuries in elite sports. Despite their high incidence, current rehabilitation approaches are often based on time-based criteria and neglect the physiological status of the injured tissues. Infrared thermography (IRT) is a non-invasive tool useful for detecting temperature asymmetries related to inflammation and tissue dysfunction. This study aimed to analyze the temporal evolution of ankle temperature asymmetry during return-to-play (RTP). Methods: A retrospective observational study of 26 ankle injuries analyzed with thermography that met the inclusion criteria. Thermograms were processed with a software to calculate temperature asymmetry in the ankle region of interest (ankleROI). Statistical analyses included paired and one-sample t-tests, as well as linear regression models, to assess temporal changes throughout the RTP process. Results: A significant hyperthermic response was observed immediately after injury (Δ = +0.594 °C; p < 0.001, Cohen’s d = 0.918). The first significant asymmetry reduction occurred between 21.5 and 28.5 days post-injury (Δ = −0.488 °C; p = 0.004), with a consistent weekly decrease of −0.109 °C (95% CI [−0.143, −0.078]). These findings indicate a progressive decrease in decrement on thermal asymmetry over approximately four weeks of RTP. Conclusions: IRT demonstrates potential as a physiological monitoring tool during the RTP process after ankle sprains. The observed pattern of temperature recovery provides objective reference thresholds that could complement existing functional and clinical criteria. Full article

Objective: A modeling and simulation tool, OpenSim, was used to determine the optimal relationship between actuator stiffness and actuation timing of a passive ankle exoskeleton for reducing metabolic costs during walking. We hypothesized that the absolute minimum in total metabolic cost would exist at an actuation timing of 15% of stance and at a spring stiffness of 7.5 kN/m. We also hypothesized that a local minimum in total metabolic cost would exist at an actuation timing of 50% of stance. Methods: Bilateral kinematics and kinetics data were collected on a healthy male walking overground wearing his regular tennis shoe. The passive ankle exoskeleton geometry and the spring actuator were integrated into the OpenSim model. Simulations were performed for every combination of 25 spring stiffnesses ranging from 5.5 kN/m to 17.5 kN/m (increments of 0.5 kN/m) and 10 actuation timings ranging from 15% to 60% of stance (increments of 5%). Total energy expenditure was calculated as the sum of the energy expenditure of all the muscles in the model. Results: The greatest reduction in energy consumption (−2.67%) was observed at an actuation timing of approximately 15% of the stance phase with a spring stiffness of ~5.5 kN/m. A quadratic relationship between spring stiffness and energy consumption was identified (R² = 0.99), with an optimal stiffness of approximately 5.5 kN/m minimizing the energy cost. Conclusions: Our findings suggest that OpenSim effectively predicts optimal exoskeleton parameters, supporting personalized assistance to improve energy efficiency and rehabilitation outcomes. Full article

In response to the personalized and precise rehabilitation needs for motor injuries and stroke associated with population aging, this study proposes a design method for an intelligent rehabilitation trainer that integrates Bayesian information gain (BIG) and axis matching techniques. Grounded in the biomechanical characteristics of the human ankle joint, the design fully draws upon biomimetic principles, constructing a 3-PUU-R hybrid serial–parallel bionic mechanism. By mimicking the dynamic variation of the ankle’s instantaneous motion axis and its balance between stiffness and compliance, a three-dimensional digital model was developed, and multi-posture human factor simulations were conducted, thereby achieving a rehabilitation process more consistent with natural human movement patterns. Natural randomized disability grade experimental data were collected for 100 people to verify the validity of the design results. On this basis, a Bayesian information gain framework was established by quantifying the reduction of uncertainty in rehabilitation outcomes through characteristic parameters, enabling the dynamic optimization of training strategies for personalized and precise ankle rehabilitation. The rehabilitation process was modeled as a problem of uncertainty quantification and information gain optimization. Prior distributions were constructed using surface EMG (electromyography) signals and motion trajectory errors, and mutual information was used to drive the dynamic adjustment of training strategies, ultimately forming a closed-loop control architecture of “demand perception–strategy optimization–execution adaptation.” This innovative integration of probabilistic modeling and cross-joint bionic design overcomes the limitations of single-joint rehabilitation and provides a new paradigm for the development of intelligent rehabilitation devices. The deep integration mechanism-based dynamic axis matching and Bayesian information gain holds significant theoretical value and engineering application prospects for enhancing the effectiveness of neural plasticity training. Full article

Human mobility is commonly assessed in the laboratory environment, but accurate and robust joint motion measurement and task classification in the home setting are rarely undertaken. This study aimed to develop a digital twin model of a home to measure, visualize, and classify joint motion during activities of daily living. A fully furnished single-bedroom apartment was digitally reconstructed using 3D photogrammetry. Ten healthy adults performed 19 activities of daily living over a 2 h period throughout the apartment. Each participant’s upper and lower limb joint motion was measured using inertial measurement units, and body spatial location was measured using an ultra-wide band sensor, registered to the digital home model. Supervised machine learning classified tasks with a mean 82.3% accuracy. Hair combing involved the highest range of shoulder elevation (124.2 ± 21.2°), while sit-to-stand exhibited both the largest hip flexion (75.7 ± 10.3°) and knee flexion (91.8 ± 8.6°). Joint motion varied from room to room, even for a given task. For example, subjects walked fastest in the living room (1.0 ± 0.2 m/s) and slowest in the bathroom (0.78 ± 0.10 m/s), while the mean maximum ankle dorsiflexion in the living room was significantly higher than that in the bathroom (mean difference: 4.9°, p = 0.002, Cohen’s d = 1.25). This study highlights the dependency of both upper and lower limb joint motion during activities of daily living on the internal home environment. The digital twin modeling framework reported may be useful in planning home-based rehabilitation, remote monitoring, and for interior design and ergonomics. Full article

Background/Objectives: While strength training interventions improve walking performance in stroke survivors, the underlying neuromuscular mechanisms remain poorly understood. This study investigated muscle-level adaptations following a 12-week moderate-to-high-intensity strength training program in ten chronic stroke survivors using comprehensive musculoskeletal modeling analysis. Methods: Three-dimensional gait analysis was performed pre- and post-intervention, with subject-specific OpenSim models estimating individual muscle forces, powers, and work capacities throughout stance phase. Results: Non-paretic hip flexor negative work capacity increased significantly (0.033 to 0.042 J/kg, p = 0.033, Cohen’s d = 0.47), driven by enhanced rectus femoris power absorption during late stance that mechanistically facilitated trunk acceleration through leg deceleration. Knee extensor force generation showed increasing trends during loading response in both limbs. During push-off, ankle plantar flexor force generation showed trends toward bilateral improvements, primarily through paretic soleus and gastrocnemius contributions, though power output remained unchanged, indicating persistent velocity-dependent muscular deficits. Conclusions: Improved gait performance in both limbs demonstrates that strength training produces functionally beneficial bilateral muscle-level reorganization. The absence of a control group limits causal inference, though the observed biomechanical adaptations align with functional improvements, supporting the integration of strength training into comprehensive stroke rehabilitation protocols targeting locomotor recovery. Full article

Powered ankle exoskeletons have become efficient ability-enhancing and rehabilitation tools that support human body movements. Traditionally, the control schemes for ankle exoskeletons were implemented relying on precise physical and kinematic models. However, this approach resulted in poor coordination of human–machine coupled motion and an increase in the wearer’s energy consumption. To solve the cooperative control issue between the wearer and the ankle exoskeleton, this work introduces an adaptive impedance control method for the ankle exoskeleton that is based on the surface electromyography (sEMG) of the calf muscles. The proposed method achieves cooperative control by leveraging an experience-based fuzzy rule interpolation (E-FRI) approach to dynamically adjust the impedance model parameters. This adaptive mechanism is driven by the wearer’s calf sEMG signals, which capture the wearer’s movement state. The adaptive impedance model then computes the desired torque for the ankle exoskeleton. To validate and evaluate the system, the control method was implemented on a simplified ankle exoskeleton. Experimental validation with five healthy participants (age 19 ± 1.35 years) demonstrated significant improvements over conventional fixed-impedance approaches: mean RMS reductions of 19.7% in gastrocnemius activation and 21.4% in soleus activation during treadmill walking. This study establish a new paradigm for responsive exoskeleton control through symbiotic integration of neuromuscular signals and adaptive fuzzy inference, offering critical implications for rehabilitation robotics and assistive mobility technologies. Full article

Wearables enable objective measurement of physical activity (PA) and sleep. Studies that have examined PA and sleep in children with Down syndrome (DS) have not been systematically reviewed. The objectives of this systematic review (PROSPERO: CRD420251036478) were to: (1) describe patterns of PA and sleep in children with DS; (2) compare PA and sleep between DS and non-DS; and (3) evaluate sensor data collection procedures. Searches were conducted in PubMed, Scopus, Web of Science, Embase, and SPORTDiscus, with the last search on 7 October 2025. Risk of bias was assessed with the Joanna Briggs Institute tools. From 203 records, 9 original studies were included. Children with DS (n = 8–66 participants; 1–67 months) showed small changes in movement rates over time and greater upper- than lower-limb movements. Segment-specific counts and time spent on high-intensity activity were lower in DS than non-DS. Overall, children with DS exhibited poor sleep quality, sleeping approximately one hour less than controls and 3–7 h below global recommendations. Sensor data collection protocols varied in epoch length (15–30 s), attachment site (wrist, ankle, and hip), and device model. Population-based research employing standardized sensor procedures is warranted to better establish PA levels and sleep quality in children with DS. Full article

Background/Objectives: Cardiovascular diseases remain the leading cause of death among women, with peripheral arterial disease (PAD) representing an important manifestation of systemic atherosclerosis. The ankle–brachial index (ABI) is a simple, non-invasive measure used for PAD screening and cardiovascular risk assessment. This study aimed to compare ABI values between women of reproductive and postmenopausal age and to explore associations with lifestyle and clinical characteristics in primary care settings. Methods: This cross-sectional study included 437 women recruited from family medicine offices in two Croatian counties between November and December 2024. Participants completed validated questionnaires on dietary habits (MEDAS) and physical activity (IPAQ/PASE), and underwent anthropometric and blood pressure measurements. ABI was assessed using an automated MESI device following a standardized protocol. Multivariable logistic regression was performed to identify independent predictors of abnormal ABI (<1.00), adjusting for age, BMI, hypertension, smoking, and county. Results: Most participants had normal ABI values (right 95.7%; left 95.0%). Mild to moderate PAD (ABI 0.90–0.99) was observed in approximately 3% and severe PAD (ABI < 0.90) in ≤1.1% of cases. Postmenopausal women were more likely to present with lower ABI values (p = 0.046), though this association was attenuated after adjusting for age. Lifestyle factors, including diet and physical activity, showed no significant association with ABI in the adjusted models. Conclusions: Age emerged as the primary determinant of reduced ABI, while hypertension and smoking showed positive but non-significant associations. The findings underscore the importance of early vascular screening and lifestyle-based prevention in women, particularly in the postmenopausal period. Larger longitudinal studies are warranted to clarify causal pathways and the role of hormonal and behavioral factors in peripheral arterial disease development. Full article

Freezing of gait (FoG) is a common motor symptom in advanced Parkinson’s disease, leading to falls, disability, and reduced quality of life. Although cueing systems using visual or auditory stimuli can help patients resume walking, existing solutions are often expensive, uncomfortable, and conspicuous. ParCuR (Parkinson Cueing and Rehabilitation) is a compact, ankle-worn wearable integrating an inertial sensor, haptic stimulator, and AI-based software. It was developed to detect FoG episodes in real time and provides automatic sensory cues to assist patients with Parkinson’s Disease (PwP). A classifier was trained for FoG detection using the DAPHNet dataset, comparing patient-specific and patient-independent models. While a small-scale trial with PwP assessed usability and reliability. ParCuR is watch-sized (35 × 41 mm), discreet, and comfortable for daily use. The online detection algorithm triggers stimulation within 0.7 s of episode onset and achieves 94.9% sensitivity and 91.3% specificity using only 14 frequency-based features. Preliminary trials confirmed device feasibility and guided design refinements. This low-cost, wearable solution supports personalized, real-time FoG detection and responsive cueing, improving patient mobility while minimizing discomfort and continuous stimulation habituation. Full article

Background/Objectives: Outcomes following Anterior Cruciate Ligament (ACL) reconstruction vary widely among patients, yet existing classification techniques often lack transparency and clinical interpretability. To address this gap, we developed a multi-modal framework that integrates gait dynamics with patient-specific characteristics to enhance personalized assessment of ACL reconstruction outcomes. Methods: Participants, both post-ACL reconstruction and healthy controls, were equipped with inertial measurement unit (IMU) sensors on bilateral wrists, ankles, and the sacrum during standardized locomotion tasks. Using the Phase Slope Index (PSI), we quantified causal relationships between sensor pairs, hypothesizing that (1) PSI-derived metrics capture discriminative biomechanical interactions; (2) task-specific differences in segment coordination patterns influence model performance; and (3) recovery duration modulates classifier confidence and the structure of high-dimensional data distributions. Classification models were trained using PSI features, and permutation-based sensor importance analyses were conducted to interpret task-specific biomechanical contributions. Results: PSI-based classifiers achieved 96.37% accuracy in distinguishing ACL reconstruction outcomes, validating the first hypothesis. Permutation importance revealed that jogging tasks produced more focused importance distributions across fewer sensor pairs while improving accuracy, confirming task-specific coordination effects (hypothesis two). Visualization via t-SNE demonstrated that longer recovery durations corresponded to reduced model confidence but more coherent feature clusters, supporting the third hypothesis. Conclusions: By integrating causal gait metrics and patient recovery profiles, this approach enables interpretable and high-performing ACL outcome prediction. Quantitative evaluation measures—including model confidence and t-SNE cluster coherence—offer clinicians objective tools for personalized rehabilitation monitoring and data-driven return-to-sport decisions. Full article