Search Results (1,932)

The deployment of Convolutional Neural Networks (CNNs) on entry-level Edge FPGAs is severely constrained by the scarcity of Digital Signal Processing (DSP) blocks, a phenomenon termed the “DSP Wall”. To circumvent this bottleneck, this paper presents AEMAC, a Software–Hardware Co-Designed accelerator architecture that decouples arithmetic computation from DSP availability. The proposed methodology synergizes a software-level Dynamic Integer Scaling strategy with a hardware-level Adaptive Error-Compensated Multiply-Accumulate unit. By mapping floating-point activations to an optimal integer domain and employing a DSP-free, LUT-based tri-mode datapath, the architecture achieves extreme resource efficiency. To mitigate the precision loss inherent in logic-based truncation, a statistical bias compensation mechanism is integrated into the accumulator chain. Experimental validation on a Xilinx Zynq-7020 FPGA demonstrates a strictly zero-DSP implementation with minimal logic utilization (100 LUTs). Post-implementation timing simulations confirm a dynamic power of 0.490 W for a 64-core cluster under worst-case random workloads, yielding a verified energy efficiency of 26.1 GOPS/W. Micro-level analysis confirms a 16.7% reduction in arithmetic Mean Absolute Error (MAE) compared to naive truncation. Furthermore, macro-level evaluation on the CIFAR-10 dataset reveals that the co-design strategy recovers system accuracy to 64.74%, outperforming the uncompensated baseline by 0.55% and achieving statistical comparability to floating-point baselines. To ensure absolute internal consistency, all hardware metrics are strictly validated via SAIF-based post-implementation simulations. Based on a conservative full-chip projection that incorporates a routing derating model, these internally consistent results establish AEMAC as a highly scalable and reliable solution for breaking the DSP wall in resource-constrained edge intelligence. Full article

Satellite-based precipitation estimates (SPE) provide essential spatial coverage and near real-time availability for hydrological applications but often exhibit systematic biases in regions characterized by complex terrain and strong climatic variability, limiting their reliability for flood-related studies. To address these limitations, this study proposes an Adaptive Regularization framework integrated within a Long Short-Term Memory (LSTM) model to enhance satellite–gauge rainfall fusion beyond conventional optimization strategies. The framework dynamically adjusts learning rate and weight decay during training based on validation performance and overfitting indicators, improving training stability, data efficiency, and model generalization across diverse precipitation regimes. The proposed approach was applied to refine Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG-Final) daily rainfall estimates over the flood-prone east coast of Peninsular Malaysia. Model performance was assessed against ten optimization algorithms using correlation coefficient (CC), mean absolute error (MAE), normalized root mean squared error (NRMSE), percentage bias (PBias), and Kling–Gupta efficiency (KGE). Results show that the Adaptive Regularization framework consistently outperforms all benchmark optimizers, achieving an MAE of 6.87, CC of 0.68, NRMSE of 1.84, and KGE of 0.56. Overall, the proposed framework enhances spatial consistency and robustness across monsoon seasons, offering a scalable solution for improving SPE in flood-prone regions. Full article

Cardiac point-of-care ultrasound (cPOCUS) is used to obtain key information about the heart’s structure and function when an echocardiogram is not available. This prospective, cross-sectional study aimed to compare fractional shortening (FS%) and left-atrium-to-aorta ratio (LA:Ao) obtained by cPOCUS in different body positions to echocardiography. Thirty-nine dogs had cPOCUS performed in three different body positions: left lateral recumbency (RT), right lateral recumbency (LT), and standing or sternal recumbency (RST). The cPOCUS values from each body position for FS% and LA:Ao were tested for agreement with the echocardiogram by Bland-Altman plots, correct clinical assessment by generalized estimated equation models, and quality score of the cPOCUS images as a percentage. Bland-Altman analysis showed a positive bias for FS% (0.9% to 9.8%) and both positive and negative bias for LA:Ao (within 0.2) for the cPOCUS values. The correct clinical assessment was made in the majority of cases for FS% in RST (67%) and RT (67%), and for LA:Ao in RST (55%). The clinical assessment was more often correct when the image quality score was higher. Intraclass correlation showed good agreement (≥0.61) between investigators for FS% in all body positions and LA:Ao in RT and RST. This study showed that cPOCUS performed from the right hemithorax can provide estimates and correct clinical assessment of FS% and LA:Ao. Obtaining measurements in the LT position is not recommended. Full article

The critical brain hypothesis proposes that neural systems operate near a phase transition to optimize information processing. A key method for investigating this hypothesis is the phenomenological renormalization group (pRG), which looks for scale-invariant features across levels of coarse-graining. One such feature is the power-law scaling of eigenvalues of covariance matrices of coarse-grained variables. However, the estimation of this scaling exponent, $\mu$, often relies on linear regression over arbitrarily selected ranges of the plot of eigenvalues versus rank. This heuristic “eyeballing” introduces uncontrolled bias and complicates the interpretation of observed scaling relationships. In order to obtain a more robust estimation of $\mu$, we do not fit the standard eigenvalue-vs-rank relationship, but rather the density of eigenvalues, for which standard protocols exist for fitting power laws to empirical data distributions. We demonstrate this approach using a synthetic model that replicates the scaling signatures of neural data while providing control over the system’s exponents as well as neural data obtained from publicly available Neuropixels recordings. We also establish standards for the minimal data required to quantify power-law behavior in a pRG eigenvalue analysis. Our approach contributes a tool for understanding the fundamental limitations imposed by spatial and temporal constraints of experimental datasets, which is required to rigorously assess the neural criticality hypothesis. Full article

Background: Carpal tunnel syndrome (CTS) is one of the most common entrapment neuropathies. While surgical decompression is widely considered the definitive treatment, conservative options remain clinically relevant, particularly for symptom relief and functional recovery in the short term. Objectives: To update the evidence comparing surgical versus non-surgical interventions for CTS, assessing pain, function, and clinical recovery. Design: Systematic review of randomised controlled trials (RCTs). Data Sources and Methods: Six databases (CENTRAL, MEDLINE, Embase, Cochrane Neuromuscular Register, ClinicalTrials.gov, and WHO ICTRP) were searched for RCTs published between November 2022 and January 2025. Risk of bias was assessed with RoB 2.0 and certainty of evidence with GRADE. Due to clinical heterogeneity, a narrative synthesis was performed. Results: Four RCTs (n = 1158) were included. Corticosteroid injection and percutaneous electrical nerve stimulation (PENS) appeared to provide faster symptom relief than surgery at short-term follow-up. However, surgery was associated with a higher probability of sustained recovery at 12–18 months (RR 1.36; 95% CI 1.19–1.56). Evidence for PENS was limited to one female-only trial, which restricts generalisability. Certainty of evidence was moderate for long-term outcomes and low for short-term results and safety. Conclusions: The available evidence suggests that surgery may offer more durable long-term recovery, whereas corticosteroids and PENS may be useful for short-term symptom relief. These findings should be interpreted with caution given the limited number of trials and the risk of bias in most included studies. Treatment choice should align with patient goals and recovery timelines. Registration: PROSPERO (CRD420250650789). Full article

This study presents a pilot methodological investigation of the thermal performance of a Najdi mudbrick dwelling in Ushaiger, Saudi Arabia, using short-term field monitoring and a preliminary digital-twin inspired workflow. Two field campaigns in August and September 2025 measured indoor and outdoor conditions with a portable weather station under severe site constraints, including lack of electrical infrastructure, restricted access, and the use of consumer-grade sensors. The monitored results indicate that the massive earthen walls attenuated part of the outdoor daily temperature swing, but indoor conditions remained very hot: in August, indoor temperatures averaged 38.1 °C, compared with 40.2 °C outdoors, and in September, indoor temperatures averaged 36.3 °C, compared with 36.1 °C outdoors. A simplified IDA ICE model was compared with the monitored indoor temperature over the available windows, and a post-processing affine bias adjustment was tested only as a diagnostic short-window correction rather than as a transferable calibration. Monte Carlo sensitivity analysis was used in an exploratory way. It examined how passive envelope and boundary-related parameters influenced simulated indoor relative humidity, with infiltration emerging as the dominant factor affecting relative humidity dynamics; peak indoor relative humidity increased from about 67% at 0.15 air changes per hour (ACH) to more than 74% at 0.60 ACH, whereas wall thickness had a modest buffering effect. Given the short monitoring duration and field limitations, the study is not presented as a fully validated digital twin but as a feasibility-oriented workflow that combines constrained in situ monitoring with exploratory simulation to support future, longer-term conservation and adaptive reuse research on earthen heritage in hot–arid climates. Full article

Infant respiration is a physiological marker of health and wellbeing that can provide insight into sleep and wake patterns. Technological innovation presents opportunities to enhance measurements of physiological signals, which improves ecological validity and participant experiences. This is particularly true in the context of studying infant sleep, as it can be disrupted by changes in the environment and the physical sensation of unfamiliar or uncomfortable sensors. The goal of this study was to examine if a commercially available video baby monitor (Nanit system) can accurately estimate respiration during a nap relative to a commonly used cardiorespiratory sensor (Isansys Lifetouch sensor). Thirty-three infants (M = 9.7 months; range = 1–22 months) took a nap while wearing the Lifetouch sensor and Nanit Breathing Band. Infants slept in view of the Nanit camera. A computer vision algorithm applied to the video detected movement of the patterns on the fabric band worn around the infant’s torso to determine respiratory rates. The results showed strong consistency between the devices. More than 95% of the minute-by-minute respiration data fell within the limits of agreement, with little bias. Agreement was not influenced by age or nap duration, suggesting the Nanit Breathing Band provides a valid measure of respiration across infancy. Full article

Background: Cardiovascular diseases are the main cause of mortality and morbidity in Portugal, with coronary artery bypass grafting (CABG) being one of the most performed surgeries in cardiothoracic centers. After cardiac surgery, patients often experience a decrease in physical capacity, which results in an increased risk of mortality or hospitalization expenditures. The objective of this systematic review was to characterize changes in respiratory function in patients undergoing CABG. Methods: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Web of Science, Pubmed, SCOPUS, and Sport Discus were searched using a predefined research strategy to identify relevant original studies published until August 2025. To be included, studies must have assessed adult patients submitted to CABG who evaluated the respiratory function before and after cardiac surgery. Studies that reported other types of cardiac surgery were excluded. The Risk of Bias in Non-randomized Studies-of-Exposure and the Cochrane risk-of-bias tool for randomized trials were used to analyze the risk of bias of the selected studies. Results: After screening 1184 potential articles, six studies met the inclusion criteria. The studies included participants who underwent CABG (n = 324), with a mean age ranging from 54.05 ± 13.6 to 67 ± 10 years. Conclusions: All included studies reported significant postoperative reductions in respiratory function following CABG, including forced vital capacity, forced expiratory volume in one second, maximal inspiratory pressure, and maximal expiratory pressure. Although these findings consistently indicate a decline in pulmonary function, the limited number of available studies limits the strength of the conclusions. This systematic review suggests that monitoring respiratory impairments after CABG may be clinically relevant to improve health-related quality of life. Full article

The assessment of risk of bias in systematic reviews and meta-analyses is crucial, as it indicates the accuracy of the synthesized and evaluated data and the validity of the presented results and conclusions. Until now, standardized tools for this purpose have been available only for clinical and animal studies, while adapted forms of these tools and novel ones have been proposed for in vitro and laboratory studies. However, none of them have been universally standardized so far. The apparent lack of a risk of bias assessment tool for systematic reviews of in vitro antimicrobial susceptibility testing studies constitutes a methodological flaw in these studies. To this end, we developed a risk of bias assessment tool for in vitro antimicrobial susceptibility testing studies. Our tool assesses the risk of bias across six domains: methodological bias, selection bias, preparation bias (including contamination/cross-contamination bias), measurement/observer bias, reporting and publication bias, and bias related to unreported funding and conflicts of interest. The tool evaluates a total of 16 specific criteria. The risk of bias is graded as low, moderate, or high for each evaluated criterion. The proposed risk of bias assessment tool was tested in a pilot validation study of ten relevant studies by two reviewers independently. We believe that the use of the proposed risk of bias assessment tool will increase the methodological strength of systematic reviews and meta-analyses of in vitro antimicrobial susceptibility testing studies. Full article

Pinus caribaea M. comprises three varieties: hondurensis, bahamensis and caribaea, the latter being crucial to the Cuban forestry industry. This systematic review evaluated some physical–mechanical properties and tracheid biometry of Pinus caribaea M. wood, with particular emphasis on var. caribaea, to identify potential knowledge gaps and followed the PRISMA 2020 guidelines. The investigation was conducted in four databases, including gray literature up to December 2024, and the risk of bias was assessed using a tool adapted from the JBI critical appraisal checklist. A total of 535 studies were identified, of which 75 were included in the review based on the inclusion criteria. It was found that only 17.3% of the selected publications focus on var. caribaea. Most studies evaluate physical properties, with less attention paid to mechanical properties and cell biometry. A downward trend in recent publications was noted for this variety, along with a predominance of the radial direction as a source of variation. A lack of research on mature trees (>30 years) as well as other sources of variation were identified as information gaps. Value ranges for density, shrinkage, modulus of elasticity and modulus of rupture in static bending, compressive strength parallel to the grain, as well as tracheid biometry were synthesized from the available publications for all varieties. It is concluded that var. caribaea is under-researched, and a systematic study is therefore required to optimize its use and industrial impact. Full article

Background/Objectives: Ultrasound shear-wave elastography (SWE) enables quantitative assessment of tissue stiffness and may provide a non-invasive biomarker of carotid plaque vulnerability. This study aimed to evaluate the ability of SWE to differentiate symptomatic from asymptomatic carotid plaques and to assess its reproducibility. Methods: A systematic search of PubMed, Web of Science, EMBASE, and the Cochrane Library was conducted in the last ten years until January 2026 for publications evaluating carotid plaques using ultrasound SWE. Inclusion criteria required original publications that used quantitative ultrasound SWE parameters for the evaluation of carotid plaque in symptomatic and asymptomatic patients and/or investigated the reproducibility of SWE parameters for carotid plaques; non-carotid studies, non-original articles, and studies not comparing symptomatic versus asymptomatic plaques or not reporting reproducibility were excluded. Fourteen studies comprising 1781 carotid plaques were included. Quantitative SWE measurements were meta-analyzed using random effects. Differences between symptomatic and asymptomatic plaques were assessed using standardized mean differences (SMDs). The reproducibility of SWE measurements was evaluated using pooled correlation coefficients. Publication bias was evaluated using funnel plots and Egger’s regression test. Results: Ten studies including 1246 plaques compared SWE stiffness between symptomatic (n = 472) and asymptomatic plaques (n = 774). The meta-analysis demonstrated significantly lower stiffness values in symptomatic plaques compared with asymptomatic plaques (SMD −1.10, p < 0.001). Reproducibility analysis of correlation coefficients extracted from seven studies demonstrated excellent agreement for SWE measurements (r = 0.92, n = 602). Heterogeneity was observed across the included studies. No statistically significant evidence of publication bias was detected. Conclusions: Ultrasound SWE is a promising approach for assessing carotid plaque vulnerability, with lower SWE stiffness observed in symptomatic plaques compared to asymptomatic plaques. This finding should be interpreted with consideration of methodological heterogeneity and the cross-sectional nature of the available assessed evidence. Further prospective studies with standardized imaging protocols and longitudinal follow-up are needed to determine clinically applicable stiffness thresholds and evaluate the prognostic value of ultrasound SWE in cerebrovascular risk stratification. Full article

Background: Musculoskeletal pain affects an estimated 1.7 billion people worldwide and ranks among the leading causes of global disability. This review evaluates the effectiveness and safety of osteopathy in treating musculoskeletal pain across multiple body regions and conditions. Methods: A systematic literature review following PRISMA guidelines was conducted across five databases (Embase, Medline via Ovid, The Cochrane Library, PEDro, and INAHTA), yielding 964 citations. Eligible studies were RCTs published in English or German up to May 2022; conference abstracts were excluded. A hybrid design was employed: a systematic review of RCTs for neck, shoulder, knee, foot, osteoporosis, and fibromyalgia was combined with a pre-specified umbrella review component for chronic non-specific low back pain (registered in PROSPERO) to avoid duplication of an existing high-confidence evidence synthesis. From 35 critically appraised articles, the best available evidence (n = 15) was selected per body region based on a risk of bias (RoB) assessment (Cochrane Collaboration tool, version 1); the existing review was appraised with AMSTAR 2. An updated search (2022–July 2025) was performed without a RoB assessment. Data were synthesised qualitatively and reported narratively. Results: Fifteen RCTs and one systematic review were included, covering eight body regions and conditions (2408 participants). Pain improved immediately post-treatment in most regions; statistically significant between-group differences were less consistent at mid- and long-term follow-ups. Key findings: neck pain (n = four RCTs)—improvement in three of four studies immediately post-treatment; shoulder pain (n = two RCTs)—improvements across all follow-up points in one study; low back pain (n = one systematic review, 10 RCTs, 1160 participants)—pain reduced immediately and at mid-term follow-up; knee pain (n = two RCTs)—significant reduction in one study; foot pain (n = two RCTs)—improvement in both studies post-treatment and at mid-term follow-up; osteoporosis (n = one RCT)—no improvement immediately post-treatment; fibromyalgia (n = two RCTs)—significant between-group differences in one study post-treatment and at mid-term follow-up. Functional outcomes were heterogeneous across regions. Adverse events were minor and transient; no serious side effects were reported across any included study. The updated search (2022–July 2025) identified 12 additional RCTs across five regions, with findings broadly consistent with the primary analysis, though results for the neck region were marginally less favourable. Discussion: Based on current evidence, osteopathy can improve neck and low back pain for up to three months and may reduce shoulder and foot pain; evidence for other body regions remains inconclusive. RoB was unclear to high across studies, largely due to the inherent inability to blind patients and practitioners in manual therapy trials. Substantial heterogeneity in interventions, outcome measures, and study designs limits comparability. Overall certainty of evidence was low to moderate, warranting cautious interpretation. The consistent absence of serious adverse events across all included studies supports osteopathy as a safe therapeutic option. High-quality research with standardised interventions, rigorous designs, long-term follow-ups, and a focus on technique, dosage, and safety is needed to inform clinical practice and healthcare policy. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector. Full article

Existing research confirms associations between Big Five personality traits and emotional states, yet investigations into how personality traits modulate emotional dynamics and their gender-specific patterns remain limited. The present study developed a TFace-Bi-GRU-SE deep learning model that achieved a weighted accuracy of 63.50 ± 0.98% (peak single-run: 64.96%) and an F1 score of 65.21% in performance testing, with a single-inference time of 14.1 s, outperforming traditional methods. The model processed 10 min video recordings from 30 participants (19,262 observations), generating time-series data for valence (P) and arousal (A). Combined with Big Five personality assessments, continuous-time structural equation modeling (CTSEM) revealed distinct emotional dynamics: both P and A exhibited significant negative autoregression (−0.056 and −0.558, p < 0.001), with A reverting to baseline substantially faster (half-life: 1.2 s) than P (half-life: 12.3 s); cross-lagged effects were nonsignificant (P_A: 0.007; A_P: −0.026, p > 0.05). Arousal demonstrated greater instantaneous volatility (=0.339) than valence (=0.286, p < 0.001), with positive covariation between dimensions (0.218, p = 0.006). Exploratory analyses (N = 30) indicated that higher neuroticism and openness scores were associated with elevated arousal (Cohen’s d > 0.8), whereas higher agreeableness and conscientiousness scores were associated with elevated valence (d > 0.8). Gender moderated the neuroticism–arousal relationship, with more potent effects in females (r = 0.746, p = 0.008). Robustness analyses demonstrated high stability of core DRIFT parameters (P_P, A_A): bootstrap resampling (n = 50) yielded coefficients of variation < 0.35 with 100% directional consistency; subgroup validation confirmed cross-sample invariance. Sensitivity analyses revealed that an additional 8% measurement error induced less than 9% bias (8.3% for both P_P and A_A) in autoregressive parameters while preserving half-life ratios, confirming CTSEM’s capacity to extract reliable dynamics from moderately accurate AI outputs. Bootstrap and Bayesian analyses identified ten personality–DRIFT associations with directional consistency ≥ 70%; these constitute preliminary hypotheses for adequately powered future studies (N ≥ 61). This study provides methodological foundations for personalized affective intervention research. Data and code are publicly available (see Data Availability Statement). Full article

Background and Objectives: Coronavirus disease 2019 (COVID-19) is characterized by excessive inflammatory responses, including the so-called cytokine storm, which contributes substantially to morbidity and mortality in hospitalized patients. The vagus nerve, through the cholinergic anti-inflammatory pathway, represents a theoretically attractive therapeutic target for modulating systemic inflammation. Vagus nerve stimulation (VNS) has emerged as a potential adjunctive treatment for COVID-19, with several randomized controlled trials (RCTs) investigating its efficacy on inflammatory biomarkers and clinical outcomes. The quality of this evidence base has not been rigorously evaluated. This systematic review critically appraises all available RCT evidence for VNS in hospitalized COVID-19 patients. Materials and Methods: We systematically searched PubMed, Scopus, Cochrane (CENTRAL), and Web of Science from database inception to January 2026, for RCTs evaluating any form of VNS (invasive, non-invasive, cervical, or auricular) in hospitalized patients with confirmed acute COVID-19. Two reviewers independently screened titles, abstracts, and full texts according to pre-specified eligibility criteria. Risk of bias was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool, with assessments initially performed using multiple artificial intelligence tools and subsequently validated by the authors in accordance with PRISMA 2020 guidelines. Given substantial heterogeneity and high risk of bias, narrative synthesis was performed rather than meta-analysis. Also, GRADE assessment was performed. Results: From 437 records identified, six RCTs comprising 221 patients met the inclusion criteria. Five trials (83%) were rated as high risk of bias, primarily due to inadequate blinding, substantial baseline imbalances, significant missing data and extensive multiple testing without statistical correction. The single double-blind trial with a credible sham control (Rangon et al.) found null results across all outcomes, including clinical progression, ICU transfer, and mortality, while the five “high” risk-of-bias trials generally reported positive findings on various inflammatory markers and clinical outcomes. One trial (Corrêa et al.) measured heart rate variability as a direct indicator of vagal activation and found no change despite claiming anti-inflammatory effects, contradicting the proposed mechanism of action. Significant cognitive findings from an interim analysis (Uehara et al., n = 21) disappeared in the larger completed trial (Corrêa et al., n = 52), providing empirical demonstration of false positive findings in small, underpowered studies. Conclusions: Currently available evidence supporting the use of VNS for acute COVID-19 remains scarce; however, the physiological rationale remains sound, although the absence of reliable target engagement markers in the included studies limits confidence in this treatment method. Large-scale, double-blind, sham-controlled trials are required before VNS can be firmly recommended for COVID-19 management. Full article

Gait analysis study comparing unicompartmental vs. total knee arthroplasty, differences in knee kinematics: a retrospective cohort study. Background and Objectives: Total knee arthroplasty (TKA) is an effective treatment for advanced knee osteoarthritis, although functional outcomes may remain suboptimal in many patients. Unicompartmental knee arthroplasty (UKA) often provides better functional recovery but shows lower long-term implant survival. Recently, personalized TKA approaches have been developed to improve kinematic restoration and patient satisfaction. This study aimed to compare knee kinematics among patients who underwent personalized TKA, medial UKA, and healthy controls. Materials and Methods: This retrospective cohort study included 9 patients treated with robotic-assisted personalized TKA, 9 patients treated with medial UKA, and 9 healthy controls matched for age, sex, and BMI. Inclusion criteria were age 60–80 years, Kellgren–Lawrence grade III–IV, a minimum follow-up of 12 months, deviation from neutral HKA < 15°, healthy contralateral knee, and high postoperative functional scores. Exclusion criteria included valgus knees (HKA > 180°), postoperative complications, and neuromotor disorders. In the TKA group, a Medial Congruent implant was implanted with ROSA robotic assistance using a restricted kinematic alignment (±5° HKA) and asymmetric intercompartmental balancing. In the UKA group, a fixed-bearing medial implant (Physica ZUK) was used. Gait analysis was performed on a markerless instrumented treadmill (WalkerView™; Dalmine, Italy). Differences between groups were analyzed using one-way ANOVA and Tukey’s post-hoc test (p < 0.05). Results: UKA patients walked with a stiffer knee during stance. Knee range of motion during stance increased from UKA (6.3° ± 7.2°) to TKA (13.6° ± 8.8°, p = 0.045) and to controls (16.6° ± 4.5°, p = 0.02). During loading response, UKA patients showed lower flexion (10.2° ± 6.1°) than TKA (19.4° ± 7.9°, p = 0.049) and controls (19.6° ± 2.8°, p = 0.004). Knee flexion during swing was comparable between UKA and TKA. Conclusions: UKA patients demonstrated reduced knee flexion during early stance compared with robotic-assisted TKA and healthy controls. The observed differences may reflect multiple factors, including surgical technique, implant design, and patient-related characteristics. Because preoperative functional data were not available, potential selection bias cannot be excluded. These findings should be interpreted cautiously and warrant confirmation in larger prospective studies. Full article