Search Results (1,976)

Despite growing policy support for active travel, the fatality rate of vulnerable road users has remained persistently high in recent years, while the emergence of autonomous vehicles has further increased the complexity of mixed traffic environments. Interactions between cyclists and motorized vehicles are a major contributor to these fatalities, highlighting the urgent need for effective cyclist protection strategies. As one of the most widely adopted active transport modes, cycling safety cannot be assessed solely through crash statistics; understanding cyclists’ perceived safety is equally critical, as it reflects how infrastructure design and dynamic traffic conditions influence cycling behavior. In this study, we propose a cyclist safety perception framework that combines vision–language models with interpretable machine learning to analyze perceived safety in mixed traffic scenarios. A vision–language model is employed to generate semantic descriptions of traffic scenes, while an Explainable Boosting Machine quantifies both individual and interactive contributions of traffic-related features. By integrating visual information with road attributes extracted from OpenStreetMap, the proposed framework achieves a binary safety classification accuracy of 71% and a mean absolute error of 1.01 on a safety score scale ranging from 1 to 9. The results demonstrate the potential of combining multimodal perception and explainable models to support cyclist-centered safety assessment and inform sustainable and intelligent transportation system design. More specifically, the results show that protected cycling infrastructure is the most significant factor in improving perceived safety, whereas road construction has the opposite effect. Full article

Theswitched reluctance motor (SRM) suffers from torque ripple and speed fluctuations because of its doubly salient structure, magnetic saturation, and discrete commutation. To improve commutation performance and disturbance rejection, this paper proposes a progressive torque ripple suppression strategy. First, a multimodal magnetic co-energy model is developed to describe position-dependent saturation and generate the reference current through model inversion. Then, envelope extraction and frequency identification reveal the commutation-related periodic torque-error characteristic. Based on this feature, an angle-domain binned compensation method combining cycle averaging and linear interpolation is proposed to correct the reference current. A score-based finite-set PI hysteresis current controller is further designed to optimize magnetizing, freewheeling, and demagnetizing states, while a linear active disturbance rejection control (LADRC) speed loop improves load-disturbance rejection. Ablation studies verify the synergistic effect between angle-domain compensation and finite-set current execution. Robustness tests confirm low sensitivity to parameter variations, and theoretical analysis proves ultimate boundedness. Simulation results show that torque ripple is reduced to 2.00%, 2.03%, and 2.18% at 250, 500, and 1000 r/min, respectively. Under load-disturbance conditions, speed fluctuation is reduced by 59.92% and 57.20%, and all normalized parameter sensitivities remain below 0.35. Full article

Understanding the neural dynamics underlying expressive musical performance remains a major challenge at the intersection of neuroscience, music cognition, and computational modeling. While Electroencephalogram (EEG) studies of emotion have largely focused on passive exposure to affective stimuli, comparatively little research has examined oscillatory brain activity during active musical expression. The present single-subject study investigated whether band-limited EEG activity recorded during expressive piano performance by a professional concert pianist contains sufficient discriminative structure to support supervised multi-class classification of musically defined emotional categories. EEG was recorded from 128 scalp sites while a professional concert pianist performed emotionally characterized excerpts from Bach, Beethoven, and Chopin in a continuous naturalistic session. Musical excerpts had been previously categorized and perceptually validated according to emotional valence, tempo, energy/arousal, and tonal structure. From the continuous EEG recording, 180 non-overlapping 2 s artifact-free segments were extracted, yielding 30 segments for each emotional category. Mean spectral power was computed within theta (3.5–7.5 Hz), alpha (7.5–12.5 Hz), and high-beta (24–30 Hz) frequency bands across selected centro-parietal and posterior electrodes, resulting in 24 EEG-derived features per segment. Linear Support Vector Machine, Random Forest, and Gradient Boosting classifiers were evaluated using an 80/20 train-test split combined with five-fold cross-validation. EEG-only classification achieved above-chance performance across models, with Random Forest yielding the highest accuracy (0.42), macro F1-score (0.414), and Cohen’s κ (0.30), exceeding the theoretical chance level of 0.167. Feature importance analysis revealed distributed contributions across theta, alpha, and high-beta oscillatory activity, particularly over parietal and occipital regions, without evidence for a single dominant neural marker. Inclusion of an additional binary arousal-related feature substantially improved Random Forest performance (accuracy = 0.58; macro F1 = 0.579; κ = 0.50), indicating that arousal organization contributed strongly to category separability within the classification framework. These findings suggest that oscillatory EEG activity accompanying expressive musical action contains measurable statistical structure associated with emotionally differentiated performance states. Rather than identifying discrete neural correlates of emotion, the present results provide a computational characterization of distributed oscillatory dynamics emerging during expressive motor-acoustic interaction, extending affective EEG research beyond passive perception paradigms toward ecologically grounded musical performance contexts. Full article

Reliable condition monitoring of wind turbine gearboxes is critical to reducing unplanned downtime and maintenance costs in wind farms. However, this task presents significant challenges due to the non-stationary nature of vibration signals, in which fault-relevant features are sparsely and unevenly distributed across the time–frequency map. Although time–frequency analysis has been widely adopted to represent nonlinear and non-stationary vibration signals, existing deep learning methods typically process the full spectrogram directly, without distinguishing redundant or uninformative regions. This leads to high input dimensionality and exposes the model to substantial spectral noise. Consequently, it increases computational burden and potentially reduces the diagnostic reliability. To address this issue, this paper proposes a two-stage hybrid framework based on complementary selection mechanisms operating on two distinct feature spaces. In the first stage, eXtreme Gradient Boosting (XGBoost) importance scores are used to identify and permanently prune uninformative time–frequency features from the input spectrogram, reducing the input map size by 25%. In the second stage, a Squeeze-and-Excitation (SE) block, inserted after the deepest residual layer, performs soft channel-wise recalibration of the abstract feature maps produced by the residual convolutional neural network (ResCNN), thereby amplifying discriminative representations prior to classification. The proposed method was evaluated in an eight-class variable-speed fault classification task using the MCC5-THU benchmark, where data were collected from a 2.2 kW motor-driven gearbox test rig. The proposed method achieves a mean accuracy of 97.81% ± 0.33% under 5-fold stratified cross-validation (CV), while reducing classifier training time by approximately 23% compared to a baseline model trained on the full spectrogram. These results demonstrate that explicit input-level spectrogram pruning, combined with model-level channel attention, yields a robust and computationally efficient diagnostic framework for wind turbine gearbox condition monitoring. Full article

Background/Objectives: Following total knee arthroplasty (TKA), adductor canal block (ACB) is usually used for postoperative analgesia; however, the optimal injection level is yet unclear. This study tried to determine how the injection level of the ACB had an impact on postoperative analgesic efficacy and functional results after total knee arthroplasty. Methods: A total of 108 patients undergoing unilateral total knee arthroplasty under spinal anesthesia were included in this prospective observational study and were categorized according to the level of ultrasound-guided adductor canal block performed (proximal [Group I], mid [Group II], or distal [Group III]). The visual analog scale (VAS) was used to measure postoperative pain at 1, 4, 8, 12, and 24 h. Additionally, functional pain throughout 24-h standardized static and dynamic tests was assessed. We noted 24-h opioid consumption, motor strength levels, and sensory and motor block features. Results: During each time point, the distal group’s VAS scores were considerably higher than those of the proximal and mid groups (e.g., 8th hour: 40.69 ± 10.50 vs. 26.94 ± 8.72 and 23.47 ± 7.64, p < 0.001), whereas there was no difference between the proximal and mid groups (p > 0.05). At 24 h, the distal group had significantly higher functional pain scores on all dynamic and static measures (p < 0.001). The proximal and mid groups had longer sensory block durations (5.38 ± 1.33 and 5.03 ± 1.29 h) than the distal group (2.95 ± 0.95 h, p < 0.001). While mid-level ACB maintained motor function, 13.9% of patients receiving proximal ACB experienced transient motor block. Conclusions: After TKA, injection level has a major impact on postoperative analgesia. Mid-level ACB supports the employment of multimodal analgesia techniques by offering the best possible compromise between efficient pain management and motor function maintenance. Full article

Background/Objectives: Diabetic peripheral neuropathy (DPN) is a common and disabling complication of diabetes. B vitamins play essential roles in neuronal metabolism, but evidence on their therapeutic efficacy remains inconsistent. The review and meta-analysis aimed to evaluate the effects of vitamin B supplementation on clinical and neurophysiological outcomes in DPN. Methods: We searched PubMed, Cochrane Database, and ClinicalTrials.gov, supplemented by reference screening of relevant systematic reviews. Randomized controlled trials (RCTs) comparing vitamin B (any form, dose, route) versus placebo or standard care in adults with DPN were included. Primary outcomes were pain intensity, neuropathy scores, and nerve conduction parameters. Risk of bias was assessed using RoB 2. Random-effects meta-analyses were performed where appropriate. Results: Thirteen RCTs (834 participants) were included. Vitamin B supplementation significantly improved Michigan Neuropathy Screening Instrument Questionnaire (MNSIQ: MD −1.44, 95% CI −2.48 to −0.39) and Examination (MNSIE: MD −0.39, 95% CI −0.66 to −0.12). However, the improvement in MNSIE did not reach the established minimal clinically important difference (MCID) of 0.5 points. Pain intensity on numeric/visual analogue scales showed no significant effect (MD −0.44, 95% CI −1.77 to 0.89; high heterogeneity, I² = 84.5%), but disease-specific pain scales favoured vitamin B (MD −3.06, 95% CI −5.61 to −0.51). Sural nerve conduction velocity (MD 2.10 m/s, 95% CI 0.35 to 3.86) and amplitude (MD 0.88 µV, 95% CI 0.08 to 1.67) improved significantly. Peroneal and tibial nerve parameters showed no consistent benefit; tibial velocity favoured control (MD −1.23 m/s, 95% CI −2.37 to −0.09). Combination B-vitamin regimens appeared more effective than monotherapy. Formal subgroup analysis did not demonstrate a statistically significant difference between monotherapy and combination therapy for MNSIE, MNSIQ, or sural nerve NCV (interaction p > 0.05) but demonstrated one for peroneal nerve NCV (interaction p = 0.039), although a numerical trend towards greater benefit with combination regimens was observed. Risk of bias was low in six studies, some concerns in five, and high in two. Conclusions: Vitamin B supplementation may improve certain clinical neuropathy scores and sural nerve function in DPN, but effects on pain and motor nerve parameters are inconsistent. Combination therapy (multiple B vitamins) seems more promising than single agents. However, substantial heterogeneity and risk of bias preclude firm recommendations for routine use. Well-designed RCTs stratified by baseline vitamin status are needed. Full article

Background: Visio-spatial skills (VSS) are fundamental perceptual–cognitive capacities that enable athletes to process dynamic visual information, interpret spatial relationships, and execute precise motor responses under competitive conditions. In taekwondo, where scoring actions are executed within milliseconds and success depends on the rapid detection and anticipation of an opponent’s movements, well-developed VSS are considered a functional prerequisite for performance. Method: This cross-sectional observational study examined differences in VSS between amateur taekwondo athletes (n = 50) and non-athletes (n = 50) recruited from the King Cetshwayo Municipality District, KwaZulu-Natal, South Africa. Six VSS were assessed using standardized, validated instruments: accommodation facility (AF), saccadic eye movement (SEM), speed of recognition (SR), hand–eye coordination (HEC), peripheral awareness (PA), and visual memory (VM). Between-group comparisons were performed using the Mann–Whitney U test, with effect sizes reported as rank-biserial correlations (r). Results: Taekwondo athletes demonstrated significantly superior performance across all VSS domains (all p ≤ 0.05), with a large effect observed for SR (r = 0.91), HEC (r = 0,87), SEM (r = 0.78), and AF (r = 0.74), and moderate effect for VM (r = 0.58) and PA (r = 031). The largest between-group percentage differences were observed for SR (79.43%), HEC (48.13%), and SEM (33.33%), with smaller but significant differences in AF (31.05%), VM (14.92%), and PA (4.23%). Pearson correlation analysis revealed a dense, globally integrated VSS network in non-athletes anchored by AF, contrasting with a sparse pattern in taekwondo athletes, in which SEM showed the greatest number of moderate or stronger associations with other variables. These within-group correlation structures are presented as preliminary and descriptive observations only. Intraclass correlation coefficients were excellent for five of the six VSS (ICC ≥ 0.963), with PA yielding a point estimate of ICC = 0.853, characterized by a wide confidence interval. Conclusions: These findings indicate that amateur taekwondo athletes show superior perceptual, oculomotor, and visuo-motor performance compared to non-athletes. Within-group VSS correlation pattern differs descriptively between the groups. The cross-sectional design cannot determine whether these differences reflect training-associated perceptual adaptation, pre-existing trait-based self-selection into taekwondo, or a combination of both mechanisms. Both interpretations carry applied implications for talent identification and vision training program design. A longitudinal investigation is required to establish causal directionality. SEM and AF are proposed as the most diagnostically informative VSS markers for taekwondo screening, under either interpretation. Full article

Background/Objectives: Non-motor symptoms (NMS) are highly prevalent in advanced Parkinson’s disease (PD) and substantially affect quality of life. Continuous infusion therapies are established treatment options for motor fluctuations not controlled by oral medication, but their effects on NMS remain incompletely characterized. We aimed to evaluate the effects of continuous infusion therapies on NMS in advanced PD. Methods: A systematic review was conducted according to PRISMA guidelines. PubMed, Embase, and Cochrane were searched for English-language original studies published between January 2005 and 1 March 2026. Eligible studies included patients with PD treated with levodopa–carbidopa intestinal gel (LCIG), continuous subcutaneous apomorphine infusion (CSAI), subcutaneous levodopa formulations, or levodopa–entacapone–carbidopa intestinal gel (LECIG) and reported quantitative NMS outcomes. Due to methodological heterogeneity, results were synthesized qualitatively. Results: Fifty-four studies were included. Most evaluated LCIG (n = 38), followed by CSAI (n = 14), subcutaneous levodopa formulations (n = 6), and LECIG (n = 2). Overall, 4157 patients were assessed at baseline and 2919 at follow-up. Global non-motor burden improved in 33/45 (73.3%) baseline-to-follow-up comparisons. NMSS total score decreased from 84.4 ± 35.2 to 54.9 ± 17.6. The most consistent benefits were observed for sleep/fatigue and gastrointestinal symptoms. Sleep/fatigue outcomes improved in 26/31 (83.9%) baseline-to-follow-up comparisons. Cognitive outcomes were mostly stable, while cardiovascular, urinary, sexual, and mood-specific outcomes showed less consistent benefit. Conclusions: Continuous infusion therapies may be associated with reduced global non-motor burden in advanced PD, particularly sleep/fatigue and gastrointestinal symptoms. Evidence is strongest for LCIG, while data for CSAI, LECIG, and subcutaneous levodopa formulations remain limited. Full article

Background and aim: Motor fitness is a key determinant of functional independence and healthy aging in older adults. The Motor Fitness Scale (MFS) is a simple and widely used instrument for assessing mobility, strength, and balance; however, no validated Arabic version exists. This study aimed to translate, cross-culturally adapt, and evaluate the psychometric properties of the Arabic MFS in a Saudi geriatric population. Methods: This cross-sectional validation study was conducted at King Saud University Medical City (2025–2026) among adults aged ≥50 years. Structural validity was examined using confirmatory factor analysis (CFA) with a hierarchical three-factor model (mobility, strength, balance). Reliability was assessed using Cronbach’s alpha, composite reliability, and intraclass correlation coefficient (ICC). Discriminative validity was examined using logistic regression and ROC analysis. Results: A total of 140 participants (median age 60 years) were included. CFA supported the second-order three-factor model with good model fit (CFI = 0.986, TLI = 0.983, RMSEA = 0.038). Composite reliability ranged from 0.703 to 0.840 across subscales, and internal consistency was good (α = 0.842). Test–retest reliability was strong (r = 0.797; ICC = 0.831), with no systematic score differences over time. The MFS demonstrated moderate discriminative ability for physical activity status (AUC = 0.671), and higher MFS scores independently predicted physical activity (OR = 1.19, p = 0.007). Conclusions: The Arabic Motor Fitness Scale demonstrates good structural validity, internal consistency, and test–retest reliability among older adults in Saudi Arabia. The Ar-MFS is a practical and psychometrically sound instrument for assessing motor fitness and functional performance in Arabic-speaking geriatric populations. Full article

Background/Objectives: The aim of this study was to precisely characterize neurological deficits in patients with idiophatic scoliosis (IS) by comparing preoperative clinical and neurophysiological examination results in patients with Lenke 1 and 3 spinal curvatures. Bracing alone (NTP) is commonly applied preoperatively in subjects with IS, but incorporating the concept of prerehabilitation with additional physiotherapy (TP) may further slow the progression of scoliosis. Methods: An interview regarding the development and conservative treatment of IS, clinical neurological assessment, and bilateral neurophysiological tests involving electromyography (sEMG) of motor unit activity in the paraspinal and lower extremity muscles, electroneurography (ENG) of neural impulse transmission in the peroneal nerve motor fibers and entire efferent conduction involving recordings of motor evoked potentials (MEPs) induced with transcranial magnetic field stimulation (TMS) were performed in patients with Lenke 1 (N = 33) and Lenke 3 (N = 27) spine curvatures in two groups (N = 30 each) that were treated (TP) or not treated (NTP) with physiotherapy. Results: Back pain, assessed on the VAS by all Lenke 3 patients, was 3.3 on average. Limited spine mobility (p < 0.001) was not associated with better results following physiotherapeutic treatment in either Lenke patient group. Sensory perception studies within the L3–S1 dermatomes and vibration sensation tests were found to be slightly decreased in Lenke 3 patients (p < 0.001), predominantly on the concave IS side, but less so in the TP group. Achilles tendon and patellar reflexes were detected as pathological (p < 0.001) only in Lenke 3 patients, and less frequently in the TP group. Asymmetry on the concave side of scoliosis in manual muscle testing scores was found (p < 0.001) in Lenke 3 patients, showing moderate muscle weakness in the distal lower extremities, mainly in the NTP group. sEMG recordings from the paraspinal muscles revealed moderate neurogenic abnormality that was more intense on the concave side of scoliosis curvature, both main and second; the pattern of muscle motor unit activity in the proximal and distal muscles of the lower extremities was consistent with the muscle strength deficits observed in manual muscle testing, though less so in the TP group. Deficits in MEP amplitudes recorded from lower extremity muscles and the peroneal nerve were found to be more commonly expressed on the concave side of the main scoliosis curvature and on the concave side of the second scoliosis curvature, particularly in Lenke 3 patients, but the significance of changes was lower in the TP group (p = 0.03–0.009). ENG studies showed moderate abnormalities in peripheral neural conduction of peroneal nerve motor fibers originating at the L5 ventral root, especially in Lenke 3 patients from the NTP group. Conclusions: Neurological diagnostic tests, supported by selected clinical neurophysiological studies, reveal greater motor and sensory abnormalities in IS patients with Lenke 3 than with Lenke 1 curvatures. The study indicates that patients in both groups who received only bracing had poorer outcomes than those who received additional physiotherapy. In the context of prerehabilitation, a combined conservative treatment approach including physiotherapy can provide functional benefits for the IS patient before the necessary surgical treatment. In this study, differences were observed between the groups treated with physiotherapy and those not treated; however, a causal link cannot be established. The results are consistent with a possible benefit of the physiotherapy, but they require further prospective studies to be proven. Full article

Parkinson’s disease is a progressive neurodegenerative disorder characterized by motor impairments that significantly affect handwriting and fine motor control. Recent advances in artificial intelligence have enabled the non-invasive analysis of handwritten patterns as reliable digital biomarkers for early Parkinson’s disease detection. However, existing deep-learning approaches often struggle with diagnostic uncertainty and lack interpretability, limiting their clinical reliability and practical adoption. Moreover, models trained on single datasets frequently exhibit poor generalization across heterogeneous handwriting sources. This study uses two image-based handwriting datasets and one CSV-based HandPD feature dataset, including the Parkinson’s Augmented Handwriting Dataset, Parkinson’s Drawings Dataset, and HandPD Spiral/Meander feature records. A Transformer-based architecture is employed to learn global motor patterns from handwriting images, followed by a fuzzy-logic-based decision layer to handle uncertainty and improve robustness. The novelty of this work lies in integrating Transformer-driven deep feature learning with fuzzy clinical reasoning, supported by an AIC-based handcrafted feature analysis for interpretability. The model performance is evaluated using accuracy, precision, recall, F1-score, MCC, and AUC metrics. The experimental results demonstrate that the proposed Transformer–Fuzzy framework consistently outperforms CNN and Transformer-only baselines, achieving superior classification performance and robust generalization across all datasets, thereby establishing its effectiveness for reliable and interpretable Parkinson’s disease screening. Full article

Background/Objectives: Major Depressive Disorder (MDD) is a leading cause of disability, yet physical therapy (PT) is underrepresented in hospital-based psychiatric care. While exercise is a known adjunctive treatment, specific evidence on functional, task-oriented interventions in acute settings remains scarce. This study explored changes in quality of life, depressive symptoms, pain, and self-efficacy in patients with MDD following a specialized hospital-based PT program focused on functional movement and autonomy. Methods: We conducted a prospective pre–post case series in the Short-Stay Psychiatric Unit of the Royo Villanova University Hospital (Zaragoza, Spain). We recruited seven adult patients with MDD via convenience sampling. The intervention consisted of a group-based PT program (two 45 min sessions/week during the hospital stay) utilizing task-oriented functional exercises targeting progressive strength, balance, and motor control designed to enhance self-efficacy through activities of daily living (ADLs), combined with health education. Outcomes included the EQ-5D-3L (quality of life), MADRS (depression), NRS (pain), GSE (self-efficacy), and GCPC-UN-ESU (satisfaction). Results: All seven participants (100%) exhibited a positive upward trend in self-perceived health status via the EQ-VAS (mean increase of 35 points). Six cases (85.7%) showed preliminary positive trends in the anxiety/depression dimension of the EQ-5D-3L, with the mean Single Index Value increasing from 0.310 to 0.683. Reductions in depressive symptom severity were observed in six participants, with several transitioning toward moderate or mild levels. Additionally, four patients reported descriptive reductions in pain intensity and showed favorable shifts in self-efficacy scores. Six participants expressed high satisfaction with the intervention. Conclusions: Integrating a hospital-based functional PT program with standard care may offer preliminary benefits for quality of life and reduce depressive symptoms in MDD patients. These findings suggest that task-oriented PT presents a feasible complementary approach for acute psychiatric admissions, although larger controlled trials are needed to confirm these exploratory results. Full article

Background/Objectives: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impairments in social communication and the presence of restricted and repetitive behaviors, often accompanied by motor impairments. Previous research indicates that regular physical exercise may reduce autism-related behaviors and improve motor competence. This study aimed to examine the effects of an adapted aquatic exercise program on autism-related behaviors, flexibility, and handgrip strength, key motor functions relevant to daily functioning. Methods: In this parallel-group randomized controlled trial, 35 boys with mild autism spectrum disorder (aged 8.4 ± 2.1 years) were enrolled. Participants were randomly assigned to an exercise group (n = 17) and a control group (n = 18). The exercise group completed a 16-week adapted aquatic exercise program (2 sessions/week, 50 min/session), while the control group received usual education only. The primary outcome was autism-related behaviors assessed by the Autism Behavior Checklist (ABC); secondary outcomes included flexibility and handgrip strength. Results: The exercise group showed significant improvements in Autism Behavior Checklist (ABC) scores, flexibility, and handgrip strength compared with the control group (p < 0.05). Large effect sizes were observed across all outcomes (partial eta squared, ηp² > 0.14). These findings indicate that adapted aquatic exercise confers beneficial effects on behavioral and motor outcomes in children with mild ASD. Conclusions: Regular participation in adapted aquatic exercise reduces autism-related behaviors and improves flexibility and handgrip strength. These findings provide empirical support for the inclusion of aquatic exercise in intervention programs targeting children with ASD and may inform future research and practice. Full article

Background: Artificial intelligence in medicine has largely relied on supervised training of disease-specific models, limiting scalability in conditions where labeled data are scarce. Large language models (LLMs), which encode broad medical knowledge through large-scale pretraining, offer an alternative paradigm in which structured physiological measurements can be interpreted directly without task-specific model training. Objective: To evaluate whether smartphone-derived ocular motor biomarkers can be translated into clinically meaningful probabilistic assessments of Huntington’s disease (HD) using general-purpose LLMs operating as inference engines. Methods: In this prospective proof-of-concept study, 26 participants (13 with genetically confirmed HD and 13 age-matched controls) completed a standardized ocular motor assessment using a custom smartphone application. Quantitative eye-movement metrics were validated against expert neurologist ratings. Structured physiological features were then provided to four general-purpose LLMs without task-specific training or diagnostic labels, and the models generated an AI-Assigned HD Probability Score (HAIPS). Discriminative performance and associations with clinical severity measures were evaluated. Results: Smartphone-derived ocular motor metrics showed strong agreement with clinician assessments (Spearman ρ = 0.76–0.95; all p < 0.001), confirming preservation of clinically meaningful physiological signals. LLM-derived HAIPS distinguished HD from controls with high accuracy (AUC 0.879–0.944), with no significant differences across models. Discrimination was statistically equivalent to a supervised logistic regression model trained on the same features. HAIPS correlated strongly with established measures of disease severity, including cognitive (MoCA, ρ = −0.86), functional (TFC, ρ = −0.74), and motor impairment (UHDRS, ρ = 0.85) (all p ≤ 0.003). Conclusions: Structured ocular motor biomarkers acquired using a consumer smartphone can be translated into clinically meaningful probabilistic assessments of HD by general-purpose LLMs without disease-specific model training. These findings support a framework in which physiologically grounded digital biomarkers are coupled with general-purpose inference models, potentially enabling scalable assessment in rare neurological diseases where labeled data are limited. Full article

Background/Objectives: Wearable technology is increasingly used to provide biofeedback in physical rehabilitation; however, there is no consensus on which biofeedback parameter is most appropriate for clinical use, as most studies evaluate only one arbitrarily selected parameter. This study presents a wearable multimodal biofeedback system integrating multiple parameters selected based on the prior literature and evaluates its feasibility, usability, and implementation within a rehabilitation context through a longitudinal post-stroke case study. Methods: The system integrates inertial and electromyographic sensors to monitor centre of mass (CoM-B), joint angle (ANG-B), and muscle activity (EMG-B), delivering real-time sensory cues based on the monitored parameters. Feasibility was assessed in a post-stroke participant (male, 32 years, 29 months post-stroke, left hemiparesis, Fugl-Meyer Lower Extremity Score = 27) across 15 sessions involving stand-to-sit, split-stance weight shifting, and walking tasks. Each task was practiced with all three biofeedback parameters, with five sessions per parameter. Results: The motor performance varied across biofeedback parameters and tasks. CoM-B was associated with favourable trends in motor performance during stand-to-sit, showing improvements in medio-lateral displacement (0.03/session); ANG-B during walking, showing increased ankle dorsiflexion (1 deg/session); and EMG-B during split-stance weight shifting, showing increased tibialis anterior activation (5 µV/session). Conclusions: The findings generate the hypothesis that the ability of biofeedback to elicit favourable motor performance is task-dependent, suggesting that the choice of biofeedback parameters may need to be adapted to task demands. The system demonstrated high usability and feasibility, supporting its potential for post-stroke rehabilitation. Further studies are needed to test the generated hypothesis and evaluate the system efficacy. Full article