Search Results (621)

Motor impairments significantly affect individuals’ ability to perform activities of daily living, reducing autonomy and quality of life. In response to this, robot-assisted rehabilitation has emerged as an effective and practical solution, enabling controlled limb movements and supporting functional recovery. This study presents the development of an upper-limb exoskeleton designed to assist rehabilitation by integrating neurophysiological signal processing and real-time control strategies. The system incorporates a proportional–derivative (PD) controller to execute cyclic flexion and extension movements based on a sinusoidal reference signal, providing repeatability and precision in motion. The exoskeleton integrates a brain–computer interface (BCI) that utilizes electroencephalographic signals for therapy selection and engagement enabling user-driven interaction. The EEG data extraction was possible by using the UltraCortex Mark IV headset, with electrodes positioned according to the international 10–20 system, targeting alpha-band activity in channels O1, O2, P3, P4, Fp1, and Fp2. These channels correspond to occipital (O1, O2), parietal (P3, P4), and frontal pole (Fp1, Fp2) regions, associated with visual processing, sensorimotor integration, and attention-related activity, respectively. This approach enables a more adaptive and personalized rehabilitation experience by allowing the user to influence therapy mode selection through real-time feedback. Experimental evaluation across five subjects showed an overall mean accuracy of 86.25% in alpha wave detection for EEG-based therapy selection. The PD control strategy achieved smooth trajectory tracking with a mean angular error of approximately 1.70°, confirming both the reliability of intention detection and the mechanical precision of the exoskeleton. Also, our core contributions in this research are compared with similar studies inspired by the rehabilitation needs of stroke patients. In this research, the proposed system demonstrates the potential of integrating robotic systems, control theory, and EEG data processing to improve rehabilitation outcomes for individuals with upper-limb motor deficits, particularly post-stroke patients. By focusing the exoskeleton on a single degree of freedom and employing low-cost manufacturing through 3D printing, the system remains affordable across a wide range of economic contexts. This design choice enables deployment in diverse clinical settings, both public and private. Full article

This paper presents a detailed analysis of the severe structural anomalies that led to the urgent rehabilitation of the Eduardo Caldeira Bridge in Machico, Madeira. Situated in a challenging coastal environment with complex volcanic geology, the bridge exhibited a critical failure of its bearing devices, which were assigned the highest defect severity rating (Grade 5). A multidisciplinary diagnostic methodology, combining visual inspection data, non-destructive testing, and geotechnical analysis, was employed to identify the root causes of this degradation. The investigation concluded that the bearing failure was not due to widespread material deterioration but was directly linked to significant lateral structural displacements, exacerbated by localized geotechnical instabilities. This paper details the data-driven rehabilitation strategy that was subsequently implemented, including the complete replacement of the bearings and substructure stabilization measures. The study provides a valuable case study of a complex, mechanics-driven failure mode and demonstrates that for such critical infrastructure, a proactive management model integrating advanced technologies like Structural Health Monitoring (SHM) and Building Information Modelling (BIM) is essential for ensuring long-term safety and resilience. Full article

Exoskeleton robots function as augmentation systems that establish mechanical couplings with the human body, substantially enhancing the wearer’s biomechanical capabilities through assistive torques. We introduce a lumbar spine-assisted exoskeleton design based on Variable-Stiffness Pneumatic Artificial Muscles (VSPAM) and develop a dynamic adaptation mechanism bridging the pneumatic drive module with human kinematic intent to facilitate human–robot cooperative control. For kinematic intent resolution, we propose a multimodal fusion architecture integrating the VGG16 convolutional network with Long Short-Term Memory (LSTM) networks. By incorporating self-attention mechanisms, we construct a fine-grained relational inference module that leverages multi-head attention weight matrices to capture global spatio-temporal feature dependencies, overcoming local feature constraints inherent in traditional algorithms. We further employ cross-attention mechanisms to achieve deep fusion of visual and kinematic features, establishing aligned intermodal correspondence to mitigate unimodal perception limitations. Experimental validation demonstrates 96.1% ± 1.2% motion classification accuracy, offering a novel technical solution for rehabilitation robotics and industrial assistance. Full article

Background and Objectives: Knee Osteoarthritis affects about 10% of people over 50, causing pain and functional limitation. Hyaluronic acid (HA) is crucial in regulating the osteocartilaginous matrix. Patients are usually assessed using clinical scores to examine symptoms and quality of life, and in this context, gait analysis could provide an objective assessment of walking patterns to identify any deficits. This systematic review investigates the short and long-term effects of intra-articular HA injections on gait kinematics, pain and activities of daily living (ADL), investigating the correlation between outcomes. Materials and Methods: The review followed PRISMA guidelines. The PICO model included patients with radiographic knee osteoarthritis who received intra-articular HA injections, comparing them to healthy controls or those receiving corticosteroids or placebo. Outcomes included gait kinetics and functional scales at baseline and during follow-ups. Results: From 342 identified articles, 13 were included, comprising a total of 321 patients. The gait analysis utilized optoelectronic systems, inertial sensors, and electromyographic sensors pre- and post-HA treatment. Clinical parameters were assessed using the Visual Analogue Scale, WOMAC OA, Knee Society Score, Lequesne Score, and SF-36. The data showed significant improvement in speed (p = 0.001) and step cadence (p < 0.005) 30 days post-treatment and improvements in knee adduction moment (p < 0.001) and sagittal ground reaction force vectors (p < 0.01) up to six months post-treatment. Pain reduction and improvements in VAS (p < 0.001) and Lequesne score (p < 0.001) were observed in short-term follow-ups. Conclusions: Our study suggests an improvement in pain and knee function after hyaluronic acid injection. Moreover, gait analysis is an important tool for objectively assessing deficits and developing personalized rehabilitation programs. Furthermore, combining infiltrative treatment with rehabilitation could extend the effects of hyaluronic acid and improve results. Full article

Accurately distinguishing hemiplegic gait from healthy gait is significant for alleviating clinicians’ diagnostic workloads and enhancing rehabilitation efficiency. The center of pressure (CoP) trajectory extracted from pressure sensor arrays can be utilized for hemiplegic gait recognition. Existing research studies on hemiplegic gait recognition based on plantar pressure have paid limited attention to the differences in recognition performance offered by CoP trajectories along different directions. To address this, this paper proposes a neural network model based on time–frequency domain feature interaction—the temporal–frequency domain interaction network (TFDI-Net)—to achieve efficient hemiplegic gait recognition. The work encompasses: (1) collecting CoP trajectory data using a pressure sensor array from 19 hemiplegic patients and 29 healthy subjects; (2) designing and implementing the TFDI-Net architecture, which extracts frequency domain features of the CoP trajectory via fast Fourier transform (FFT) and interacts or fuses them with time domain features to construct a discriminative joint representation; (3) conducting five-fold cross-validation comparisons with traditional machine learning methods and deep learning methods. Intra-fold data augmentation was performed by adding Gaussian noise to each training fold during partitioning. Box plots were employed to visualize and analyze the performance metrics of different models across test folds, revealing their stability and advantages. The results demonstrate that the proposed TFDI-Net outperforms traditional machine learning models, achieving improvements of 2.89% in recognition rate, 4.6% in F1-score, and 8.25% in recall. Full article

This study presents a two-dimensional (2D) hydro-morphodynamic simulation of sediment dynamics in the Gemenc floodplain, a critical ecological zone along Hungary’s Danube River. The 60 km study area has a mean discharge of approximately 2300 m³/s, with peak floods exceeding 8000 m³/s. The objective was to analyze sediment transport, deposition, and flood hydrodynamics to support future floodplain restoration. The HEC-RAS 2D model was calibrated using water levels (Baja station), 2024 flood discharges, suspended sediment measurements, and visual stratigraphy surveys conducted after the event. A roughness sensitivity analysis was conducted to optimize Manning’s n values for various land covers. The hydrodynamic model showed strong agreement with observed hydrographs and discharge distributions across multiple cross-sections, capturing complex bidirectional flow between the main River and side branches. Sediment dynamics during the September 2024 Danube flood were effectively simulated, with SSC calibration showing a decreasing concentration trend, highlighting the floodplain’s function as a sediment trap. Predicted deposition patterns aligned with field-based visual stratigraphy, confirming high sediment accumulation near riverbanks and reduced deposition in distal zones. The model reproduced deposition thickness with acceptable variation, demonstrating spatial reliability and predictive strength. This study underscores the value of 2D modeling for integrating hydrodynamics and sediment transport to inform sustainable floodplain rehabilitation. Full article

Background/Objectives: This study assessed outcomes between penetrating keratoplasty (PK) and Descemet’s stripping automated endothelial keratoplasty (DSAEK) when combined with cataract surgery as part of the triple procedure. Methods: Retrospective analysis of 727 triple procedures (525 PK and 202 DSAEK) from 2007–2023. Graft survival, visual acuity, and refractive outcomes were analyzed. Kaplan–Meier and Cox regression were used for survival and prognostic analysis. Results: No statistically significant difference in survival was found (PK—42 months; DSAEK—47 months). DSAEK had better visual acuity improvement and refractive stability. PK had higher astigmatism and variability in refractive error. Conclusions: While graft survival was comparable, DSAEK offers superior visual rehabilitation, supporting its use when refractive predictability is important. Full article

This study presents a wearable haptic feedback system designed to support speech training for individuals with speech and hearing impairments. The system provides real-time tactile cues based on detected phonemes, helping users correct their pronunciation independently. Unlike prior approaches focused on passive reception or therapist-led instruction, our method enables active, phoneme-level feedback using a multimodal interface combining audio input, visual reference, and spatially mapped vibrotactile output. We validated the system through three user studies measuring pronunciation accuracy, phoneme discrimination, and learning over time. The results show a significant improvement in word articulation accuracy and user engagement. These findings highlight the potential of real-time haptic pronunciation tools as accessible, scalable aids for speech rehabilitation and second-language learning. Full article

Total knee replacement (TKR) is a common procedure for pain relief and restoration of the mobility of the knee joint in patients with severe knee joint problems. Despite this, some patients still suffer from stiffness, instability, or pain caused by soft tissue imbalance, malalignment, or implant-related issues. Previously, surgeons have had to use their experience and visual judgment to balance the knee, which has resulted in variability of outcomes. Smart knee implants are addressing these issues by using sensor technology to provide real-time feedback on joint motion, pressure distribution, and loading forces. This enables more accurate intra-operative adjustment, enhancing implant positioning and soft tissue balance and eliminating post-operative adjustment. These implants also enable post-operative monitoring, simplifying the ability to have more effective individualized rehabilitation programs directed at optimizing patient mobility and minimizing complications. While the patient pool for smart knee implantation remains not commonly documented, it was found in a study that 83.6% of the patients would opt to have the monitoring device implemented, and nearly 90% find reassurance in monitoring their healing indicators. As the number of knee replacements is likely to rise due to aging populations and the rising prevalence of joint disease, smart implants are a welcome development in orthopedics, optimizing long-term success and patient satisfaction. Smart knee implants are built with embedded sensors such as force, motion, temperature, and pressure detectors placed within the implant structure. These sensors provide real-time data during surgery and recovery, allowing earlier detection of complications and supporting tailored rehabilitation. The design aims to improve outcomes through better monitoring and personalized care. Full article

Background: Clinical assessment of balance and postural disorders is usually carried out through several common practices including tests such as the Subjective Visual Vertical (SVV) and Limit of Stability (LOS). Nowadays, several cutting-edge technologies have been proposed as supporting tools for stability evaluation. Extended Reality (XR) emerges as a powerful instrument. This proof-of-concept study aims to assess the feasibility and potential clinical utility of a novel MR-based framework integrating HoloLens 2, Wii Balance Board, and Azure Kinect for multimodal balance assessment. An innovative test is also introduced, the Innovative Dynamic Balance Assessment (IDBA), alongside an MR version of the SVV test and the evaluation of their performance in a cohort of healthy individuals. Results: All participants reported SVV deviations within the clinically accepted ±2° range. The IDBA results revealed consistent sway and angular profiles across participants, with statistically significant differences in posture control between opposing target directions. System outputs were consistent, with integrated parameters offering a comprehensive representation of postural strategies. Conclusions: The MR-based framework successfully delivers integrated, multimodal measurements of postural control in healthy individuals. These findings support its potential use in future clinical applications for balance disorder assessment and personalized rehabilitation. Full article

Amblyopia, commonly affecting children aged 0–6 years, results from disrupted visual processing during early development and often leads to reduced visual acuity in one eye. This study presents the development and preliminary usability assessment of a non-invasive ocular monitoring device designed to support oculomotor engagement and therapy adherence in amblyopia management. The system incorporates an interactive maze-navigation task controlled via gaze direction, implemented during monocular and binocular sessions. The device tracks lateral and anteroposterior eye movements and generates visual reports, including displacement metrics and elliptical movement graphs. Usability testing was conducted with a non-probabilistic adult sample (n = 15), including individuals with and without amblyopia. The System Usability Scale (SUS) yielded an average score of 75, indicating good usability. Preliminary tests with two adults diagnosed with amblyopia suggested increased eye displacement during monocular sessions, potentially reflecting enhanced engagement rather than direct therapeutic improvement. This feasibility study demonstrates the device’s potential as a supportive, gaze-controlled platform for visual engagement monitoring in amblyopia rehabilitation. Future clinical studies involving pediatric populations and integration of visual stimuli modulation are recommended to evaluate therapeutic efficacy and adaptability for early intervention. Full article

Chronic musculoskeletal pain negatively affects patients’ quality of life, and pain perceptions may significantly influence rehabilitation outcomes. This study investigated the relationships among pain intensity, pain perceptions, and kinesiophobia in individuals with chronic musculoskeletal pain. No previous studies have examined these variables in combination. A cross-sectional observational study was conducted with 37 participants with non-specific chronic musculoskeletal pain for at least 6 months, affecting the neck (n = 8), lower back (n = 18), upper limbs (n = 5), lower limbs (n = 5), or shoulder (n = 1). The following validated tools were used: (a) Pain Beliefs and Perceptions Inventory (PBPI), (b) the Tampa Scale for Kinesiophobia (TSK), and (c) the Short-Form McGill Pain Questionnaire (SF-MPQ). Spearman r correlation analyses were performed. Total kinesiophobia scores were positively correlated with (a) total pain intensity (McGill score) (r = 0.37, p = 0.022), (b) present pain intensity (PPI) (r = 0.52, p = 0.001), (c) pain duration (r = 0.51, p = 0.001), (d) the “mystery” factor of pain perception (r = 0.41, p = 0.013), and (e) the Visual Analogue Scale (VAS) (r = 0.42, p = 0.009). The total pain perception scores were positively associated with the “fear of injury” factor of kinesiophobia (r = 0.36, p = 0.028). The McGill pain scores were strongly correlated with both PPI (r = 0.63, p = 0.001) and VAS (r = 0.51, p = 0.001). There is a significant relationship between pain perception and kinesiophobia levels in patients with chronic musculoskeletal pain. Limitations of the study include a small and heterogeneous sample regarding pain localization. Further research is required using larger, more homogeneous populations to confirm the present findings. Full article

Objectives: To synthesize evidence on structural and functional neuroplasticity in patients after anterior cruciate ligament reconstruction (ACLR) and its clinical implications. Methods: Adhering to the PRISMA guidelines for systematic reviews and meta-analyses, a literature search was conducted using PubMed, Embase, Web of Science, Scopus, and Cochrane CENTRAL (2018–2025) using specific keyword combinations, screening the results based on predetermined inclusion and exclusion criteria. Results: Among the 27 included studies were the following: (1) sensory cortex reorganization with compensatory visual dependence (5 EEG/fMRI studies); (2) reduced motor cortex efficiency evidenced by elevated AMT (TMS, 8 studies) and decreased γ-CMC (EEG, 3 studies); (3) progressive corticospinal tract degeneration (increased radial diffusivity correlating with postoperative duration); (4) enhanced sensory-visual integration correlated with functional recovery. Conclusions: This review provides a novel synthesis of evidence from transcranial magnetic stimulation (TMS), electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), diffusion tensor imaging (DTI), and functional magnetic resonance imaging (fMRI) studies. It delineates characteristic patterns of post-ACLR structural and functional neural reorganization. Targeting visual–cognitive integration and corticospinal facilitation may optimize rehabilitation. Full article

Background/Objectives: Early experiences can significantly influence brain development, particularly when they occur during specific time windows known as sensitive or critical periods. Therefore, the early promotion of neurodevelopmental functions is crucial in children at risk for neurodevelopmental disabilities, such as those with cerebral palsy. This article introduces AMIRA (A Multidimensional and Integrated Rehabilitation Approach), a rehabilitative framework designed for infants at risk of neurodevelopmental disabilities. Methods: AMIRA is intended to guide clinical–rehabilitation reasoning rather than prescribe a rigid sequence of predetermined activities for the child. The theoretical foundation and structure of AMIRA are presented by formalizing its criteria, objectives, tools, and intervention procedures. The framework comprises four distinct sections, each supported by adaptive strategies to facilitate access to materials and to promote play-based interactions among the child, their environment, and communication partners. Particular attention is given to optimizing both micro- and macro-environments for children with, or at risk of, co-occurring visual impairment. Each rehabilitative section includes three progressive phases: an initial observation phase, a facilitation phase to support the child’s engagement, and an active experimentation phase that gradually introduces more challenging tasks. Results: The intervention pathways in AMIRA are organized according to six core developmental domains: behavioral–emotional self-regulation, visual function, postural–motor skills, praxis, interaction and communication, and cognitive function. These are outlined in structured charts that serve as flexible guidelines rather than prescriptive protocols. Each chart presents activities of increasing complexity aligned with typical developmental milestones up to 24 months of age. For each specific ability, the corresponding habilitation goals, contextual recommendations (including environmental setup, objects, and tools), and suggested activities are provided. Conclusions: This study presents a detailed intervention approach, offering both a practical framework and a structured set of activities for use in rehabilitative settings. Further studies will explore the efficacy of the proposed standardized approach. Full article

Spontaneous quadriceps tendon rupture is a very rare occurrence, notably for bilateral simultaneous ruptures. Its occurrence is commonly linked to an underlying condition that may weaken the tendons leading to rupture. We report the case of a 68-year-old Caucasian male afflicted with long-term gout who presented a bilateral simultaneous quadriceps tendon rupture (BSQTR). We showcase the clinical presentation, the surgical intervention, rehabilitation program, dynamic sonographic monitoring, and home-based rehabilitation techniques of this injury, which aimed to improve activities of daily living (ADL) and quality of life (QoL). The patient was included in a 9-week post-surgical rehabilitation program and a home-based rehabilitation program with subsequent pain management and gait reacquisition. The outcome measures included right and left knee active range of motion (AROM), pain intensity measured on Visual Analogue Scale (VAS), functioning measured through ADL score, and gait assessment on Functional Ambulation Categories (FAC). All endpoints were measured at different time points, scoring significant improvement at discharge compared to baseline (e.g., AROM increased from 0 degrees to 95 degrees, while VAS decreased from 7 to 1, ADL score increased from 6 to 10, and FAC increased from 1 to 5). Moreover, some of these outcomes continued to improve after discharge, and the effects of home-based rehabilitation program and a single hip joint manipulation were assessed at 6-month follow-up. Musculoskeletal ultrasound findings showed mature tendon structure, consistent dynamic glide, and no scarring. Full article