Search Results (150)

Background/Objectives: This study aimed to identify the functional adaptations that enable competitive performance in a Paralympic cyclist with optimized bilateral transtibial prostheses compared to a conventional cyclist. Additionally, it describes the development of the prosthesis, designed through a user-centered engineering process incorporating Quality Function Deployment (QFD), Computer-Aided Design (CAD), Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), and topological optimization, with the final design (Design 1.4) achieving optimal structural integrity, aerodynamic efficiency, and anatomical fit. Methods: Both athletes performed a progressive cycling test with 50-watt increments every three minutes until exhaustion. Cardiorespiratory metrics, lactate thresholds, and joint kinematics were assessed. Results: Although the conventional cyclist demonstrated higher Maximal Oxygen Uptake (VO₂max) and anaerobic threshold, the Paralympic cyclist exceeded 120% of his predicted VO₂max, had a higher Respiratory Exchange Ratio (RER) [1.32 vs. 1.11], and displayed greater joint ranges of motion with lower trunk angular variability. Lactate thresholds were similar between athletes. Conclusions: These findings illustrate, in this specific case, that despite lower aerobic capacity, the Paralympic cyclist achieved comparable performance through efficient biomechanical and physiological adaptations. Integrating advanced prosthetic design with individualized evaluation appears essential to optimizing performance in elite adaptive cycling. Full article

This paper presents a real-time framework for bilateral gait reconstruction and adaptive joint control using sparse inertial sensing. The system estimates full lower-limb motion from a single-side inertial measurement unit (IMU) by applying a pipeline that includes signal smoothing, temporal alignment via Dynamic Time Warping (DTW), and motion modeling using Gaussian Mixture Models with Regression (GMM-GMR). Contralateral leg trajectories are inferred using both ideal and adaptive symmetry-based models to capture inter-limb variations. The reconstructed motion serves as reference input for joint-level control. A classical Proportional–Integral–Derivative (PID) controller is first evaluated, demonstrating satisfactory results under simplified dynamics but notable performance loss when virtual stiffness and gravity compensation are introduced. To address this, an adaptive fuzzy PID controller is implemented, which dynamically adjusts control gains based on real-time tracking error through a fuzzy inference system. This approach enhances control stability and motion fidelity under varying conditions. The combined estimation and control framework enables accurate bilateral gait tracking and smooth joint control using minimal sensing, offering a practical solution for wearable robotic systems such as exoskeletons or smart prosthetics. Full article

In our previous work, we developed a neuromorphic decoder of intended movements of tetraplegic patients using ECoG recordings from the brain motor cortex, called Motor Control Decoder (MCD). Even though the training data are labeled based on the desired movement, there is no guarantee that the patient is satisfied by the action of the effectors. Hence, the need for the classification of brain signals as satisfactory/unsatisfactory is obvious. Based on previous work, we upgrade our neuromorphic MCD with a Neural Response Decoder (NRD) that is intended to predict whether ECoG data are satisfactory or not in order to improve MCD accuracy. The main aim is to design an actor–critic structure able to adapt via reinforcement learning the MCD (actor) based on NRD (critic) predictions. For this aim, NRD was trained using not only an ECoG signal but also the MCD prediction or prescribed intended movement of the patient. The achieved accuracy of the trained NRD is satisfactory and contributes to improved MCD performance. However, further work has to be carried out to fully utilize the NRD for MCD performance optimization in an on-line manner. Possibility to include feedback from the patient would allow for further improvement of MCD-NRD accuracy. Full article

Background: The interaction between prosthetic restorations and periodontal health is a critical factor for the long-term success of dental treatments. A biologically compatible prosthetic design supports periodontal stability, whereas neglecting periodontal principles can compromise treatment outcomes. This study aimed to validate a questionnaire designed to assess dentists’ perceptions regarding the influence of prosthetic restorations on the periodontium. Material and Methods: An observational cross-sectional study was conducted using a self-administered questionnaire distributed to licensed dentists across Romania. The questionnaire underwent expert review, pilot testing (n = 50), and statistical validation, including the Content Validity Index (CVI), Cronbach’s alpha for internal consistency, and Exploratory Factor Analysis (EFA) using Principal Component Analysis (PCA) with Varimax rotation. The final sample included 39 respondents. Data was analyzed using SPSS v26.0. Results: The questionnaire demonstrated excellent internal consistency (Cronbach’s alpha = 0.900; standardized alpha = 0.917). Most items had corrected item-total correlations > 0.40. EFA revealed eight coherent factors explaining 81.68% of total variance, with high communalities (0.549–0.966), strong Kaiser–Meyer–Olkin test (KMO) values, and significant Bartlett’s test values, confirming construct validity. Descriptive statistics showed predominantly positive attitudes among dentists regarding the periodontal considerations in prosthetic treatment. The highest-rated items emphasized oral hygiene, periodontal stability, and biological adaptation of restorations. Lower scores were associated with routine use of periodontal indices and recognition of failures due to insufficient evaluation. Conclusions: The validated instrument proved reliable and demonstrated strong psychometric properties in this exploratory validation, supporting its use in research and education. Romanian dentists demonstrated a favorable perception of the role of periodontal health in prosthetic success. This tool can inform curriculum development and interdisciplinary clinical protocols in prosthodontics and periodontology. Full article

The integration of artificial intelligence (AI) and advanced digital workflows is revolutionising full-arch implant dentistry, particularly for geriatric patients with edentulous and atrophic arches, for whom achieving both prosthetic passivity and optimal aesthetic outcomes is critical. This narrative review evaluates current challenges in intraoral scanning accuracy—such as scan distortion, angular deviation, and cross-arch misalignment—and presents how innovations like the Medit SmartX AI-guided workflow and the Scan Ladder system can significantly enhance precision in implant position registration. These technologies mitigate stitching errors by using real-time scan body recognition and auxiliary geometric references, yielding mean RMS trueness values as low as 11–13 µm, comparable to dedicated photogrammetry systems. AI-driven prosthetic design further aligns implant-supported restorations with facial symmetry and smile aesthetics, prioritising predictable midline and occlusal plane control. Early clinical data indicate that such tools can reduce prosthetic misfits to under 20 µm and lower complication rates related to passive fit, while shortening scan times by up to 30% compared to conventional workflows. This is especially valuable for elderly individuals who may not tolerate multiple lengthy adjustments. Additionally, emerging AI applications in design automation, scan validation, and patient-specific workflow adaptation continue to evolve, supporting more efficient and personalised digital prosthodontics. In summary, AI-enhanced scanning and prosthetic workflows do not merely meet functional demands but also elevate aesthetic standards in complex full-arch rehabilitations. The synergy of AI and digital dentistry presents a transformative opportunity to consistently deliver superior precision, passivity, and facial harmony for edentulous implant patients. Full article

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article

This paper proposes an adaptive human–robot concurrent control scheme that achieves the appropriate gait trajectory for a robotic leg prosthesis to improve the wearer’s comfort in various tasks. To accommodate different wearers, a neuromuscular-force-based impedance method was developed using muscle activation to reshape gait trajectory. To eliminate the use of sensors for torque measurement, a disturbance observer was established to estimate the interaction force between the human residual limb and the prosthetic receptacle. The cost function was combined with the interaction force and tracking errors of the joints. We aim to reduce the cost function by minimally changing the control weight of the gait trajectory generated by the Central Pattern Generator (CPG). The control scheme was primarily based on human-in-the-loop optimization to search for a suitable control weight to regenerate the appropriate gait trajectory. To handle the uncertainties and unknown coupling of the motors, an adaptive law was designed to estimate the unknown parameters of the system. Through a stability analysis, the control framework was verified by semi-globally uniformly ultimately bounded stability. Experimental results are discussed, and the effectiveness of the adaptive control framework is demonstrated. In Case 1, the mean error (MEAN) of the tracking performance was $3.6°$ and $3.3°$, respectively. And the minimized mean square errors (MSEs) of the tracking performance were $2.3°$ and $2.8°$, respectively. In Case 2, the mean error (MEAN) of the tracking performance is $2.7°$ and $3.1°$, respectively. And the minimized mean square errors (MSEs) of the tracking performance are $1.8°$ and $2.4°$, respectively. In Case 3, the mean errors (MEANs) of the tracking performance for subject1 and 2 are $2.4°$, $2.9°$, $3.4°$, and $2.2°$, $2.8°$, $3.1°$, respectively. The minimized mean square errors (MSEs) of the tracking performance for subject1 and 2 were $1.6°$, $2.3°$, $2.6°$, and $1.3°$, $1.7°$, $2.2°$, respectively. Full article

Cutibacterium acnes (C. acnes) is a commensal bacterium of the skin microbiota that can transform itself into a pathogen depending on the peculiar susceptibility of the host: it is the sole microorganism so far to be found in the specific organ lesions of sarcoidosis, and C. acnes-induced activation of T-helper-type-1 cell responses is generally higher in patients with sarcoidosis than in healthy subjects. This bacterium acts as an opportunistic agent in several inflammatory conditions other than sarcoidosis, such as prostate cancer and prosthetic joint infections. Both innate and adaptive immunity systems are involved in the pathogenesis of C. acnes-mediated sarcoid lesions, and a seminal role is played by host toll-like receptor (TLR)-2, TLR-4, TLR-6, NOD-like receptors, and mononuclear cell cytoplasmic receptors. This review summarizes current knowledge on the potential cause–effect relationship existing between C. acnes and sarcoidosis, addressing issues of future research directions and novel therapeutic strategies in the management of a complex disease such as sarcoidosis. Full article

Electroencephalography (EEG) and surface electromyography (sEMG) signals are widely used in human–machine interaction (HMI) systems due to their non-invasive acquisition and real-time responsiveness, particularly in neurorehabilitation and prosthetic control. However, existing deep learning approaches often struggle to capture both fine-grained local patterns and long-range spatio-temporal dependencies within these signals, which limits classification performance. To address these challenges, we propose a lightweight deep learning framework that integrates adaptive spatial attention with multi-scale temporal feature extraction for end-to-end EEG and sEMG signal decoding. The architecture includes two core components: (1) an adaptive attention mechanism that dynamically reweights multi-channel time-series features based on spatial relevance, and (2) a multi-scale convolutional module that captures diverse temporal patterns through parallel convolutional filters. The proposed method achieves classification accuracies of 79.47% on the BCI-IV 2a EEG dataset (9 subjects, 22 channels) for motor intent decoding and 85.87% on the NinaPro DB2 sEMG dataset (40 subjects, 12 channels) for gesture recognition. Ablation studies confirm the effectiveness of each module, while comparative evaluations demonstrate that the proposed framework outperforms existing state-of-the-art methods across all tested scenarios. Together, these results demonstrate that our model not only achieves strong performance but also maintains a lightweight and resource-efficient design for EEG and sEMG decoding. Full article

Assistive technologies, particularly multi-fingered robotic hands (MFRHs), are critical for enhancing the quality of life for individuals with upper-limb disabilities. However, achieving precise and stable control of such systems remains a significant challenge. This study proposes an Improved Grey Wolf Optimization (IGWO)-tuned Linear Quadratic Regulator (LQR) to enhance the control performance of an MFRH. The MFRH was modeled using Denavit–Hartenberg kinematics and Euler–Lagrange dynamics, with micro-DC motors selected based on computed torque requirements. The LQR controller, optimized via IGWO to systematically determine weighting matrices, was benchmarked against PID and PID-PSO controllers under diverse input scenarios. For step input, the IGWO-LQR achieved a settling time of 0.018 s with zero overshoot for Joint 1, outperforming PID (settling time: 0.0721 s; overshoot: 6.58%) and PID-PSO (settling time: 0.042 s; overshoot: 2.1%). Similar improvements were observed across all joints, with Joint 3 recording an IAE of 0.001334 for IGWO-LQR versus 0.004695 for PID. Evaluations under square-wave, sine, and sigmoid inputs further validated the controller’s robustness, with IGWO-LQR consistently delivering minimal tracking errors and rapid stabilization. These results demonstrate that the IGWO-LQR framework significantly enhances precision and dynamic response. Full article

Background/Objectives: Hypohidrotic ectodermal dysplasia (HED) is a rare hereditary disorder affecting ectoderm-derived tissues including teeth, hair, and sweat glands. The dental abnormalities associated with HED, such as oligodontia and conical teeth, often result in significant functional, esthetic, and psychosocial challenges, particularly during childhood. Methods: A 10-year-old child presented with psychosocial concerns related to missing and malformed teeth. Clinical examination revealed oligodontia, conical anterior teeth, and a resorbed mandibular ridge. Based on clinical findings and a positive family history, a diagnosis of HED with significant dental involvement was confirmed. Results: A conservative prosthodontic approach was selected. A maxillary overdenture was fabricated over the retained primary teeth to enhance retention and preserve the alveolar bone, and a resin-bonded bridge was placed in the mandible due to poor ridge anatomy. The treatment restored oral function and esthetics and improved the child’s self-esteem. A recall visit after three months confirmed good prosthesis adaptation and a positive response from the patient and parents. Conclusions: This case highlights the importance of early, conservative, and developmentally appropriate prosthetic rehabilitation in pediatric patients with HED. Interim prostheses can significantly improve oral function, appearance, and psychosocial well-being while preserving future treatment options as the child matures. Full article

Introduction: Pediatric prosthetic knee joints must be appropriately scaled from adult designs to ensure proper gait biomechanics. However, direct dimensional scaling without considering the biomechanical implications may lead to functional discrepancies. This study aimed to evaluate whether using a linear scaling factor can effectively adapt a knee for pediatric use. The study assessed whether such an approach yields a viable pediatric prosthetic knee joint by applying a fixed scaling factor and analyzing the resultant knee geometry. Methods: The linear scaling factor was determined based on the pylon tube diameter, a key constraint in compact pediatric knee design. Given a pediatric pylon diameter of 22 mm, the length of the tibial link was set to 22 mm, yielding a scaling factor of 0.6875 when compared to the adult-sized knee. This scaling factor was used to determine the dimensions of the pediatric four-bar (scaled) knee joint. Static geometric analysis was conducted using GeoGebra^® to model the lower-body segment lengths. The knee joint’s performance was evaluated based on stance and swing phase parameters. These metrics were compared between the scaled knee and a commercial pediatric knee. Results: The geometric analysis revealed that while using the linear scaling factor maintained proportional relationships, certain biomechanical parameters deviated from the expected pediatric norms. The scaled knee achieved a toe clearance of 13.5 mm compared to 19.7 mm in the commercial design and demonstrated a swing-phase heel clearance of 11.6 mm versus 13.3 mm, maintaining negative x/y ratios at heel contact and showing significant stability in push-off moments, while the stance flexion angle remained within an acceptable range. The heel contact and push-off ratios (x/y) were found to be comparable, with the scaled model achieving values of −1.21 and −0.59, respectively. The stance flexion angle measured 10.6°, closely aligning with the commercial reference. Conclusions: Using a linear scaling factor provides a straightforward method for adapting adult prosthetic knee designs to pediatric use. However, deviations in key biomechanical parameters indicate that further experimental study may be required to validate the applicability of the scaled knee joint for pediatric users. Future work should explore dynamic simulations and experimental validations to refine the design further and ensure optimal gait performance. Full article

Hands are central to nearly every aspect of daily life, so losing an upper limb due to amputation can severely affect a person’s independence. Robotic prostheses offer a promising solution by mimicking many of the functions of a natural arm, leading to an increasing need for advanced prosthetic designs. However, developing an effective robotic hand prosthesis is far from straightforward. It involves several critical steps, including creating accurate models, choosing materials that balance biocompatibility with durability, integrating electronic and sensory components, and perfecting control systems before final production. A key factor in ensuring smooth, natural movements lies in the method of control. One popular approach is to use electromyography (EMG), which relies on electrical signals from the user’s remaining muscle activity to direct the prosthesis. By decoding these signals, we can predict the intended hand and arm motions and translate them into real-time actions. Recent strides in machine learning have made EMG-based control more adaptable, offering users a more intuitive experience. Alongside this, researchers are exploring tactile sensors for enhanced feedback, materials resilient in harsh conditions, and mechanical designs that better replicate the intricacies of a biological limb. This review brings together these advancements, focusing on emerging trends and future directions in robotic upper-limb prosthesis development. Full article

The success of orthopedic implants critically depends on achieving mechanical and biological compatibility with bone tissue. Traditional titanium implants often suffer from high stiffness, which induces stress shielding, a phenomenon that compromises implant integration and accelerates prosthetic loosening. This study introduces an innovative approach to mitigate these limitations by engineering a porous titanium substrate with a controlled microstructure. Utilizing sodium chloride as a spacer holder, an elution and sintering process was applied at 1250 °C under high vacuum conditions to reduce the material’s elastic modulus. By manipulating NaCl volume fractions (20%, 25%, 30%, and 35%), porous titanium samples were created with elastic moduli between 16.37 and 22.56 GPa, closely matching cortical bone properties (4 to 20 GPa). A hydroxyapatite coating applied via plasma thermal spraying further enhanced osseointegration of the material. Comprehensive characterization through X-ray diffraction, scanning electron microscopy, and compression testing validated the material’s structural integrity. In vitro cytotoxicity assessments using osteoblast cells demonstrated exceptional cell viability exceeding 70%, confirming the material’s biocompatibility. These findings represent a significant advancement in biomaterial design, offering a promising strategy for developing next-generation joint prostheses with superior mechanical and biological adaptation to bone tissue. Full article

Background/Objectives: Semi-active prosthetic feet present a promising solution that enhances adaptability while maintaining modest size, weight, and cost. We propose a semi-active Two-Keel Variable-Stiffness Foot (VSF-2K), the first prosthetic foot where both the hindfoot and forefoot stiffness can be independently and actively modulated. We present a model-based analysis of the effects of different VSF-2K settings on prosthesis characteristics and gait metrics. Methods: The study introduces a simulation model for the VSF-2K: (1) one sub-model to optimize the design of the keels of VSF-2K to maximize compliance, (2) another sub-model to simulate the stance phase of walking with different stiffness setting pairs and ankle alignment angles (dorsiflexion/plantarflexion), and (3) a third sub-model to simulate the keel stiffness of the hindfoot and forefoot keels comparably to typical mechanical testing. We quantitatively analyze how the VSF-2K’s hindfoot and forefoot stiffness settings and ankle alignments affect gait metrics: Roll-over Shape ($ROS$), Effective Foot Length Ratio ($EFLR$), and Dynamic Mean Ankle Moment Arm ($DMAMA$). We also introduce an Equally Spaced Resampling Algorithm (ESRA) to address the unequal-weight issue in the least-squares circle fit of the Roll-over Shape. Results: We show that the optimal-designed VSF-2K successfully achieves controlled stiffness that approximates the stiffness range observed in prior studies of commercial prostheses. Our findings suggest that stiffness modulation significantly affects gait metrics, and it can mimic or counteract ankle angle adjustments, enabling adaptation to sloped terrain. We show that $DMAMA$ is the most promising metric for use as a control parameter in semi-active or variable-stiffness prosthetic feet. We identify the limitations in $ROS$ and $EFLR$, including their nonmonotonic relationship with hindfoot/forefoot stiffness, insensitivity to hindfoot stiffness, and inconsistent trends across ankle alignments. We also validate that the angular stiffness of a two-independent-keel prosthetic foot can be predicted using either keel stiffness from our model or from a standardized test. Conclusions: These findings show that semi-active variation of hindfoot and forefoot stiffness based on single-stride metrics such as $DMAMA$ is a promising control approach to enabling prostheses to adapt to a variety of terrain and alignment challenges. Full article