Search Results (146)

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

Soft and flexible capacitive tactile sensors are vital in prosthetics, wearable health monitoring, and soft robotics applications. However, achieving accurate real-time force detection and spatial localization remains a significant challenge, especially in dynamic, non-rigid environments like prosthetic liners. This study presents a real-time force point detection and tracking system using a custom-fabricated soft elastomeric capacitive sensor array in conjunction with image processing and machine learning techniques. The system integrates Otsu’s thresholding, Connected Component Labeling, and a tailored cluster-tracking algorithm for anomaly detection, enabling real-time localization within 1 ms. A $6\times 6$ Dragon Skin-based sensor array was fabricated, embedded with copper yarn electrodes, and evaluated using a UR3e robotic arm and a Schunk force-torque sensor to generate controlled stimuli. The fabricated tactile sensor measures the applied force from 1 to 3 N. Sensor output was captured via a MUCA breakout board and Arduino Nano 33 IoT, transmitting the Ratio of Mutual Capacitance data for further analysis. A Python-based processing pipeline filters and visualizes the data with real-time clustering and adaptive thresholding. Machine learning models such as linear regression, Support Vector Machine, decision tree, and Gaussian Process Regression were evaluated to correlate force with capacitance values. Decision Tree Regression achieved the highest performance ($R^2=0.9996, RMSE=0.0446$), providing an effective correlation factor of $51.76$ for force estimation. The system offers robust performance in complex interactions and a scalable solution for soft robotics and prosthetic force mapping, supporting health monitoring, safe automation, and medical diagnostics. Full article

Three-dimensional (3D) printing represents a pivotal technological advancement in dental prosthetics, fundamentally transforming the fabrication of provisional crowns and bridges through innovative vat photopolymerization methodologies, specifically stereolithography (SLA) and digital light processing (DLP). This comprehensive scholarly review critically examines the technological landscape of 3D-printed resin-based dental provisional crowns and bridges, systematically analyzing their material performance, clinical applications, and prospective developmental trajectories. Empirical investigations demonstrate that these advanced restorations exhibit remarkable mechanical characteristics, including flexural strength ranging from 60 to 90 MPa and fracture resistance of 1000–1200 N, consistently matching or surpassing traditional manufacturing techniques. The digital workflow introduces substantial procedural innovations, dramatically reducing fabrication time while simultaneously achieving superior marginal adaptation and internal architectural precision. Despite these significant technological advancements, critical challenges persist, encompassing material durability limitations, interlayer bonding strength inconsistencies, and the current paucity of longitudinal clinical evidence. Contemporary research initiatives are strategically focused on optimizing resin formulations through strategic filler incorporation, enhancing post-processing protocols, and addressing fundamental limitations in color stability and water sorption characteristics. Ultimately, this scholarly review aims to provide comprehensive insights that will inform evidence-based clinical practices and delineate future research trajectories in the dynamically evolving domain of digital dentistry, with the paramount objective of advancing patient outcomes through technological innovation and precision-driven methodological approaches. Full article

In recent years, robotics has made notable progress, becoming an essential component of daily life by facilitating complex tasks and enhancing human experiences. While most robots have traditionally featured hard surfaces, the growing demand for more comfortable and safer human–robot interactions has driven the development of soft robots. One type of soft robot, which incorporates innovative skin materials, transforms rigid structures into more pliable and adaptive forms, making them better suited for interacting with humans. Especially in healthcare and rehabilitation, robotic skin technology has gained substantial attention, offering transformative solutions for improving the functionality of prosthetics, exoskeletons, and companion robots. Although replicating the complex sensory functions of human skin remains a challenge, ongoing research in soft robotics focuses on developing sensors that mimic the softness and tactile sensitivity necessary for effective interaction. This review provides a narrative analysis of current trends in robotic skin development, specifically tailored for healthcare and rehabilitation applications, including skin types of sensor technologies, materials, challenges, and future research directions in this rapidly developing field. Full article

Background: Head and neck cancers (HNCs) and their surgical treatment can result in significant functional deficits including impaired masticatory function, dysphagia and dysgeusia, among others. These contribute to nutritional deficits weakening immune responses, increased post-surgical infections and complications. Aim: This study assesses the impact of removable prosthetic restorations on nutritional habits in edentulous patients who have undergone surgery for head and neck cancer. Materials and methods: This study included 44 post-surgical oncology patients and 20 healthy edentulous patients who served as controls. All patients received removable acrylic complete prostheses. Controls received maxillary and mandibular complete prostheses and HNC patients received post-resection complete maxillary and mandibular prostheses. Nutritional intake was assessed through a 24 h dietary recall and the Food Frequency Questionnaire administered before prosthetic treatment and 6 weeks and 3, 6 and 12 months after the provision of removable prosthetic restorations. Results: This study found that both patient groups maintained consistent meal frequency, with the study group exhibiting stable food intake over time. The intake of various food items fluctuated post prosthesis delivery in both groups, with an initial decline followed by partial recovery. Statistically significant differences were observed in food preferences; however, diet variations between and within the groups were not statistically significant. Conclusions: This study found that the use of removable prosthetic restoration in surgically managed edentulous head and neck cancer patients and edentulous controls showed no significant differences apart from certain food preferences and diet variations. A prolonged adaptation period was observed highlighting the need to include clinical dietitians to support the patients. Full article