Search Results (1,827)

Neuromuscular robotic prostheses have emerged as a critical convergence point between biomedical engineering, machine learning, and human–machine interfaces. This work provides a narrative state-of-the-art review regarding recent developments in robotic prosthetic technology, emphasizing sensor integration, actuator architectures, signal acquisition, and algorithmic strategies for intent decoding. Special focus is given to non-invasive biosignal modalities, particularly surface electromyography (sEMG), as well as invasive approaches involving direct neural interfacing. Recent developments in AI-driven signal processing, including deep learning and hybrid models for robust classification and regression of user intent, are also examined. Furthermore, the integration of real-time adaptive control systems with surgical techniques like Targeted Muscle Reinnervation (TMR) is evaluated for its role in enhancing proprioception and functional embodiment. Finally, this review highlights the growing importance of modular, open-source frameworks and additive manufacturing in accelerating prototyping and customization. Progress in this domain will depend on continued interdisciplinary research bridging artificial intelligence, neurophysiology, materials science, and real-time embedded systems to enable the next generation of intelligent prosthetic devices. Full article

Distribution System Operators (DSOs) increasingly need planning tools that coordinate utility-influenced assets—such as electric-vehicle charging stations (EVCS) and voltage-support resources—with customer-sited distributed generation (DG). We present a Nash-equilibrium-based Iterative Best Response Algorithm (IBRA-NE) for joint planning of DG and EVCS in radial distribution networks. The framework supports two applicability modes: (i) a DSO-plannable mode that co-optimizes EVCS siting/sizing and utility-controlled reactive support (DG operated as VAR resources or functionally equivalent devices), and (ii) a customer-sited mode that treats DG locations as fixed while optimizing DG reactive set-points/sizes and EVCS siting. The objective minimizes network losses and voltage deviation while incorporating deployment costs and EV charging service penalties, subject to standard operating limits. A backward/forward sweep (BFS) load flow with Monte Carlo simulation (MCS) captures load and generation uncertainty; a Bus Voltage Deviation Index (BVDI) helps identify weak buses. On the EEU 114-bus system, the method reduces base-case losses by up to 57.9% and improves minimum bus voltage from 0.757 p.u. to 0.931 p.u.; performance remains robust under a 20% load increase. The framework explicitly accommodates regulatory contexts where DG siting is customer-driven by treating DG locations as fixed in such cases while optimizing EVCS siting and sizing under DSO planning authority. A mixed scenario with 5 DGs and 3 EVCS demonstrates coordinated benefits and convergence properties relative to PSO, GWO, RFO, and ARFO. Additionally, the proposed algorithm is also tested on the IEEE 69-bus system and results in acceptable performance. The results indicate that game-theoretic coordination, applied in a manner consistent with regulatory roles, provides a practical pathway for DSOs to plan EV infrastructure and reactive support in networks with uncertain DER behavior. Full article

Background and Clinical Significance: In most cases, the success of radiotherapy in the treatment for skin cancer is limited, particularly due to the irregularities of the neoplasm’s surfaces or even tissue discontinuity. Based on a comprehensive clinical assessment, the therapeutic approach for radiotherapy was established for the patients included in this study. Wax-paraffin (50:50) devices were custom-designed for radiotherapy treatment, confirming adequate homogeneity and conformity indices for doses of 55–66 Gy, and chemotherapy when necessary. Toxicity and treatment response were also assessed; Cases Presentation: For patient 1, two lesions located on the right nasolabial fold and right thigh were treated with radiation, and a 1 cm thick wax-paraffin surface bolus was designed, allowing for improved dose distribution and favorable local response. For patient 2, in addition to the thick wax-paraffin homogenizer, lead eye protectors were designed due to the location of the tumor, with the aim of protecting organs at risk. The treatment in this patient resulted in effective local response. Finally, for patient 3, with a lesion in the supraclavicular region extending to the left shoulder due to acantholytic squamous cell carcinoma with secondary carcinomatous lymphangitis, 1 cm thick wax-paraffin surface homogenizers were used; Conclusions: Due to the characteristics of the customized homogenizers, tumor lesion remission was successfully achieved in all three patients, highlighting both the advantages of these devices and their efficacy in dose distribution and local response in radiotherapy treatment of non-melanoma skin carcinoma. Full article

This is a single-center study about upward facing in branched endovascular aortic repair. Background: The evolution of branched endovascular aortic repair (BEVAR) has introduced upward-facing branches as a novel approach to facilitate exclusive transfemoral access in complex aortic aneurysm repair. This study evaluates the feasibility, safety, and early outcomes of custom-made BEVAR devices incorporating upward-facing branches in patients with cranially oriented renal arteries. The investigation further aims to analyze the technical success and mid-term outcomes related to these novel devices, as well as to identify any challenges or complications specific to the use of upward-facing branches in clinical practice. Methods: We retrospectively analyzed 17 patients treated at a single center between January 2020 and December 2024 using custom-made Cook Medical branched stent grafts with at least one upward-facing branch. Demographics, comorbidities, target vessel details, bridging stent graft (BSG) configurations, and procedure-related complications were collected. The primary endpoints were technical success and branch patency. Secondary endpoints included short- and mid-term branch-related complications. Results: The cohort had a mean age of 70 years, with hypertension (88%) and coronary artery disease (47%) being common comorbidities. Technical success was achieved in 100% of cases. The left renal artery was the most frequently targeted vessel (63.2%). Most upward-facing branches were bridged using a combination of balloon-expandable and self-expandable stents. One patient (5.9%) experienced a renal bleeding complication requiring embolization. There were no cases of primary stent occlusion or dislocation. At a mean follow-up of 14 months, one asymptomatic occlusion of an upward-facing branch was detected in computed tomography angiography. No further upward-facing branch-related complications occurred, and 1-year follow-up was available in 41.2% of patients. Conclusions: In our single-center study including 17 patients, upward-facing branches in BEVAR demonstrate high technical success and a low complication rate, offering a promising alternative to traditional access strategies. These findings support broader adoption in select anatomical scenarios, pending larger comparative studies and longer-term data collection. Full article

Objectives: This study aimed to compare the skeletal and dentoalveolar effects of a fully customized elastodontic appliance with those of the traditional Twin Block appliance in growing patients with Class II malocclusion during the mixed dentition phase. Methods: A total of 35 patients were included: 18 treated with a customized elastodontic appliance (C-Ela group) and 17 with a Twin Block appliance (TB group). Digital dental models and lateral cephalometric radiographs were obtained at baseline (T1) and after 12 months of treatment (T2). All patients were treated by experienced clinicians according to standardized appliance protocols. Data analysis was performed by a blinded operator using Ortho Analyzer and Dolphin Imaging software. The Shapiro–Wilk test was applied to verify the normal distribution of the data. Paired-sample t-tests were used to assess within-group changes between T1 and T2. For intergroup comparisons two-tail independent-sample t-tests were used, and chi-square tests were used for categorical variables. Statistical significance was set at p < 0.05. Results: Both groups showed significant intragroup improvements in overjet (C-Ela: −2.77 ± 2.07; TB: −2.30 ± 2.72 mm), overbite (C-Ela: −1.79 ± 1.95; TB: −1.40 ± 2.65 mm), and sagittal molar relationship (p < 0.05) after treatment. The C-Ela group exhibited a significantly greater reduction in anterior dental crowding (p < 0.05) and better control of upper (C-Ela: −4.93 ± 7.65°; TB: −1.80 ± 5.72°) and lower incisor inclination (C-Ela: +1.70 ± 4.80°; TB: +4.35 ± 6.22°). In intergroup comparisons, the TB group showed a significantly greater proclination of the lower incisors at T2 (L1/Go-Gn: +4.35°; L1/A-Pog: +1.44 mm), whereas the C-Ela more effectively limited these changes (L1/Go-Gn: +1.70°; L1/A-Pog: +1.18 mm). Skeletal analysis revealed an increase in ANB angle in both groups (C-Ela: −1.49 ± 2.62°; TB: −1.78 ± 2.78°), with no statistically significant intergroup differences, and no other skeletal parameters showed significant between-group changes. Conclusions: Both appliances effectively corrected Class II malocclusions. However, the customized elastodontic device provided better dentoalveolar control, particularly in managing anterior crowding and incisor inclination. Its individualized fit may enhance biomechanical precision and improve overall treatment outcomes in growing patients. Full article

Background: The iliotibial band (ITB) is an anatomically complex structure with multiple proximal and distal attachments, making its mechanical behavior difficult to interpret. In the study of iliotibial band syndrome (ITBS), prior research has often considered the underlying lateral femoral epicondyle (LFE) as a fixed reference to describe ITB movement during knee flexion, potentially misrepresenting true tissue dynamics. This proof-of-concept study introduces the musculoskeletal advanced transillumination technique (MATT) to visualize and measure LFE displacement relative to the ITB and the tubercule of the ITB (tITB) on the tibia during passive knee flexion. Methods: Un-embalmed donor knees (n = 8) were dissected to expose the ITB and positioned on a device allowing standardized passive motion from 0° to 30°. A trocar was inserted between the femoral epicondyles, and a 300-watt xenon light source illuminated the LFE. Video was recorded with an iPhone 15, and key frames were analyzed using ImageJ Version 1.54i, and a custom Python (Version 3.12.5) script to quantify LFE displacement relative to the ITB and to the tITB. Results: Median absolute LFE displacement from 0° to 30° was 9.18 mm (IQR 7.23–10.95). Between 0° and 30°, the LFE shifted anteriorly by −1.76 mm (IQR −10.28 to −8.72) relative to the anterior border of the ITB, and by 11.26 mm (IQR 8.27 to 26.33) relative to its posterior border. The LFE-tITB distance increased from 51.98 mm (IQR 49.13–52.36) at 0° to 53.66 mm (IQR 50.08–60.11) at 30°, with a median displacement of 3.92 mm (IQR: 2.48–5.73). Conclusions: Musculoskeletal Advance Transillumination Technique (MATT) is a straightforward and reproducible technique that offers direct visualization of the dynamic relationship between a skeletal landmark and myofascial structures, such as the LFE and the ITB. By challenging the assumption that the LFE is a fixed reference point, MATT opens new perspectives for investigating the biomechanical mechanisms underlying conditions like iliotibial band syndrome. Full article

The increasing demand for energy efficiency in manufacturing has driven the need for advanced modeling techniques to optimize power consumption in machining processes. This study presents a novel approach to modeling power consumption in milling processes using machine learning, leveraging a custom-designed braking device integrated into the milling machine’s main spindle to measure friction forces with high precision. A comprehensive dataset of observations, including parameters such as speed, force, intensity, apparent power, active power, and power factor, was collected under loaded conditions. Nine machine learning models—Linear Regression, Random Forest, Support Vector Regression, Polynomial Regression, Multi-Layer Perceptron with 2 and 3 layers, K-Nearest Neighbors, Bagging, and a hybrid Probabilistic Random Forest—Multi-Layer Perceptron (PIRF–MLP)—were evaluated using 5-fold cross-validation to ensure robust performance assessment. The PIRF–MLP model achieved the highest performance, demonstrating superior accuracy in predicting utile power. The feature importance analysis revealed that force and speed significantly influence power consumption. The proposed methodology, validated on a milling machine, offers a scalable solution for real-time energy monitoring and optimization in machining, contributing to sustainable manufacturing practices. Future work will focus on expanding the dataset and testing the models across diverse machining conditions to enhance generalizability. Full article

The quality of RF signal coverage of mobile networks, and for example, the parameters of LTE signals at many places, is not reliable enough for intensive data transfer. This fact causes mobile service customers to look for and to apply additional local devices or systems for amplification of the initially supplied RF signal level to improve the quality of the service. This local improvement covers a small area around the customer’s residence. This paper shares some useful results of design, analyses, and optimization for effective performance of the tranceiving antenna for LTE (4G) signals. Full article

Most available smart meters sample at low rates and transmit the acquired measurements to a cloud server for further processing. This article presents a prototype smart meter operating at a high sampling frequency (15 kHz) and performing energy disaggregation locally, thus negating the need to transmit the acquired high-frequency measurements. The prototype’s architecture comprises a custom signal conditioning circuit and an embedded board that performs energy disaggregation using a deep learning model. The influence of the sampling frequency on the model’s accuracy and the edge device power consumption, throughput, and latency across different hardware platforms is evaluated. The architecture embeds NILM inference into the meter hardware while maintaining a compact and energy-efficient design. The presented smart meter is benchmarked across six embedded platforms, evaluating model accuracy, latency, power usage, and throughput. Furthermore, three novel hardware-aware performance metrics are introduced to quantify NILM efficiency per unit cost, throughput, and energy, offering a reproducible framework for future NILM-enabled edge meter designs. Full article

This study presents the development of an innovative battery-free, RF-powered implantable microdevice designed for intravesical chemotherapy delivery. The system utilizes a custom-designed RF energy harvesting module that enables wireless energy transfer through biological tissue, eliminating the need for internal power sources. Mechanical and electronic components were co-optimized to achieve full functionality within a compact, biocompatible housing suitable for intravesical implantation. The feasibility of the device was validated through simulation studies and ex vivo experiments using biological tissue models. The results demonstrated successful energy transmission, storage, and sequential actuator activation within a biological environment. The proposed system offers a promising platform for minimally invasive, wirelessly controlled drug delivery applications in oncology and other biomedical fields. Full article

Spinal cord injury (SCI) profoundly affects motor–sensory functions, reducing mobility and quality of life. Robotic exoskeletons offer a promising solution to support gait training, improve mobility, and prevent secondary complications. Existing research predominantly focuses on complete SCI, with limited exploration of long-term effects and tailored training for incomplete SCI. This study investigates device-based outcomes of personalized exoskeleton gait training in 33 individuals with incomplete SCI, with different lesion levels: cervical, thoracic, and lumbar. Participants underwent up to 39 sessions of gait training with a commercially available lower limb exoskeleton. Session parameters, including duration, intensity, and modality, were tailored to each individual’s clinical needs as determined by a medical team. Analysis focused on endurance, performance on the device, and patient-reported outcomes related to walking fluidity, safety, and satisfaction. Results showed overall improvement in endurance and performance, with the most significant gains observed in participants with thoracic-level injuries. All participants reported increased perceived safety, walking fluidity, and high satisfaction with the training. These findings support the potential of personalized exoskeleton training to enhance outcomes and experiences for individuals with incomplete SCI. The difference in improvement between lesion levels highlights the need for customized approaches to address the diverse clinical conditions within this population. Full article

Background/Objectives: Hip-level amputees face ambulatory challenges due to the lack of a lower limb and prosthetic hip power. Some hip-level amputees restore mobility by using a prosthesis with hip, knee, and ankle joints. Powered prosthetic joints contain an actuator that provides external flexion-extension moments to assist with movement. Powered knee and powered ankle-foot units are on the market, but no viable powered hip unit is commercially available. This research details the development of a novel powered four-bar prosthetic hip joint that can be integrated into a full-leg prosthesis. Methods: The hip joint design consisted of a four-bar linkage with a harmonic drive DC motor placed in the inferior link and an additional linkage to transfer torque from the motor to the hip center of rotation. Link lengths were determined through engineering optimization. Device strength was demonstrated with force and finite element analysis and with ISO 15032:2000 A100 static compression tests. Walking tests with a wearable hip-knee-ankle-foot prosthesis simulator, containing the novel powered hip, were conducted with three able-bodied participants. Each participant walked back and forth on a level 10 m walkway. Custom hardware and software captured joint angles. Spatiotemporal parameters were determined from video clips processed in the Kinovea software (ver. 0.9.5). Results: The powered hip passed all force and finite element checks and ISO 15032:2000 A100 static compression tests. The participants, weighing 96 ± 2 kg, achieved steady gait at 0.45 ± 0.11 m/s with the powered hip. Participant kinematic gait profiles resembled those seen in transfemoral amputee gait. Some gait asymmetries occurred between the sound and prosthetic legs. No signs of mechanical failure were seen. Most design requirements were met. Areas for powered hip improvement include hip flexion range, mechanical advantage at high hip flexion, and device mass. Conclusions: The novel powered four-bar hip provides safe level-ground walking with a full-leg prosthesis simulator and is viable for future testing with hip-level amputees. Full article

During the investigation, the effect of screw tightening torque on the potential loosening of screws under load was examined in the case of custom-made subperiosteal implants. The study focused on the connection screws between the implant components, testing the commonly applied tightening torques of 15 Ncm and 30 Ncm. Mastication was simulated using a custom-designed, PLC-controlled testing device, which allowed for the reproduction of variable numbers, forces, and speeds of bite cycles. With this device, six different scenarios were tested, including 500, 2000, and 10,000 bite cycles, under both constant and variable bite forces. A caliper was used to record potential length changes of the screws, force sensors measured the bite forces, and calibrated torque screwdrivers were used to verify the loosening torques. Based on the analysis of the measured data, it was concluded that for the M1.8 screws tested, a tightening torque of 15 Ncm does not provide sufficient resistance against loosening, whereas 30 Ncm offers adequate stability. Full article

Silicon carbide (SiC) MOSFETs with voltage ratings above 3.3 kV are emerging as key enablers for next-generation medium-voltage (MV) power conversion systems, offering superior blocking capabilities, faster switching speeds, and an improved thermal performance compared to conventional silicon IGBTs. However, the practical deployment of 10 kV SiC devices remains constrained by the immaturity of high-voltage chip and packaging technologies. Current development is often limited to engineering samples provided by a few suppliers and custom packaging solutions evaluated only in laboratory settings. To advance the commercialization of 10 kV SiC power modules, this paper presents the design and characterization of a 10 kV, 60 A half-bridge module employing the XHP housing and newly developed SiC MOSFET chips from China Electronics Technology Group Corporation (CETC). Electro-thermal simulations based on a finite element analysis were conducted to extract key performance parameters, with a measured parasitic inductance of 24 nH and a thermal resistance of 0.0948 K/W. To further validate the packaging concept, a double-pulse test platform was implemented. The dynamic switching behavior of the module was experimentally verified under a 6 kV DC-link voltage, demonstrating the feasibility competitiveness of this approach and paving the way for the industrial adoption of 10 kV SiC technology in MV applications. Full article

Facial emotion recognition has become increasingly important in healthcare, where understanding delicate cues like pain, discomfort, or unconsciousness can support more timely and responsive care. Yet, recognizing facial expressions in real-world settings remains challenging due to varying lighting, facial occlusions, and hardware limitations in clinical environments. To address this, we propose TriViT-Lite, a lightweight yet powerful model that blends three complementary components: MobileNet, for capturing fine-grained local features efficiently; Vision Transformers (ViT), for modeling global facial patterns; and handcrafted texture descriptors, such as Local Binary Patterns (LBP) and Histograms of Oriented Gradients (HOG), for added robustness. These multi-scale features are brought together through a texture-aware cross-attention fusion mechanism that helps the model focus on the most relevant facial regions dynamically. TriViT-Lite is evaluated on both benchmark datasets (FER2013, AffectNet) and a custom healthcare-oriented dataset covering seven critical emotional states, including pain and unconsciousness. It achieves a competitive accuracy of 91.8% on FER2013 and of 87.5% on the custom dataset while maintaining real-time performance (~15 FPS) on resource-constrained edge devices. Our results show that TriViT-Lite offers a practical and accurate solution for real-time emotion recognition, particularly in healthcare settings. It strikes a balance between performance, interpretability, and efficiency, making it a strong candidate for machine-learning-driven pattern recognition in patient-monitoring applications. Full article