Search Results (717)

Bioinspired soft adhesive systems capable of stable and intelligent object manipulation are critical for next-generation robotics. In this study, a soft gripper combining an octopus-inspired suction mechanism with a frog-inspired hexagonal friction pattern was developed to enhance adhesion performance under diverse surface conditions and orientations. The hexagonal pattern, inspired by frog toe pads, contributed to improved stability against tilting and shear forces. The integrated strain gauge enabled real-time monitoring of gripping states and facilitated the detection of contact location and changes in load distribution during manipulation. The system demonstrated robust adhesion under both dry and wet conditions, with adaptability to various object geometries and inclinations. These results suggest broad potential for bioinspired gripping platforms in fields such as collaborative robotics, medical tools, and underwater systems. Full article

Total knee arthroplasty is an extensive orthopedic surgery for patients with severe cases of osteoarthritis. This surgery restores the range of motion in the knee joint and allows for pain-free movement. Advancements in medical techniques used in the surgical zone and implant technology, as well as the management of operations and administration for around two decades prior, have hugely improved surgical outcomes for patients. In this study, advancements in TKA were examined through exploring aspects such as robotic surgery, new implants and materials, minimally invasive surgery, and post-surgery rehabilitation. This paper entails a review of the peer-reviewed literature published between 2005 and 2025 in the PubMed and Google Scholar databases. For predictors, we incorporated clinical relevance together with methodological soundness and relation to review questions to select relevant research articles. We used the PRISMA flowchart to illustrate the article selection system in its entirety. Since robotic surgical and navigation systems have been implemented, surgical accuracy has improved, there is an increased possibility of ensuring alignment, and the use of cementless and 3D-printed implants has increased, offering durable long-term fixation features. The trend in the current literature is that minimally invasive knee surgery (MIS) techniques reduce permanent pain after surgery and length of hospital stays for patients, though the long-term impact still needs to be established. There is various evidence outlining that the enhanced recovery after surgery (ERAS) protocols show positive results in terms of functional recovery and patient satisfaction. The integration of these new advancements enhances TKA surgeries and translates them into ‘need of patient’ procedures, ensuring improved results and increases in patient satisfaction. The aim of this study was to perform a comprehensive analysis of the existing literature regarding TKA advancement studies to identify current gaps and problems. Full article

Background: A critical review of the literature demonstrates that masticatory apparatus with an artificial oral environment is of interest in the fields including (i) dental science; (ii) food science; (iii) the pharmaceutical industries for drug release. However, apparatus that closely mimics human chewing and oral conditions has yet to be realised. This study investigates the vital role of dental morphology and form–function connections using two-bite test parameters for effective drug release from medicated chewing gum (MCG) and compares them to human chewing efficiency with the aid of a humanoid chewing robot and a bionics product lifecycle management (PLM) framework with built-in reverse biomimetics—both developed by the first author. Methods: A novel, bio-engineered two-bite testbed is created for two testing machines with compression and torsion capabilities to conduct two-bite tests for evaluating the mechanical properties of MCGs. Results: Experimental studies are conducted to investigate the relationship between biting force and crushing/shearing and understand chewing efficiency and effective mastication. This is with respect to mechanochemistry and power stroke for disrupting mechanical bonds releasing the active pharmaceutical ingredients (APIs) of MCGs. The manuscript discusses the effect and the critical role that jaw physiology, dental morphology, the Bennett angle of mandible (BA) and the Frankfort-mandibular plane angle (FMA) on two-bite test parameters when FMA = 0, 25 or 29.1 and BA = 0 or 8. Conclusions: The impact on other scientific fields is also explored. Full article

Design and use of wearable technology have grown exponentially, particularly in consumer products and service sectors, e.g., healthcare. However, there is a lack of a comprehensive understanding of wearable technology in consumer acceptance. This systematic review utilized a PRISMA on peer-reviewed articles published between 2014 and 2024 and collected on WoS, Scopus, and ScienceDirect. A total of 38 full-text articles were systematically reviewed and analyzed using bibliometric, thematic, and descriptive analysis to understand the technical functions of digital wearable products (DWPs) in consumer acceptance. The findings revealed four key functions: (i) wearable technology, (ii) appearance and design, (iii) biomimetic innovation, and (iv) security and privacy, found in eight types of DWPs, among them smartwatches, medical robotics, fitness devices, and wearable fashions, significantly predicted the customers’ acceptance moderated by the behavioral factors. The review also identified five key outcomes: health and fitness, enjoyment, social value, biomimicry, and market growth. The review proposed a comprehensive acceptance model that combines biomimetic principles and AI-driven features into the technical functions of the technical function model (TAM) while addressing security and privacy concerns. This approach contributes to the extended definition of TAM in wearable technology, offering new pathways for biomimetic research in smart devices and robotics. Full article

This paper presents the PRONOBIS project, an ultrasound-only, robotically assisted, deep learning-based system for prostate scanning and biopsy treatment planning. The proposed system addresses the challenges of precise prostate segmentation, reconstruction and inter-operator variability by performing fully automated prostate scanning, real-time CNN-transformer-based image processing, 3D prostate reconstruction, and biopsy needle position planning. Fully automated prostate scanning is achieved by using a robotic arm equipped with an ultrasound system. Real-time ultrasound image processing utilizes state-of-the-art deep learning algorithms with intelligent post-processing techniques for precise prostate segmentation. To create a high-quality prostate segmentation dataset, this paper proposes a deep learning-based medical annotation platform, MedAP. For precise segmentation of the entire prostate sweep, DAF3D and MicroSegNet models are evaluated, and additional image post-processing methods are proposed. Three-dimensional visualization and prostate reconstruction are performed by utilizing the segmentation results and robotic positional data, enabling robust, user-friendly biopsy treatment planning. The real-time sweep scanning and segmentation operate at 30 Hz, which enable complete scan in 15 to 20 s, depending on the size of the prostate. The system is evaluated on prostate phantoms by reconstructing the sweep and by performing dimensional analysis, which indicates 92% and 98% volumetric accuracy on the tested phantoms. Three-dimansional prostate reconstruction takes approximately 3 s and enables fast and detailed insight for precise biopsy needle position planning. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article

This paper examines the integration of markerless augmented reality (AR) within the da Vinci Surgical Robot, utilizing artificial intelligence (AI) for improved precision. The main challenge in creating AR for these systems is the small size (5 mm diameter) of the cameras used. Traditional camera-calibration approaches produce significant errors when used for miniature cameras. Further, the use of external markers can be obstructive and inaccurate in dynamic surgical environments. The study focuses on overcoming these limitations of traditional AR methods by employing advanced neural networks for camera calibration and real-time image processing. We demonstrate the use of a dense neural network to reduce the total projection error by directly learning the mapping of a 3D point to a 2D image plane. The results show a median error of 7 pixels (1.4 mm) when using a neural network, as compared to an error of 50 pixels (10 mm) when using a more traditional approach involving camera calibration and robot kinematics. This approach not only enhances the accuracy of AR for surgical procedures but also offers a more seamless integration with existing robotic platforms. These research findings underscore the potential of AI in revolutionizing AR applications in medical robotics and other teleoperated systems, promising efficient and safer interventions. Full article

Biomimetic robotics and sensor technologies are reshaping the landscape of healthcare and rehabilitation. Despite significant progress across various domains, many areas within healthcare still demand further bio-inspired innovations. To advance this field effectively, it is essential to synthesize existing research, identify persistent knowledge gaps, and establish clear frameworks to guide future developments. This systematic review addresses these needs by analyzing 89 peer-reviewed sources retrieved from the Scopus database, focusing on the application of biomimetic robotics and sensing technologies in healthcare and rehabilitation contexts. The findings indicate a predominant focus on enhancing human mobility and support, with rehabilitative and assistive technologies comprising 61.8% of the reviewed literature. Additionally, 12.36% of the studies incorporate intelligent control systems and Artificial Intelligence (AI), reflecting a growing trend toward adaptive and autonomous solutions. Further technological advancements are demonstrated by research in bioengineering applications (13.48%) and innovations in soft robotics with smart actuation mechanisms (11.24%). The development of medical robots (7.87%) and wearable robotics, including exosuits (10.11%), underscores specific progress in clinical and patient-centered care. Moreover, the emergence of transdisciplinary approaches, present in 6.74% of the studies, highlights the increasing convergence of diverse fields in tackling complex healthcare challenges. By consolidating current research efforts, this review aims to provide a comprehensive overview of the state of the art, serving as a foundation for future investigations aimed at improving healthcare outcomes and enhancing quality of life. Full article

As artificial intelligence (AI) becomes ubiquitous across various fields, understanding people’s acceptance and trust in AI systems becomes essential. This review aims to identify quantitative measures used to measure trust in AI and the associated studied elements. Following the PRISMA guidelines, three databases were consulted, selecting articles published before December 2023. Ultimately, 45 articles out of 1283 were selected. Articles were included if they were peer-reviewed journal publications in English reporting empirical studies measuring trust in AI systems with multi-item questionnaires. Studies were analyzed through the lenses of cognitive and affective trust. We investigated trust definitions, questionnaires employed, types of AI systems, and trust-related constructs. Results reveal diverse trust conceptualizations and measurements. In addition, the studies covered a wide range of AI system types, including virtual assistants, content detection tools, chatbots, medical AI, robots, and educational AI. Overall, the studies show compatibility of cognitive or affective trust focus between theorization, items, experimental stimuli, and level of anthropomorphism of the systems. The review underlines the need to adapt measurement of trust in the specific characteristics of human–AI interaction, accounting for both the cognitive and affective sides. Trust definitions and measurement could be chosen depending also on the level of anthropomorphism of the systems and the context of application. Full article

Background: Drones are rapidly establishing themselves as one of the most critical technologies. Robotics, automated machinery, intelligent manufacturing, and other high-impact technological research and applications bring up pressing ethical, social, legal, and political issues. Methods: The present research aims to present the results of a qualitative investigation that looked at perceptions of the growing socio-ethical conundrums surrounding the development of drone applications. Results: According to the obtained results, participants often share similar opinions about whether different drone applications are approved by the public, regardless of their level of experience. Perceptions of drone applications appear consistent across various levels of expertise. The most notable associations are with military objectives (73%), civil protection (61%), and passenger transit and medical purposes (56%). Applications that have received high approval include science (8.70), agriculture (8.78), and disaster management (8.87), most likely due to their obvious social benefits and reduced likelihood of ethical challenges. Conclusions: The study’s findings can help shape the debate on drone acceptability in particular contexts, inform future research on promoting value-sensitive development in society more broadly, and guide researchers and decision-makers on the use of drones, as people’s attitudes, understanding, and usage will undoubtedly impact future advancements in this technology. Full article

Technology roadmapping is conducted by systematic mapping of technological evolution through patent analytics to inform innovation strategies. This study proposes an integrated framework combining hierarchical Latent Dirichlet Allocation (LDA) modeling with multiphase technology lifecycle theory, analyzing 113,449 Derwent patent abstracts (2008–2022) across three dimensions: technological novelty, functional applications, and competitive advantages. By segmenting innovation stages via logistic growth curve modeling and optimizing topic extraction through perplexity validation, we constructed dynamic technology roadmaps to decode latent evolutionary patterns in AI-powered programmable manipulators (B25J classification) within an innovation trajectory. Key findings revealed: (1) a progressive transition from electromechanical actuation to sensor-integrated architectures, evidenced by 58% compound annual growth in embedded sensing patents; (2) application expansion from industrial automation (72% early stage patents) to precision medical operations, with surgical robotics growing 34% annually since 2018; and (3) continuous advancements in adaptive control algorithms, showing 2.7× growth in reinforcement learning implementations. The methodology integrates quantitative topic modeling (via pyLDAvis visualization and cosine similarity analysis) with qualitative lifecycle theory, addressing the limitations of conventional technology analysis methods by reconciling semantic granularity with temporal dynamics. The results identify core innovation trajectories—precision control, intelligent detection, and medical robotics—while highlighting emerging opportunities in autonomous navigation and human–robot collaboration. This framework provides empirically grounded strategic intelligence for R&D prioritization, cross-industry investment, and policy formulation in Industry 4.0. Full article

Background: While there is an abundance of comparative studies on open, laparoscopic, and robotic-assisted distal pancreatectomies (RDPs) available in the literature, direct comparisons between RDP and hand-assisted laparoscopic distal pancreatectomy (HALDP) are limited. This study aimed to assess the safety and efficacy of RDPs in comparison to HALDPs in the treatment of pancreatic lesions. Methods: This study reviewed 97 patients who underwent distal pancreatectomy at Carmel Medical Center between 2008 and 2024. After excluding 40 patients (24 open and 16 pure laparoscopic resections), the final cohort comprised 57 patients: 20 RDPs and 37 HALDPs. The primary outcomes included peri-operative parameters, while secondary outcomes encompassed 90-day morbidity and mortality. Results: RDPs led to significantly longer operative times (3.9 vs. 2.5 h, p < 0.001) but resulted in shorter hospital stays (4.7 vs. 5.8 days, p = 0.02) and a higher number of harvested lymph nodes (11 vs. 5.4, p = 0.01). While clinically significant pancreatic fistula rates were numerically higher in the RDP group (35% vs. 16.2%, p = 0.18), this difference was not statistically significant. Overall, complication rates were comparable (55% vs. 43.2%, p = 0.39). Severe morbidity (Clavien–Dindo ≥ IIIa) was absent in the RDP group compared to 8% in the HALDP group (p = 0.04). No 90-day mortality was observed in either group. Conclusions: This study indicates that although RDP involves longer operative times, it may provide certain advantages for patients, such as shorter hospital stays, better lymph node retrieval, and a notable decrease in postoperative morbidity when compared to HALDP. Larger prospective studies are needed to validate these results and to determine the most effective surgical approach for distal pancreatectomy. Full article

Background/Objectives: Prostate cancer ranks as the second-most prevalent cancer globally, and is the fifth-ranking cause of cancer-related mortality. Radical prostatectomy presents a significant risk of postoperative sequelae, including erectile dysfunction. Postoperative erectile dysfunction adversely affects the patient’s quality of life and can severely impact total treatment satisfaction. Nomograms have demonstrated efficacy in forecasting diverse outcomes in urology. We sought to create a nomogram to facilitate a more precise, evidence-based, and individualized prediction of erectile function outcomes following radical prostatectomy. Between January 2018 and January 2022, one hundred and eleven prostate cancer patients had robot-assisted radical prostatectomy, excluding those who had undergone prior transurethral prostatectomy, radiotherapy, or hormone therapy. Demographics, medical records, preoperative and postoperative erectile function statuses, and IIEF scores (≥17 indicating retained erections, <17 indicating full erectile dysfunction) were evaluated. Outcomes: Patients’ ages ranged from 45 to 76 years, with an average of 61.18 ± 6.72 years. Patients in the emergency department were considerably older (p = 0.004; p < 0.01) and exhibited elevated Charlson Comorbidity Indices (3.63 ± 0.85; p = 0.004; p < 0.01). Preoperative IIEF scores in ED patients were lower (14.29 ± 5.34), although obturator internus thickness (20.61 ± 2.91) and intraprostatic urethra length (36.48 ± 9.3) were considerably elevated. Altered surgical techniques were linked to maintained erections (p = 0.002; p < 0.01), but traditional approaches were connected with erectile dysfunction (p = 0.007; p < 0.01). Bilateral nerve-sparing procedures were more prevalent among patients preserving erectile function (p = 0.003; p < 0.01). Conclusions: The nomogram, which includes age, Charlson Comorbidity Index, preoperative IIEF, obturator internus thickness, intraprostatic urethra length, surgical technique, and degree of nerve preservation, provides clinicians with a pragmatic instrument for forecasting postoperative erectile dysfunction in prostate cancer patients. Full article

Robotic arms are used in a wide range of industrial and medical applications. However, for research and education, users often face a trade-off between costly commercial solutions with no adaptability and open-source alternatives that lack usability and functionality. In education, this problem is exacerbated by the prohibitive cost of commercial systems or simplifications that distort learning. Thus, we present HELENE, an open-source robot with six degrees of freedom, closed-loop position control, and robot operating system (ROS) integration. The modular design of the robot, printed on a commercial 3D printer, and its integrated custom electronics allow for easy customization for research purposes. The joints are driven by standard stepper motors with closed-loop position control using absolute encoders. The ROS integration guarantees widespread control options and integration into existing environments. Our prototype, tested in accordance with ISO 9283, has a small positional accuracy error of 8.4 mm and a repeatability error of only 0.87 mm with a load capacity of 500 g at a reach of 432 mm. Ten prototypes were built and used in various research and education applications, demonstrating the versatile applicability of this open-source robot, closing the gap between reliable commercial systems and flexible open-source solutions. Full article

Background/Objectives: The aim of this case series is to evaluate the outcomes and safety of video-assisted mastectomy, illustrating the harmonious collaboration of oncologic and plastic surgery. This novel minimally invasive technique allows immediate prosthetic reconstruction and represents a cost-effective alternative to robotic breast surgery. Methods: Video-assisted, single-port nipple-sparing mastectomies were performed in patients with small to medium-sized breasts, followed by immediate direct-to-implant reconstruction with either prepectoral or dual plane implant placement. The patients’ electronic medical records were analyzed, including demographic characteristics, operative times and histopathology reports. Results: A total of 18 patients underwent successful video-assisted mastectomy, without conversion to traditional open procedure. Fifteen of the operations were risk-reducing mastectomies. Twelve patients had complementary procedures performed concurrently on the previously operated contralateral breast (delayed reconstruction/expander-to-implant exchange). Moreover, three patients benefited from additional minimally invasive techniques during the same surgery (prophylactic laparoscopic hysterectomy). Immediate breast reconstruction with polyurethane or microtextured breast implants up to 450 cc was performed, with satisfactory aesthetic outcomes and no cancer recurrences at 6 to 12 months postoperative follow-up. Early complications included transient hypercapnia, areolar congestion and cellulitis. No skin necrosis or implant-related complications were reported. The most frequently encountered late issues were contour irregularities. Conclusions: Video-assisted mastectomy facilitates the safe removal of proven pathologic or healthy breast tissue with minimal damage to the breast’s skin envelope, facilitating single-stage breast reconstruction. Full article