Search Results (18)

Minimally invasive interventional surgery is commonly used for diagnosing and treating breast cancer, but the high fluidity and deformability of breast tissue reduce intervention accuracy. This study proposes a bionic breast interventional robot that mimics the scorpion’s predation process, actively manipulating tissue deformation to control target displacement and enhance accuracy. The robot’s structure is designed using a modular method, and its kinematics and workspace are analyzed and solved. To address the nonlinear breast tissue deformation problem, a hierarchical tissue method is proposed to simplify the three-dimensional problem into a two-dimensional one. A two-dimensional tissue deformation solver is established based on the minimum energy method for quick resolution. The problem is treated as quasi-static, deriving the displacement relationship between external manipulation points and internal tissue targets. The method of active manipulation of tissue deformation is simulated using MATLAB (2019-b) software to verify the feasibility of the method. Results show maximum errors of 1.7 mm for prostheses and 2.5 mm for in vitro tissues in the X and Y directions. This method improves intervention accuracy in breast surgery and offers a new solution for breast cancer diagnosis and treatment. Full article

Bionic prosthetic hands hold the potential to replicate the functionality of human hands. The use of bionic limbs can assist amputees in performing everyday activities. This article systematically reviews the research progress on bionic prostheses, with a focus on control mechanisms, sensory feedback integration, and mechanical design innovations. It emphasizes the use of bioelectrical signals, such as electromyography (EMG), for prosthetic control and discusses the application of machine learning algorithms to enhance the accuracy of gesture recognition. Additionally, the paper explores advancements in sensory feedback technologies, including tactile, visual, and auditory modalities, which enhance user interaction by providing essential environmental feedback. The mechanical design of prosthetic hands is also examined, with particular attention to achieving a balance between dexterity, weight, and durability. Our contribution consists of compiling current research trends and identifying key areas for future development, including the enhancement of control system integration and improving the aesthetic and functional resemblance of prostheses to natural limbs. This work aims to inform and inspire ongoing research that seeks to refine the utility and accessibility of prosthetic hands for amputees, emphasizing user-centric innovations. Full article

Smart algorithms for gait kinematic motion prediction in wearable assistive devices including prostheses, bionics, and exoskeletons can ensure safer and more effective device functionality. Although embedded systems can support the use of smart algorithms, there are important limitations associated with computational load. This poses a tangible barrier for models with increased complexity that demand substantial computational resources for superior performance. Forecasting through Recurrent Topology (FReT) represents a computationally lightweight time-series data forecasting algorithm with the ability to update and adapt to the input data structure that can predict complex dynamics. Here, we deployed FReT on an embedded system and evaluated its accuracy, computational time, and precision to forecast gait kinematics from lower-limb motion sensor data from fifteen subjects. FReT was compared to pretrained hyperparameter-optimized NNET and deep-NNET (D-NNET) model architectures, both with static model weight parameters and iteratively updated model weight parameters to enable adaptability to evolving data structures. We found that FReT was not only more accurate than all the network models, reducing the normalized root-mean-square error by almost half on average, but that it also provided the best balance between accuracy, computational time, and precision when considering the combination of these performance variables. The proposed FReT framework on an embedded system, with its improved performance, represents an important step towards the development of new sensor-aided technologies for assistive ambulatory devices. Full article

Friction, wear, and the consequent energy dissipation pose significant challenges in systems with moving components, spanning various domains, including nanoelectromechanical systems (NEMS/MEMS) and bio-MEMS (microrobots), hip prostheses (biomaterials), offshore wind and hydro turbines, space vehicles, solar mirrors for photovoltaics, triboelectric generators, etc. Nature-inspired bionic surfaces offer valuable examples of effective texturing strategies, encompassing various geometric and topological approaches tailored to mitigate frictional effects and related functionalities in various scenarios. By employing biomimetic surface modifications, for example, roughness tailoring, multifunctionality of the system can be generated to efficiently reduce friction and wear, enhance load-bearing capacity, improve self-adaptiveness in different environments, improve chemical interactions, facilitate biological interactions, etc. However, the full potential of bioinspired texturing remains untapped due to the limited mechanistic understanding of functional aspects in tribological/biotribological settings. The current review extends to surface engineering and provides a comprehensive and critical assessment of bioinspired texturing that exhibits sustainable synergy between tribology and biology. The successful evolving examples from nature for surface/tribological solutions that can efficiently solve complex tribological problems in both dry and lubricated contact situations are comprehensively discussed. The review encompasses four major wear conditions: sliding, solid-particle erosion, machining or cutting, and impact (energy absorbing). Furthermore, it explores how topographies and their design parameters can provide tailored responses (multifunctionality) under specified tribological conditions. Additionally, an interdisciplinary perspective on the future potential of bioinspired materials and structures with enhanced wear resistance is presented. Full article

Arrays of memristive devices coupled with photosensors can be used for capturing and processing visual information, thereby realizing the concept of “in-sensor computing”. This is a promising concept associated with the development of compact and low-power machine vision devices, which is crucial important for bionic prostheses of eyes, on-board image recognition systems for unmanned vehicles, computer vision in robotics, etc. This concept can be applied for the creation of a memristor based neuromorphic analog machine vision systems, and here, we propose a new architecture for these systems in which captured visual data are fed to a spiking artificial neural network (SNN) based on memristive devices without analog-to-digital and digital-to-analog conversions. Such an approach opens up the opportunities of creating more compact, energy-efficient visual processing units for wearable, on-board, and embedded electronics for such areas as robotics, the Internet of Things, and neuroprosthetics, as well as other practical applications in the field of artificial intelligence. Full article

Adding robotic surgery to bionic reconstruction might open a new dimension. The objective was to evaluate if a robotically harvested rectus abdominis (RA) transplant is a feasible procedure to improve soft-tissue coverage at the residual limb (RL) and serve as a recipient for up to three nerves due to its unique architecture and to allow the generation of additional signals for advanced myoelectric prosthesis control. A transradial amputee with insufficient soft-tissue coverage and painful neuromas underwent the interventions and was observed for 18 months. RA muscle was harvested using robotic-assisted surgery and transplanted to the RL, followed by end-to-end neurroraphy to the recipient nerves of the three muscle segments to reanimate radial, median, and ulnar nerve function. The transplanted muscle healed with partial necrosis of the skin mesh graft. Twelve months later, reliable, and spatially well-defined Hoffmann–Tinel signs were detectable at three segments of the RA muscle flap. No donor-site morbidities were present, and EMG activity could be detected in all three muscle segments. The linear discriminant analysis (LDA) classifier could reliably distinguish three classes within 1% error tolerance using only the three electrodes on the muscle transplant and up to five classes outside the muscle transplant. The combination of these surgical procedure advances with emerging (myo-)control technologies can easily be extended to different amputation levels to reduce RL complications and augment control sites with a limited surface area, thus facilitating the usability of advanced myoelectric prostheses. Full article

A retinal prosthesis, also known as a bionic eye, is a device that can be implanted to partially restore vision in patients with retinal diseases that have resulted in the loss of photoreceptors (e.g., age-related macular degeneration and retinitis pigmentosa). Recently, there have been major breakthroughs in retinal prosthesis technology, with the creation of numerous types of implants, including epiretinal, subretinal, and suprachoroidal sensors. These devices can stimulate the remaining cells in the retina with electric signals to create a visual sensation. A literature review of the pre-clinical and clinical studies published between 2017 and 2023 is conducted. This narrative review delves into the retinal anatomy, physiology, pathology, and principles underlying electronic retinal prostheses. Engineering aspects are explored, including electrode–retina alignment, electrode size and material, charge density, resolution limits, spatial selectivity, and bidirectional closed-loop systems. This article also discusses clinical aspects, focusing on safety, adverse events, visual function, outcomes, and the importance of rehabilitation programs. Moreover, there is ongoing debate over whether implantable retinal devices still offer a promising approach for the treatment of retinal diseases, considering the recent emergence of cell-based and gene-based therapies as well as optogenetics. This review compares retinal prostheses with these alternative therapies, providing a balanced perspective on their advantages and limitations. The recent advancements in retinal prosthesis technology are also outlined, emphasizing progress in engineering and the outlook of retinal prostheses. While acknowledging the challenges and complexities of the technology, this article highlights the significant potential of retinal prostheses for vision restoration in individuals with retinal diseases and calls for continued research and development to refine and enhance their performance, ultimately improving patient outcomes and quality of life. Full article

To investigate the biomechanical performances of artificial cervical disc (ACD) prostheses, many studies have been conducted, either with cervical sections of cadavers under physiological loads or with block-like testing fixtures obeying the ASTM F2346 standard. Unfortunately, both methods are almost impossible to utilize for accurate results of lifetime anti-fatigue experiments for at least 10 million cycles due to the difficulties in cadaver preservation and great deviations of natural cervical bodies, respectively. Based on normal human cervical structural features, a novel specimen fixture was designed for testing the fatigue behavior of ACD prostheses under flexion, extension, and lateral bending conditions, with aspects of both structural and functional bionics. The equivalence between the biomimetic fatigue-testing fixture and the natural cervical sections was investigated by numerical simulations and mechanical experiments under various conditions. This study shows that this biomimetic fatigue-testing fixture could represent the biomechanical characteristics of the normal human cervical vertebrae conveniently and with acceptable accuracy. Full article

In this paper, using the self-consistent charge density-functional tight-binding (SCC DFTB) method, we perform an in silico study of the effect of functionalization by potassium atoms on the electronic properties of a new configuration of the glass-like carbon (GLC) reinforced with (4,4) and (6,5) single-walled carbon nanotubes (SWCNTs). The method of classical molecular dynamics was used to obtain energetically stable GLC configurations with different mass fractions of potassium. It is found that with an increase in the mass fraction of SWCNTs, the elasticity of GLC increases. It is shown that when the GLC structure reinforced with SWCNTs is filled with potassium, the number of available electronic states at the Fermi level increases compared to GLC without nanotubes, which significantly improves the emission and electrophysical characteristics of the carbon nanomaterial. For most structures, at a potassium/carbon mass ratio of 1:100 (0.01), an increase in the Fermi energy is observed, and, hence, a decrease in the work function. The maximum decrease in the work function by ~0.3 eV was achieved at a mass ratio of potassium/carbon of 1:4.5 (0.23) for GLC reinforced with (6,5) SWCNTs. It is revealed that, at a mass ratio of potassium/carbon of 1:28.5 (0.035), the quantum capacitance of GLC reinforced with (4,4) and (6,5) SWCNTs increases by ~9.4% (1752.63 F/g) and 24.1% (2092.04 F/g), respectively, as compared to GLC without nanotubes (1587.93 F/g). Based on the results obtained, the prospects for the application of the proposed GLC configuration in emission electronics devices are predicted. Full article

At present, the combination of 2D materials of different types of conductivity in the form of van der Waals heterostructures is an effective approach to designing electronic devices with desired characteristics. In this paper, we design novel van der Waals heterostructures by combing buckled triangular borophene (tr-B) and graphene-like gallium nitride (GaN) monolayers, and tr-B and zinc oxide (ZnO) monolayers together. Using ab initio methods, we theoretically predict the structural, electronic, and electrically conductive properties of tr-B/GaN and tr-B/ZnO van der Waals heterostructures. It is shown that the proposed atomic configurations of tr-B/GaN and tr-B/ZnO heterostructures are energetically stable and are characterized by a gapless band structure in contrast to the semiconductor character of GaN and ZnO monolayers. We find the phenomenon of charge transfer from tr-B to GaN and ZnO monolayers, which predetermines the key role of borophene in the formation of the features of the electronic structure of tr-B/GaN and tr-B/ZnO van der Waals heterostructures. The results of the calculation of the current–voltage (I–V) curves reveal that tr-B/GaN and tr-B/ZnO van der Waals heterostructures are characterized by the phenomenon of current anisotropy: the current along the zigzag edge of the ZnO/GaN monolayers is five times greater than along the armchair edge of these monolayers. Moreover, the heterostructures show good stability of current to temperature change at small voltage. These findings demonstrate that r-B/GaN and tr-B/ZnO vdW heterostructures are promising candidates for creating the element base of nanoelectronic devices, in particular, a conducting channel in field-effect transistors. Full article

Intent sensing—the ability to sense what a user wants to happen—has many potential technological applications. Assistive medical devices, such as prosthetic limbs, could benefit from intent-based control systems, allowing for faster and more intuitive control. The accuracy of intent sensing could be improved by using multiple sensors sensing multiple environments. As users will typically pass through different sensing environments throughout the day, the system should be dynamic, with sensors dropping in and out as required. An intent-sensing algorithm that allows for this cannot rely on training from only a particular combination of sensors. It should allow any (dynamic) combination of sensors to be used. Therefore, the objective of this study is to develop and test a dynamic intent-sensing system under changing conditions. A method has been proposed that treats each sensor individually and combines them using Bayesian sensor fusion. This approach was tested on laboratory data obtained from subjects wearing Inertial Measurement Units and surface electromyography electrodes. The proposed algorithm was then used to classify functional reach activities and compare the performance to an established classifier (k-nearest-neighbours) in cases of simulated sensor dropouts. Results showed that the Bayesian sensor fusion algorithm was less affected as more sensors dropped out, supporting this intent-sensing approach as viable in dynamic real-world scenarios. Full article

The complexity of the user interfaces and the operating modes present in numerous assistive devices, such as intelligent prostheses, influence patients to shed them from their daily living activities. A methodology to evaluate how diverse aspects impact the workload evoked when using an upper-limb bionic prosthesis for unilateral transradial amputees is proposed and thus able to determine how user-friendly an interface is. The evaluation process consists of adapting the same 3D-printed terminal device to the different user-prosthesis-interface schemes to facilitate running the tests and avoid any possible bias. Moreover, a study comparing the results gathered by both limb-impaired and healthy subjects was carried out to contrast the subjective opinions of both types of volunteers and determines if their reactions have a significant discrepancy, as done in several other studies. Full article

We report on a new approach toward a laser-assisted modification of biocompatible polydimethylsiloxane (PDMS) elastomers relevant to the fabrication of stretchable multielectrode arrays (MEAs) devices for neural interfacing technologies. These applications require high-density electrode packaging to provide a high-resolution integrating system for neural stimulation and/or recording. Medical grade PDMS elastomers are highly flexible with low Young’s modulus < 1 MPa, which are similar to soft tissue (nerve, brain, muscles) among the other known biopolymers, and can easily adjust to the soft tissue curvatures. This property ensures tight contact between the electrodes and tissue and promotes intensive development of PDMS-based MEAs interfacing devices in the basic neuroscience, neural prosthetics, and hybrid bionic systems, connecting the human nervous system with electronic or robotic prostheses for restoring and treating neurological diseases. By using the UV harmonics 266 and 355 nm of Nd:YAG laser medical grade PDMS elastomer is modified by ns-laser ablation in water. A new approach of processing is proposed to (i) activate the surface and to obtain tracks with (ii) symmetric U-shaped profiles and (iii) homogeneous microstructure This technology provides miniaturization of the device and successful functionalization by electroless metallization of the tracks with platinum (Pt) without preliminary sensitization by tin (Sn) and chemical activation by palladium (Pd). As a result, platinum black layers with a cauliflower-like structure with low values of sheet resistance between 1 and 8 Ω/sq are obtained. Full article

Historical evidence suggests that prostheses have been used since ancient Egyptian times. Prostheses were usually utilized for function and cosmetic appearances. Nowadays, with the advancement of technology, prostheses such as artificial hands can not only improve functional, but have psychological advantages as well and, therefore, can significantly enhance an individual’s standard of living. Combined with advanced science, a prosthesis is not only a simple mechanical device, but also an aesthetic, engineering and medical marvel. Prosthetic limbs are the best tools to help amputees reintegrate into society. In this article, we discuss the background and advancement of prosthetic hands with their working principles and possible future implications. We also leave with an open question to the readers whether prosthetic hands could ever mimic and replace our biological hands. Full article

The aim of this study was to analyze the effect of the level of amputation and various prosthetic devices on the muscle activation of the sound limb in people with unilateral transfemoral and transtibial amputation. We calculated the global coactivation of 12 muscles using the time-varying multimuscle coactivation function method in 37 subjects with unilateral transfemoral amputation (10, 16, and 11 with mechanical, electronic, and bionic prostheses, respectively), 11 subjects with transtibial amputation, and 22 healthy subjects representing the control group. The results highlighted that people with amputation had a global coactivation temporal profile similar to that of healthy subjects. However, amputation increased the level of the simultaneous activation of many muscles during the loading response and push-off phases of the gait cycle and decreased it in the midstance and swing subphases. This increased coactivation probably plays a role in prosthetic gait asymmetry and energy consumption. Furthermore, people with amputation and wearing electronic prosthesis showed lower global coactivation when compared with people wearing mechanical and bionic prostheses. These findings suggest that the global lower limb coactivation behavior can be a useful tool to analyze the motor control strategies adopted and the ability to adapt to the prosthetic device. Full article