Prosthetic Applications Research Articles

Bidirectional and Stretchable Piezoresistive Sensors Enabled by Multimaterial 3D Printing of Carbon Nanotube/Thermoplastic Polyurethane Nanocomposites.

Fabricating complex sensor platforms is still a challenge because conventional sensors are discrete, directional, and often not integrated within the system at the material level. Here, we report a facile method to fabricate bidirectional strain sensors through the integration of multiwalled carbon nanotubes (MWCNT) and multimaterial additive manufacturing. Thermoplastic polyurethane (TPU)/MWCNT filaments were first made using a two-step extrusion process. TPU as the platform and TPU/MWCNT as the conducting traces were then 3D printed in tandem using multimaterial fused filament fabrication to generate uniaxial and biaxial sensors with several conductive pattern designs. The sensors were subjected to a series of cyclic strain loads. The results revealed excellent piezoresistive responses with cyclic repeatability in both the axial and transverse directions and in response to strains as high as 50%. It was shown that the directional sensitivity could be tailored by the type of pattern design. A wearable glove, with built-in sensors, capable of measuring finger flexure was also successfully demonstrated where the sensors are an integral part of the system. These sensors have potential applications in wearable electronics, soft robotics, and prosthetics, where complex design, multi-directionality, embedding, and customizability are demanded.

Feature Selection Based on Binary Tree Growth Algorithm for the Classification of Myoelectric Signals

Electromyography (EMG) has been widely used in rehabilitation and myoelectric prosthetic applications. However, a recent increment in the number of EMG features has led to a high dimensional feature vector. This in turn will degrade the classification performance and increase the complexity of the recognition system. In this paper, we have proposed two new feature selection methods based on a tree growth algorithm (TGA) for EMG signals classification. In the first approach, two transfer functions are implemented to convert the continuous TGA into a binary version. For the second approach, the swap, crossover, and mutation operators are introduced in a modified binary tree growth algorithm for enhancing the exploitation and exploration behaviors. In this study, short time Fourier transform (STFT) is employed to transform the EMG signals into time-frequency representation. The features are then extracted from the STFT coefficient and form a feature vector. Afterward, the proposed feature selection methods are applied to evaluate the best feature subset from a large available feature set. The experimental results show the superiority of MBTGA not only in terms of feature reduction, but also the classification performance.

Study the Mechanical Properties of Polymeric Blends (SR/PMMA) Using for Maxillofacial Prosthesis Application

A number of prosthetic materials, it may be used to replace facial parts of maxillofacial that lost through disease or trauma. The silicone rubbers it is considered are the best materials in this area. So that, the aim of this research is to study the effect of addition of PMMA material on the mechanical properties of blends SR/PMMA at different loading level (5%, 10%, 15% and 20%) of PMMA to silicone rubber. FTIR test and some mechanical properties such as tensile strength, elastic modulus, elongation percentage, hardness, compression strength and roughness were done on the all prepared samples, which are used for maxillofacial prostheses applications. The results showed that the optimum percent of PMMA is 10% that has ideal characteristic. So, this sample may be a promising material to achieve the properties required for maxillofacial prosthetic applications.

Network Brain-Computer Interface (nBCI): An Alternative Approach for Cognitive Prosthetics.

Brain computer interfaces (BCIs) have been applied to sensorimotor systems for many years. However, BCI technology has broad potential beyond sensorimotor systems. The emerging field of cognitive prosthetics, for example, promises to improve learning and memory for patients with cognitive impairment. Unfortunately, our understanding of the neural mechanisms underlying these cognitive processes remains limited in part due to the extensive individual variability in neural coding and circuit function. As a consequence, the development of methods to ascertain optimal control signals for cognitive decoding and restoration remains an active area of inquiry. To advance the field, robust tools are required to quantify time-varying and task-dependent brain states predictive of cognitive performance. Here, we suggest that network science is a natural language in which to formulate and apply such tools. In support of our argument, we offer a simple demonstration of the feasibility of a network approach to BCI control signals, which we refer to as network BCI (nBCI). Finally, in a single subject example, we show that nBCI can reliably predict online cognitive performance and is superior to certain common spectral approaches currently used in BCIs. Our review of the literature and preliminary findings support the notion that nBCI could provide a powerful approach for future applications in cognitive prosthetics.

Fabrication and Characterization of Bioglass

Glasses are common in use now days. These are used in different applications like domestic, automobile, telecommunication etc. The glasses are very useful materials because of their impressive properties. Few years back a new generation of glasses were developed i.e. bioactive glasses and bioactive glass ceramics. The glasses are used for bone grafting now-a-days because of their impressive bioactive properties. These glasses have tendency to form bonds with the living tissue organs. The future of these glasses will be bright in dental, orthopedics and prosthetic applications. In the present work borosilicate glasses of different compositions have been studied. The different elements were added with appropriate mol% to compose a new bioglass composition. The samples were prepared by melt quench route. The samples were immersed for 21 days in SBF. The samples were characterized before and after immersion in SBF by different techniques. The XRD technique was done to confirm the amorphous nature of glass before immersion and after immersion. The SEM and EDX were done to check the changes on the surface after immersion. The sample S1 has better biocompatibility results than S2 andS3. The formation of apatite on the glass samples were confirmed by all techniques mentioned above.

Comparison of Surface Electromyogram Signal for Prosthetic Applications

Comparison of Surface Electromyogram Signal for Prosthetic Applications

CoCr Based Alloys in Current Dental Prosthetic Applications

CoCr alloys are traditionally manufactured by casting, but nowadays alternatives such as CAD/CAM milling or 3D Printing Technologies (Direct metal laser sintering (DMLS), Selective laser sintering (SLS), Selective laser melting (SLM), Electron beam melting (EBM)) are available. CoCr blanks to be milled in the green body state (unsintered metal powder held together by a binder) and then densely sintered try to overcome the hardness of the alloy and to ease the milling process.The aim of this paper is to compare the quality of prosthetic pieces manufactured by CAD/CAM milling, CAD/CAM sintering and Selective laser sintering.Because the chemical composition of the CoCr alloys used is comparable, differences in quality of the prosthetic pieces are the result of the manufacturing technology. In terms of structure and corrosion resistance, the CAD/CAM milling sample proved to be the best choice and the SLS sample the worst.

Long-term stability of neural signals from microwire arrays implanted in common marmoset motor cortex and striatum

Current neuroprosthetics rely on stable, high quality recordings from chronically implanted microelectrode arrays (MEAs) in neural tissue. While chronic electrophysiological recordings and electrode failure modes have been reported from rodent and larger non-human primate (NHP) models, chronic recordings from the marmoset model have not been previously described. The common marmoset is a New World primate that is easier to breed and handle compared to larger NHPs and has a similarly organized brain, making it a potentially useful smaller NHP model for neuroscience studies. This study reports recording stability and signal quality of MEAs chronically implanted in behaving marmosets. Six adult male marmosets, trained for reaching tasks, were implanted with either a 16-channel tungsten microwire array (five animals) or a Pt-Ir floating MEA (one animal) in the hand-arm region of the primary motor cortex (M1) and another MEA in the striatum targeting the nucleus accumbens (NAcc). Signal stability and quality was quantified as a function of array yield (active electrodes that recorded action potentials), neuronal yield (isolated single units during a recording session), and signal-to-noise ratio (SNR). Out of 11 implanted MEAs, nine provided functional recordings for at least three months, with two arrays functional for 10 months. In general, implants had high yield, which remained stable for up to several months. However, mechanical failure attributed to MEA connector was the most common failure mode. In the longest implants, signal degradation occurred, which was characterized by gradual decline in array yield, reduced number of isolated single units, and changes in waveform shape of action potentials. This work demonstrates the feasibility of long-term recordings from MEAs implanted in cortical and deep brain structures in the marmoset model. The ability to chronically record cortical signals for neural prosthetics applications in the common marmoset extends the potential of this model in neural interface research.

A mechanical hand for prosthetic applications: multibody model and contact simulation

The dynamical behavior study of a mechanical hand is a fundamental issue to verify its possible application as a prosthetic hand. Simulation approaches are widely used to predict the dynamics of mechanical components. In the context of mechanical hands, the multibody model represents a useful tool to predict the finger dynamics and therefore the phalanx rotations before the prototyping. The phalanx rotations drive the finger closure sequence and, consequently, influence the grasping ability of the whole mechanical hand. This article discusses the main theoretical aspects dealing with the design of a mechanical hand for prosthetic application and the solutions offered by multiple simulation approaches.

Comparison of Lichtenstein Repair and Mesh Plug Repair Methods in The Treatment of Indirect Inguinal Hernia.

Objective: The lifetime risk to develop an inguinal hernia is 27%-43% for men and 3%-6% for women. Methods of hernia repair currently involve prosthetic mesh applications. The aim of this study is to compare the Lichtenstein repair and Mesh-plug repair methods in the surgical treatment of indirect inguinal hernias and to identify which of these two techniques is superior regarding its conferred advantages.Materials and Methods: In this study, a total of 102 patients who were diagnosed with indirect inguinal hernia between the years 2014 and 2015 without a previous operation were analyzed. Patients undergoing Lichtenstein repair and Mesh-plug repair were compared, especially during operation time, hospital stay, postoperative pain and other aspects.Results: The mean age of patients was 28.7 years (19-73). The mean duration of operations and hospitalizations was significantly shorter in patients who had undergone mesh-plug repair. Inguinal pain in the operation area on postoperative day one, two weeks and six months was significantly less in patients who had undergone mesh-plug repair. Patients were followed-up for two years.Conclusion: We concluded that mesh-plug repair was superior to Lichtenstein repair regarding postoperative pain, quality of life of the patient, shorter duration of operation, and duration of hospital stay although the two methods were similar regarding both recurrence and complication rates. Considering this information, we suggest that mesh-plug repair can be used safely for the treatment of indirect inguinal hernias.

Early-onset Scoliosis: Contemporary Decision-making and Treatment Options.

Early-onset scoliosis (EOS) describes a wide array of diagnoses and deformities exposed to growth. This potentially life-threatening condition is still 1 of the biggest challenges in pediatric orthopaedics. The enlightenment of Bob Campbell's thoracic insufficiency syndrome concept and the negative impact of the earlier short and straight spine fusion approach on respiratory function and survival have fueled the evolution of EOS care. Despite all the progress made, growth-friendly spine surgery remains to be a burden to patients and caregivers. Even down-sized implants and remote-controlled noninvasive rod expansions do not omit unexpected returns to the operating room: failures of foundations, rod breakage, difficulties to keep the sagittal balance, progressive transverse plane deformities, stiffening, and the need for final instrumented fusion are still common. However, past experience and the current multitude of surgical strategies and implants have sharpened the decision-making process, patients with thoracic insufficiency syndrome require earliest possible vertical expandable prosthetic titanium ribs application. Flexible deformities below 60 degrees, with normal spinal anatomy and without thoracic involvement, benefit from serial Mehta casting which revived as a long available but not-used strategy. In case of progression, standard double growing rods or-if available, affordable, and applicable-magnetically controlled motorized rods provide deformity control and growth promotion. Shilla growth-guiding technique is a less costly alternative. Its lack of stiff lengthening boxes or actuators may be beneficial in difficult deformities. Anterior convex flexible tethering promises benefits of sparing the trunk muscles and keeping mobility. However, this step towards a true nonfusion concept has yet to stand the test of broad clinical application.

A flexible sensing system capable of sensations imitation and motion monitoring with reliable encapsulation

In this work, a flexible multiple sensor system is demonstrated for robotic and prosthetic applications. The system consists of two strain sensors, a microheater, a temperature sensor and a pressure sensor for imitating different sensations of human skin. The strain sensors are designed for monitoring the movement and bending angle of the fingers; while the temperature and pressure sensors are used to collect the information of temperature, grabbing force and stiffness of the objects being grabbed, respectively. Combination of the temperature sensor and microheater mimics the temperature sensation of human skin, allowing measuring temperature and apparent temperature of the objects grasped. Liquid metal with reliable polymer encapsulation is innovatively used to interface the sensor system with peripheral circuits. This allows reliable signal transmission and processing for the flexible sensor system for strains up to 40%. This multiple sensor system is capable of precisely monitoring movement of fingers, providing different sensations and judging some characteristics of objects for a robot hand.

Optimal design of an MR damper valve for prosthetic knee application

In this work, a magnetorheological (MR) damper valve is designed with the primary objective of controlling swing-phase damping in an above-knee prosthesis. Initially, a swing phase model of the desired single axis knee incorporating MR damper was modelled. The control parameters that govern damping force and displacement of the damper were identified and optimized to enable the prosthetic knee to produce near normal swing phase trajectory for ground walking as obtained from experimental data. Then, the MR damper valve is optimally designed by selecting typical performance indices of the damper for the intended application. A multi-objective optimization problem is formulated where the MR damper valve is constrained in a desired cylindrical volume defined by its radius and height. Effects of the geometrical design variables of the valve are analytically investigated by mapping finite element analysis (FEA) numerical responses with response surface method (RSM). The results show that the MR damper with designed damper valve enables the prosthetic knee to achieve near to normal swing phase trajectory, and compare to the existed MR damper, up to 71 % reduction by weight has been achieved.

Biomaterial characterization of off-the-shelf decellularized porcine pericardial tissue for use in prosthetic valvular applications.

Fixed pericardial tissue is commonly used for commercially available xenograft valve implants, and has proven durability, but lacks the capability to remodel and grow. Decellularized porcine pericardial tissue has the promise to outperform fixed tissue and remodel, but the decellularization process has been shown to damage the collagen structure and reduce mechanical integrity of the tissue. Therefore, a comparison of uniaxial tensile properties was performed on decellularized, decellularized‐sterilized, fixed, and native porcine pericardial tissue versus native valve leaflet cusps. The results of non‐parametric analysis showed statistically significant differences (p < .05) between the stiffness of decellularized versus native pericardium and native cusps as well as fixed tissue, respectively; however, decellularized tissue showed large increases in elastic properties. Porosity testing of the tissues showed no statistical difference between decellularized and decell‐sterilized tissue compared with native cusps (p > .05). Scanning electron microscopy confirmed that valvular endothelial and interstitial cells colonized the decellularized pericardial surface when seeded and grown for 30 days in static culture. Collagen assays and transmission electron microscopy analysis showed limited reductions in collagen with processing; yet glycosaminoglycan assays showed great reductions in the processed pericardium relative to native cusps. Decellularized pericardium had comparatively low mechanical properties among the groups studied; yet the stiffness was comparatively similar to the native cusps and demonstrated a lack of cytotoxicity. Suture retention, accelerated wear, and hydrodynamic testing of prototype decellularized and decell‐sterilized valves showed positive functionality. Sterilized tissue could mimic valvular mechanical environment in vitro, therefore making it a viable potential candidate for off‐the‐shelf tissue‐engineered valvular applications.

Skin‐Inspired Low‐Grade Heat Energy Harvesting Using Directed Ionic Flow through Conical Nanochannels

AbstractLow‐grade heat energies are ubiquitous, and most of these energies are untapped as heated river water or seawater. Therefore, it is meaningful and valuable to extract the stored energies in the context of the energy crisis by using a simple device with low‐cost effectiveness. Here, a simple thermoelectric conversion system is shown using directed ionic flow through the biomimetic smart nanochannels, inspired by the human skin. The obtained power density of the nanodevice can ideally be 88.8 W m−2 with a membrane temperature gradient (ΔT) of 40 °C. As proof of concept, it is demonstrated that the principle can be introduced into simple and portable prototypes to harvest low‐grade heat. Such a thermoelectric conversion apparatus provides a new venue for low‐grade heat harvesting. In addition, this self‐powered system may extend the electronic skin field and find applications in skin prosthetics.

Acquiring and processing of female EEG signals of various wrist movements for neuro prosthetic applications

Human brain contain neurons which generate electrical signals, this can be recorded through electro encephalograph(EEG). Sensory motor cortices are responsible for motor activity i.e., various body movements, among which wrist movement reveals frequency change in Alpha &amp; Beta bands of EEG signal. The aim of this approach is to calculate frequency changes responsible for various wrist movements such as flexion, extension, clockwise rotation and anticlockwise rotation, pronation and supination of female in both eyes open and eyes close conditions using FFT, wavelet transform classifier, where the largest set of EEG data is reduced to dimensions and the spectral frequencies for particular wrist movements are classified and the statistical analysis is done of various trials for both eyes open and eyes close conditions in both time domain and frequency domain and the mean and standard deviation of various trials will be compared for eyes open and eyes close condition in both time domain and frequency domain and these values can be implemented for neuro prosthetic applications.

Measuring Dynamic Shear Force and Vibration With a Bioinspired Tactile Sensor Skin

There is a need to measure dynamic tactile information to enhance robotic hand performance during haptic exploration and object manipulation. Here, we report on the dynamic characterization of a flexible, bioinspired, and resistive microfluidic shear force sensor skin. When the skin is subjected to shear force, one side of the skin experiences tension while the other side experiences compression, both of which are measured by liquid metal strain gauges embedded in polydimethylsiloxane. The sensor can measure dynamic shear forces during stepwise unloading, incipient slip, and controlled vibration tests. The sensor can quantify vibration up to 800 Hz with an average minimum displacement of 0.43 μm, which is equivalent to or better than human fingertips. We demonstrate the utility of the sensor skin by performing experiments with a robotic hand and arm. The shear sensing skin senses tactile events while a robotic arm performs several manipulation tasks including pick and place, drop, and handover. The skin is robust when used on a robot manipulator and shows promise in providing rich and dynamic tactile information that is beneficial to robotic and prosthetic applications.

Portable EMG Data Acquisition Module for Upper Limb Prosthesis Application

Electromyography (EMG) signals are gaining popularity to develop the prosthetics. In this paper, an efficient multi-channel EMG signal acquisition system has been proposed for upper limb prosthetic application. Various arm exercises have been performed to obtain EMG signals from five different arm muscles for the validation of developed hardware. The muscle’s position has been selected by palpation method. Furthermore, the classification algorithms have been examined for seven different activities. Total 29 subjects have been chosen (25 intact and four Amputees) to acquire the EMG data by these activities. To classify the recorded EMG data set, nine time domain and seven frequency domain features have been extracted. A comparative analysis of different classifiers is presented for different muscle position of electrodes. The signal processing and classification algorithms have been processed in MATLAB 2016a. The accuracy of classification ranges for different classification algorithms from 57.69% to 99.92% for all subjects.

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic, prosthetic, and industrial applications.

Development of force plate for prosthetic applications interfacing with internet of things

Force Plate is a measuring instrument which is used to calibrate the ground reaction force in gait cycle analysis of a subject (human or animal). Force plates are used to examine the lower limb kinematics for the applications of prosthetics, sports etc. In this study, a prototype of force plate is developed indigenously in an economical manner. It comprises of two metallic frames with a load cell (force transducer) mounted between them to produce an electrical signal as output, that is proportional to the amount of force applied on the surface of force plate. This prototype has a maximum load capacity of 3000N. The design of the force plate system along with the ground reaction force analysis and results are discussed below.