Design Of Prosthetic Hand Research Articles

The Influence of the Abduction Joints of Four Fingers to Grasp: Experimental and Simulated Verification

The thumb is the most important finger of the human hand and has a great influence on grasp manipulations. However, the extent to which joints other than the thumb joints affect the grasp, and thus, which joints should be included in a prosthetic hand, remains an open issue. In this paper, we focus on the metacarpophalangeal joints of the four fingers, except the thumb, which can generate flexion/extension and abduction/adduction motions. The contribution of these joints to grasping was evaluated in four aspects: grasp size, grasp force, grasp quality and grasp success rate. Six subjects participated in experiments with respect to the maximum grasp size and grasp force. The results show that possessing abduction mobility of the metacarpophalangeal joints can increase the grasp size by 4.67 ± 1.93 mm and the grasp force by 5.27 ± 4.25 N. Then, the grasping quality and success rate were tested in a simulation platform and using a robotic hand, respectively. The results show that grasp quality was promoted by 76.7% in the simulated environment with abduction mobility compared to without abduction mobility, whereas the grasp success rate was promoted by 68.3%. We believe that the results of this work can benefit the understanding of hand function and prosthetic hand design.

Gesture Classification of Surface Electromyography Signals Using Machine Learning Algorithms for Hand Prosthetics

The actions of humans executed by their hands play a remarkable part in controlling and handling variety of objects in their daily life activities. The effect of losing or degradation in the functioning of one hand has a greater influence in bringing down the regular activity. Hence the design of prosthetic hands which assists the individuals to enhance their regular activity seems a better remedy in this new era. This paper puts forward a classification framework using machine learning algorithms for classifying hand gesture signals. The surface electromyography (sEMG) dataset acquired for 9 wrist movements of publicly available database are utilized to identify the potential biomarkers for classification and in evaluating the efficacy of the proposed algorithm. The statistical and time domain features of the sEMG signals from 27 intact subjects and 11 trans-radial amputated subjects are extracted and the optimal features are determined implementing the feature selection approach based on correlation factor. The classifiers performance of machine learning algorithms namely support vector machine (SVM), Naïve bayes (NB) and Ensemble classifier are evaluated. The experimental results highlight that the SVM classifier can yield the maximum accuracy movement classification of 99.6% for intact and 97.56% for trans-amputee subjects. The proposed approach offers better accuracy and sensitivity compared to other approaches that have used the sEMG dataset for movement classification.

Design of a lightweight hydraulic myoelectric prosthetic hand

Design of a lightweight hydraulic myoelectric prosthetic hand

A science-driven method for determining morphological parameters of prosthetic hands

The unique morphological bases of human hands, which are distinct from other primates, endow them with excellent grasping and manipulative abilities. However, the lack of understanding of human hand morphology and its parametric features is a major obstacle in the scientific design of prosthetic hands. Existing designs of prosthetic hand morphologies mostly adopt engineering-based methods, which depend on human experience, direct measurements of human hands, or numerical simulation/optimization. This paper explores for the first time a science-driven design method for prosthetic hand morphology, aiming to facilitate the development of prosthetic hands with human-level dexterity. We first use human morphological, movement, and postural data to quantitatively cognize general morphological characteristics of human hands in static, dynamic, functional, and non-functional perspectives. Taking these cognitions as bases, we develop a method able to quickly transfer human morphological parameters to prosthetic hands and endow the prosthetic hands with great grasping/manipulative potential at the same time. We apply this method to the design of an advanced prosthetic hand (called X-hand II) embedded with compact actuating systems. The human-size prosthetic hand can reach wide grasping/manipulative ranges close to those of human hands, replicate various daily grasping types and even execute dexterous in-hand manipulation. This science-driven method may also inspire other artificial limb and bionic robot designs.

Real-time visual and EMG signals recognition to control dexterous prosthetic hand based on deep learning and machine learning

The revolution in prosthetic hands allows the evolution of a new generation of prostheses that increase artificial intelligence to control an adept hand. A suitable gripping and grasping action for different shapes of the objects is currently a challenging task of prosthetic hand design. The most artificial hands are based on electromyography signals. A novel approach has been proposed in this work using deep learning classification method for assorting items into seven gripping patterns based on EMG and image recognition. Hence, this approach conducting two scenarios; The first scenario is recording the EMG signals for five healthy participants for the basic hand movement (cylindrical, tip, spherical, lateral, palmar, and hook). Then three time-domain (standard deviation, mean absolute value, and the principal component analysis) are used to extract the EMG signal features. After that, the SVM is used to find the proper classes and achieve an accuracy that reaches 89%. The second scenario is collecting the 723 RGB images for 24 items and sorting them into seven classes, i.e., cylindrical, tip, spherical, lateral, palmar, hook, and full hand. The GoogLeNet algorithm is used for training based on 144 layers; these layers include the convolutional layers, ReLU activation layers, max-pooling layers, drop-out layers, and a softmax layer. The GoogLeNet achieves high training accuracy reaches 99%. Finally, the system is tested, and the experiments showed that the proposed visual hand based on the myoelectric control method (Vision-EMG) could significantly give recognition accuracy reaches 95%.

Design and Implementation of Upper Prosthetic Controlled remotely by Flexible Sensor Glove

The structuring and the employment for a wireless prosthetic hand adjusted by a flex sensor has been suggested. The prosthetic hand has been constructed for emulating the individual arm motion utilizing a hand mitt. The hand mitt subsists of 5 flexible sensors concerning overseeing the finger motions. The animator’s design utilized to prosthetic arm has servo-motors. The fingers motions are adjusted utilizing wires which operate similarly to the tissue for an individual hand. The prosthetic hand dominates from a faraway position utilizing using remotely unit. Prosthetic hand-design equipped with many sensors; these sensors make the prosthetic hand more intelligent. The first sensor is the force sensor resistance. The second sensor is an infrared temperature sensor. This hand contains many medical applications that can be modified to become wearable for people with missing upper limbs, and the possibility of being used by doctors to perform surgeries remotely within the specified range or much further by connecting it to the internet system in addition to industrial and military applications, which is practical and low-cost. Practically tested to imitate human hand freedom movements and holding with high accuracy.

State-of-the-Art Method in Prosthetic Hand Design: A Review

Human limb amputation can be caused due to congenital disabilities, accidents, and certain diseases. Amputation caused by occupational accidents is a frequent occurrence in developing countries. Meanwhile, amputation caused by certain diseases such as diabetes Miletus is also the leading cause. The need for prosthetic hand is increasing along with the increase in those two factors. Several researchers have developed prosthetic hands with advantages and disadvantages. Research on prosthetic hands, which are useful, low power, and low cost, is still a major issue. Therefore, the purpose of this paper is to provide a review of the various designs of prosthetic hands, specifically on the sensor, control, and actuator systems. This paper collected several references from proceedings and journals related to the design of the prosthetic hand. The results show that the EMG signal is widely used by some researchers in controlling prosthetic hands compared to other sensors, following the force-sensitive resistor (FSR) sensor. To control prosthetic hands, some researchers used a threshold system with a value of 20% of the maximum voluntary contraction (MVC), and several other researchers used a pattern recognition model based on the EMG signal feature. Moreover, In the mechanical part, the open-source prosthetic hand model is more widely used than the fabricate prosthetic hand. This is due to the cost required in the prosthetic hand design is cheaper than a fabricated one. The results of this review are expected to provide a recommendation to researchers in the development of low cost, low power, and practical prosthetic hands.

Electromyography Feature Analysis to Recognize the Hand Motion in a Prosthetic Hand Design

The increasing need for prosthetic hands for people with disabilities is one reason for innovation in the field of prosthetic hands to create the best prosthetic hand technology. In the design of EMG-based prosthetic hands, this is determined by several things, among others, the selection of features. The selection of the right features will determine the accuracy of the prosthetic hand Therefore, the purpose of this study is to analysis the time domain feature to obtain the best feature in classifying the hand motion. The contribution of this work is able to detect 4 movements in real time, namely hand close, flexion, extension, and relax. The Electromyograph signal is tapped using an electromyograph (EMG) dry electrode sensor in which there is a circuit of EMG instrumentation amplifier. Furthermore, the analog EMG signal data is processed through the ADC (Analog to Digital Converter) by using MCP3008 device. EMG signal data is processed in Raspberry Pi. A feature extraction process is applied to reduce data and determine the characteristics of each hand movement. Feature extraction used is MAV (mean absolute value), SSI (sign slope integral), VAR (variance), and RMS (root mean square). From the results of the four-time domain feature, then the best feature extraction is determined using scatter plot and Euclidean distance. The results that have been carried out on ten people with each person doing ten sets of movements (hand close, flexion, extension, relax), showing the best Euclidean distance results, is the RMS feature, with a value of 2608.07. This data is the result of the best feature extraction analysis through the method of calculating the distance of feature extraction data using Euclidean distance. This analysis of time domain feature is expected to be useful for further experiment in machine learning implementation so that it can be obtained an effective prosthetic hand.

Robotic hand design with linear actuators based on Toronto development

In this work, the design of a robotic hand with 7 degrees of freedom is presented that allows greater flexibility, achieving the usual actions performed by a normal hand. The work consists of a prototype designed with linear actuators and myoelectric sensor, following the mechanism of the University of Toronto for the management of functional phalanges. The design, construction description, components and recommendations for the elaboration of a flexible and useful robotic hand for amputee patients with a residual limb for the socket are presented.
 Keywords: Robotic hand, Degree of freedom, Toronto´s Mechanism, lineal actuator.
 References
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Wearable Robotic Glove Design Using Surface-Mounted Actuators.

We propose a novel wearable robotic glove or exo-glove design scalable to the variation of the hand kinematics. While most of the traditional robot hand is driven by rotating the joint directly with a rigid body, our exo-glove deforms a robotic finger's skin and, thus, the hand skeleton joints. Multiple tendons woven on the exo-glove's surface can make multi-DOF finger joint motions. We allocated tendons to mimic a hand's intrinsic and extrinsic muscles. Thus, a robotic hand actuated with the exo-glove can perform natural finger motions, including abduction/adduction and flexion/extension of finger joints. Moreover, additional tendons for the thumb enable power grips and the robotic hand's human-like motion. The proposed design approach places all the actuators on the surface without directly actuating any of the hand skeleton's joint. Therefore, a random hand skeleton can work as a robotic hand by putting the wearable robotic glove on it. Thus, the proposed model provides a high degree of freedom on choosing hand skeletons. We expect the aforementioned biomimetic features of our proposed method will benefit not only traditional robotic hands design but also the design of prosthetic hands and robot power-assisted hand glove.

Design and Finite Element Analysis of Prosthetic Hand Controlled by Wireless Gestures for Differently-abled People

This paper focuses on the design and finite element analysis of the prosthetic hand for differently-able people. The prosthetic hand consists of two sections: one is the transmitting section and another one is the receiving section. The transmitting section consists of a glove embedded with a series of flex sensors connected with a microcontroller and a wi-fi module. The flex sensors are fixed along with each finger which captures and converts the motion of the fingers into analog signals and is transmitted to the receiving section through the wi-fi module. The receiving section consists of the prosthetic hand in which each finger is actuated by the servo motors. The transmitted signals are received by the wi-fi module in the receiver section through the microcontroller and are converted into digital signals. The fingers of the prosthetic hand are actuated by the servo motors corresponding to the received digital signals. The methodology involved in this research is the designing, meshing, and analyzing of a prosthetic hand using the PTC Creo software and then assembling electronic components. The analysis of the prosthetic hand involves the analysis of equivalent stress and total deformation at various regions of the prosthetic hand by selecting steel as a material to fabricate.

Design of an Underactuated Finger Based on a Novel Nine-Bar Mechanism

Abstract Elastic elements are commonly adopted to realize underactuation in the design of human-friendly prosthetic hands. The stiffness of these elastic elements, which is a key factor affecting the grasp performance of the underactuated finger, has not well addressed when considering both the stability and adaptability. In this study, an adaptive anthropomorphic finger that adopted a novel nine-bar mechanism is proposed. This nine-bar mechanism is integrated through a coupled four-bar mechanism and an adaptive seven-bar mechanism. The developed finger based on the nine-bar mechanism is able to improve the grasp stability in the global workspace under an extremely small spring stiffness. A quantitative analysis of the grasp stability was carried out. Comparative experiments on the grasps using the finger with/without adaptability were also performed. The results validated that our finger has a good stability when grasping the objects of different sizes.

Design of a Lightweight Single-Actuator Multi-Grasp Prosthetic Hand With Force Magnification

Abstract Restoring human grasp functions by prosthesis is a long-standing challenge in robotics research. Aiming at prosthetic applications, this paper presents a novel anthropomorphic multi-grasp hand design. The hand is driven by only one motor, and several mechanisms were designed for enhanced functionality. First, a continuum differential mechanism (CDM) was used to generate differential finger motions and to simplify the transmission of the hand. Second, a load adaptive variable transmission (LAVT) was designed to magnify the grasp forces. Moreover, a prismatic clutch is embedded in the hand, to lower the motor's energy consumption. Myoelectric control was implemented using affordable control hardware and sensors. All the above components are integrated in the proposed prosthetic hand, which is an average adult male size and weighs 470 g (including batteries). Experiments, including a preliminary clinical evaluation, were conducted to assess the effectiveness of the hand for prosthetic use. The results show that the hand can perform various grasps and can be a viable option for transradial prosthesis.

Design and Manipulation of Robotic Prosthetic Hand

Design and Manipulation of Robotic Prosthetic Hand

Development of an Anthropomorphic Prosthetic Hand with Underactuated Mechanism

An anthropomorphic prosthetic hand for wrist or forearm amputees is developed herein. The prosthetic hand was designed with an underactuated mechanism, which makes self-adaptive grasping possible, as well as natural motions such as flexion and extension. The finger and thumb modules were designed with four degrees of freedom by motions of the distal interphalangeal, proximal interphalangeal, and metacarpophalangeal joints. In this research, we pursued several novel trials in prosthetic hand design. By using two four-bar linkages composed of a combination of linkages and gears for coupling joints at each finger, it was possible to make a compact design, and the linkage has advantages such as accurate positioning, uniform power transmission, and high payload. Also, by using constant-velocity joints, torque is transferred to finger modules regardless of adduction/abduction motions. In addition, adduction/abduction and self-adaptive grasping motions are passively realized using torsional springs. The developed prosthetic hand was fabricated with a weight of 475 g and a human hand size of 175 mm. Experiments with diverse objects showed its good functionality.

Design and Development of Prosthetic Hand Controlled by Wireless Gestures for Differently Able People

This paper focuses on the design and development of Prosthetic hand to help differently-able people who lost their hands due to accidents and diseases. Our research purpose is to develop a master and slave robotic system that will be a substitute for the lost hand to do the day-to-day activities of a person. The person has to wear smart gloves in the hand to do gesture action. The gloves will able to transfer the hand gestures of differently-able people to react suitably and move the hand gripper (which contains spring coils similar to bones in human hand) based on the data from smart gloves. The methodology behind this research is that the analog signals produced in the flex sensor due to the gesture action are transferred to the servo motors to do a similar action in the 3D printed prosthetic hand through the Wi-Fi module. This research project involves two Arduino microcontrollers for communicating and controlling applications in both master and slave sections. A number of flex sensors are placed in the glove to get readings of the motion of human fingers and it is transmitted through the Wi-Fi module by using the Arduino microcontroller. The transmitted signals are received by the Wi-Fi module in the slave section through the Arduino microcontroller and further uses this signal to control various servo motors and it controls the slave robotic hand by using the ropes attached between the servo motor and 3D printed parts. Not only for differently-able people, but the enlarged model of this project can also be used in industries to handle hazardous, harmful, high temperatures and harmful things.

Design and control of a low cost myoelectric prosthetic hand

This paper presents a prototype prosthetic hand manufactured using 3D printing techniques. The device is capable of performing four different grip patterns with an average response time of less than 300 ms, controlled wirelessly by the electromyography (EMG) signals within the user's arm through a Myo armband sensor package. Evaluation of current devices concluded that there were very limited options for low cost but functional artificial hands; the prosthetic presented in this paper amounts to a manufacturing cost of £146 (not inclusive of the Myo armband) and retains the functionality required to be of benefit to the user. Compared to the devices researched, this cost is extremely low and presents a basis for further development. The major achievement of this device is that the electronics (minus the wireless sensor package) are entirely encapsulated within the device, not requiring an additional forearm piece to house components and reducing the weight significantly. Areas for future development of the prototype are highlighted, such as the addition of sensors and haptic feedback, increasing the robustness through the use of more reliable materials and improving the capability of the device through additional grip patterns.

Towards Including End-Users in the Design of Prosthetic Hands: Ethical Analysis of a Survey of Australians with Upper-Limb Difference.

Advances in prosthetic design should benefit people with limb difference. But empirical evidence demonstrates a lack of uptake of prosthetics among those with limb difference, including of advanced designs. Non-use is often framed as a problem of prosthetic design or a user's response to prosthetics. Few studies investigate user experience and preferences, and those that do tend to address satisfaction or dissatisfaction with functional aspects of particular designs. This results in limited data to improve designs and, we argue, this is pragmatically and ethically problematic. This paper presents results of a survey we conducted in 2017 with people with upper limb difference in Australia. The survey sought to further knowledge about preferences surrounding prosthetics and understanding of how preferences relate to user experience, perspective, and context. Survey responses demonstrated variety in the uptake, use and type of prosthetic-and that use of, preferences about, and impacts of prosthetics rely not just on design factors but on various contextual factors bearing on identity and social understandings of disability and prosthetic use. From these results, we argue that non-use of prosthetics could be usefully reframed as an issue of understanding how prosthetics can best support users' autonomy. This supports the claim that there is a need to incorporate user engagement into design processes for prosthetic limbs, though further work is needed on methods for doing so.

Design and Development of Low cost Prosthetic Hand controlled by Myoelectric Signal

Design and Development of Low cost Prosthetic Hand controlled by Myoelectric Signal

Electronic Taste and Smell: The Case for Performance Standards [Point of View

International standards have proven invaluable in the technology sector for developing functional and reliable products for the global marketplace. Standards provide performance criteria that technical engineers can use to design products to optimize the reliability and safety of new products. For example, standards have played a decisive role in the development of products associated with the senses of vision, audition, and touch. The design of products that perform automated “visual” tasks including unmanned vehicles, autonomous robots, optical tracking systems, and highway traffic monitoring devices has relied heavily on standards as well as technical regulations. Likewise, standards related to the sense of hearing have played a major role in the development of devices and systems that assist or mimic “audition” including cochlear implants, hearing aids, and voice and speech recognition systems. Standards related to the sense of touch have been seminal in the design of robotic arms and prosthetic hands. Unlike the senses of vision, audition, and touch, there are, however, no formal standards for electronic devices called e-noses and e-tongues that are designed to detect and evaluate odors and tastes. The purpose of this opinion piece is to give a brief background on the senses of smell and taste, to describe why standards for e-noses and e-tongues are needed, and to call for IEEE volunteers to participate and collaborate on technical standards development to ensure that machine olfaction and taste provide reliable and reproducible results that are comparable to human smell and taste.