Prosthetic Hand

Introduction: Current terminal devices for upper limb amputees are available in a variety of hooks and hand-shaped devices with few articulating joints. While much has changed with external powered prostheses and multi-articulating hands, there have been little new developments with body-powered prosthetic hands, despite a significant unmet need for these devices. 3D printing has revolutionized the development of highly customizable products and designs. The application of 3D printing may add significant opportunities for the creation of new body-powered prosthetic hands that are customized specifically for the patient.

One of the most common problem that disabled persons with amputation in upper limb they couldn't buy a commercial prosthetic hand because it very expansive and up to thousands of dollars, Researchers and developer aspire to manufacture an prosthetic hand that performs the same functions and activates of natural hand. This paper includes the design and development of a low-cost prosthetic hand (less than a1000$) that capable of wearing from the persons who has amputation in the hand, this design represent a hand with five finger capable of movement and gripping the object, rotatable wrist and socket connect with amputation body capable to up and down the forearm. The design of this prosthetic hand possess 18 degree of freedom (DOF), 3DOFfor each finger except the thumb has 4DOF, 2DOFfor wrist and 2DOF for socket. The design prosthetic hand work by under actuated system 7 servo motors with tendon to move the fingers material (PLA). The design element and tesht in solid work to avoid overlapping between fingers and then after manufacture the design try it in real life to movement and gripping the object.

 Abstract— In view of having a precarious public health system, the Honduran population is with the needed to find alternatives to meet their health needs, this is particularly important for people with physical disabilities. For the San Felipe Public Hospital, which is the center of the country's largest prosthesis it is impossible to meet the demand, with about 1,800 people per year requiring a prosthetic limb, only in this center. In addition to high demand and shortage of materials, the center is dedicated exclusively to the production of above and below knee prosthesis, leaving aside prosthetic patients whose requirements are different. This is where the possibility of implementing prostheses made using 3D printers, which not only alleviate the arrears of prosthesis, but also reduce the price and time of creating them. Using this process the creation of hand prostheses becomes a viable possibility. This article aims to explain the procedure of this process and expose the advantages thereof, with particular emphasis on the feasibility and accessibility of hand prostheses in Honduras.

In this study robotic hands and fingers' materials are investigated from past to present and a sponge robotic hand is designed for biomedical applications. Emergence and necessity of soft robotic technology are explained and description of soft robot is made. Because of the importance of hand in a person's body, researchers have dealt with robotic hand prostheses for many centuries and developed many hand types. To mimic the best for the human limbs, softness of the hand is one of the important features. Recent studies are summarized in a table. In the table you can see materials that are used in robotic hand and fingers; they are classified as soft and rigid with their years. In literature sponge was found as the most suitable material for the fingers, but there is no study about a sponge hand. This study aims to fill this gap in literature. In this paper manufacturing of a Sponge Robotic Hand's production parameters and stages are explained clearly. Finally advantages of sponge robotic hand and future studies about sponge robotic hand are mentioned.

It has been reported that over 3 million individuals live with upper limb amputation worldwide. Losing a hand drastically reduces the individual's quality of life. Fortunately, there are several prosthetic solutions available in the market that try to restore some of the missing hand's functions and characteristics. This paper presents a review on three of the main components of a typical transradial myoelectric prosthesis that can be found in the market. The goal was to provide the reader with an overview of commercially available anthropomorphic myoelectric prosthetic hands with high degrees of freedom, pattern-recognition-based microcontrollers and sEMG sensors used for prosthetic control.

— A lot of research is happening in medical field in the area of prosthesis with a aim to reduce the cost and at the same time, the artificial limb being effective. The current work concentrates on the area of prosthetic hand. Most of the prosthetic arms currently available are motor driven and costly. There are non-powered prosthetic hand also but involve the use of elastic band on solid fingers which make the arms heavy. The current work is aimed at overcoming these difficulties by the use of EPE foamed fingers which are driven actuated by a tendon by the gesture of palm while the foam provides the necessary spring back. CAD models are prepared using proe while 3D printing is used for fabricating most of the arm. EPE is used as foam material while PLA and Acrylic are used for outer structure. Keywords— 3D printing, EPE foamed finger, PLA, prosthetic hand, tendon driven.

This paper described the development of prosthetic hand and its control system. Initially the research start by reviewing the existing prosthetic design. After investigating of those designs, a better design approach has been presented in this work. The objective of this research is to design and develop the prosthetic hand control system in order to provide solutions for the amputee who lose their hand. This project describes an under actuated artificial hand for functional replacement of the natural hand. The hand comprised of an actuator embedded in an under actuated mechanical system. After the prosthetic hand hardware completed the fabrication process, it is modelled using system identification method. An input data (voltage) and output data (position) is collected using MyRIO. Then, the PID controller is designed based on Zigler Nichols method. Finally, the prosthetic control system is verified via simulation. It is expected that the PID controller could perform well for the prosthetic system.

In the absence of the upper limb, prosthetic devices attempt to assist the user in performing the basic activities of daily life, such as holding and manipulating objects. However, such equipment has high costs, which makes it difficult for the users to acquire it. In this context, alternative solutions for prosthesis began to emerge in order to reduce costs as well as to improve usability. With the recent technological advancements, areas such as robotics and electronics tend to become more accessible. The current study reports on the process of producing a transradial myoelectric bionic prosthesis and to analyze the potential of using rapid prototyping and low cost technologies. The results present the improvement in the design of upper limb prosthesis, highlighting the potential contributions of a low cost myoelectric prosthesis in terms of functionality and aesthetics.

In this study a method has been introduced to map the features extracted from the recorded electromyogram signals from the forearm and the force generated by the fingers. In order to simultaneously record of sEMG signals and the force produced by fingers, 9 requested movements of fingers conducted by 10 healthy people. Estimation was done for 6 degrees of freedom (DoF) and generalized regression neural network (GRNN) was selected for system training. The optimal parameters, including the length of the time windows, the parameters of the neural network, and the characteristics of the sEMG signal were calculated to improve the performance of the estimate. The performance was obtained based on R criterion. The Total value of R for 6 DoF was 92.8±5.2% that obtained by greedy looking system parameters in all the subjects. The result shows that proposed method can be significant in simultaneous myoelectric control.

The study of human hand morphology reveals that developing an artificial hand with the capabilities of human hand is an extremely challenging task. This paper presents the development of a robotic prosthetic hand focusing on the improvement of a tendon driven mechanism towards a biomimetic prosthetic hand. The design of this prosthesis hand is geared towards achieving high level of dexterity and anthropomorphism by means of a new hybrid mechanism that integrates a miniature motor driven actuation mechanism, a Shape Memory Alloy actuated mechanism and a passive mechanical linkage. The synergy of these actuators enables the flexion-extension movement at each of the finger joints within a limited size, shape and weight constraints. Tactile sensors are integrated on the finger tips and the finger phalanges area. This prosthesis hand is developed with an exact size ratio that mimics a biological hand. Its behavior resembles the human counterpart in terms of working envelope, speed and to...

Speech recognition is one of the key topics in artificial intelligence, as it is one of the most common forms of communication in humans. Researchers have developed many speech-controlled prosthetic hands in the past decades, utilizing conventional speech recognition systems that use a combination of neural network and hidden Markov model. Recent advancements in general-purpose graphics processing units (GPGPUs) enable intelligent devices to run deep neural networks in real-time. Thus, state-of-the-art speech recognition systems have rapidly shifted from the paradigm of composite subsystems optimization to the paradigm of end-to-end optimization. However, a low-power embedded GPGPU cannot run these speech recognition systems in real-time. In this paper, we show the development of deep convolutional neural networks (CNN) for speech control of prosthetic hands that run in real-time on a NVIDIA Jetson TX2 developer kit. First, the device captures and converts speech into 2D features (like spectrogram). The CNN receives the 2D features and classifies the hand gestures. Finally, the hand gesture classes are sent to the prosthetic hand motion control system. The whole system is written in Python with Keras, a deep learning library that has a TensorFlow backend. Our experiments on the CNN demonstrate the 91% accuracy and 2ms running time of hand gestures (text output) from speech commands, which can be used to control the prosthetic hands in real-time.