Next-Generation Prosthetic Hand: from Biomimetic to Biorealistic

Integrating a prosthetic hand to amputees with seamless neural compatibility presents a grand challenge to neuroscientists and neural engineers for more than half century. Mimicking anatomical structure or appearance of human hand does not lead to improved neural connectivity to the sensorimotor system of amputees. The functions of modern prosthetic hands do not match the dexterity of human hand due primarily to lack of sensory awareness and compliant actuation. Lately, progress in restoring sensory feedback has marked a significant step forward in improving neural continuity of sensory information from prosthetic hands to amputees. However, little effort has been made to replicate the compliant property of biological muscle when actuating prosthetic hands. Furthermore, a full-fledged biorealistic approach to designing prosthetic hands has not been contemplated in neuroprosthetic research. In this perspective article, we advance a novel view that a prosthetic hand can be integrated harmoniously with amputees only if neural compatibility to the sensorimotor system is achieved. Our ongoing research supports that the next-generation prosthetic hand must incorporate biologically realistic actuation, sensing, and reflex functions in order to fully attain neural compatibility.

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Modeling and Analysis of a Visual Feedback System to Support Efficient Object Grasping of an EMG-Controlled Prosthetic Hand

Current Directions in Biomedical Engineering ◽

10.1515/cdbme-2019-0053 ◽

2019 ◽

Vol 5 (1) ◽

pp. 207-210

Author(s):

Tolgay Kara ◽

Ahmad Soliman Masri

Keyword(s):

Visual Feedback ◽

Low Cost ◽

Feedback System ◽

Hand Gesture ◽

Human Hand ◽

Prosthetic Hand ◽

Modeling And Analysis ◽

Prosthetic Hands ◽

Prosthetic Limbs ◽

Computer Environment

AbstractMillions of people around the world have lost their upper limbs mainly due to accidents and wars. Recently in the Middle East, the demand for prosthetic limbs has increased dramatically due to ongoing wars in the region. Commercially available prosthetic limbs are expensive while the most economical method available for controlling prosthetic limbs is the Electromyography (EMG). Researchers on EMG-controlled prosthetic limbs are facing several challenges, which include efficiency problems in terms of functionality especially in prosthetic hands. A major issue that needs to be solved is the fact that currently available low-cost EMG-controlled prosthetic hands cannot enable the user to grasp various types of objects in various shapes, and cannot provide the efficient use of the object by deciding the necessary hand gesture. In this paper, a computer vision-based mechanism is proposed with the purpose of detecting and recognizing objects and applying optimal hand gesture through visual feedback. The objects are classified into groups and the optimal hand gesture to grasp and use the targeted object that is most efficient for the user is implemented. A simulation model of the human hand kinematics is developed for simulation tests to reveal the efficacy of the proposed method. 80 different types of objects are detected, recognized, and classified for simulation tests, which can be realized by using two electrodes supplying the input to perform the action. Simulation results reveal the performance of proposed EMG-controlled prosthetic hand in maintaining optimal hand gestures in computer environment. Results are promising to help disabled people handle and use objects more efficiently without higher costs.

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A Multi-DoF Prosthetic Hand Finger Joint Controller for Wearable sEMG Sensors by Nonlinear Autoregressive Exogenous Model

Sensors ◽

10.3390/s21082576 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2576

Author(s):

Zhaolong Gao ◽

Rongyu Tang ◽

Qiang Huang ◽

Jiping He

Keyword(s):

Sensory Information ◽

Finger Joint ◽

Prosthetic Hand ◽

Prosthetic Hands ◽

Mobility Function ◽

Proposed Model ◽

Marquardt Algorithm ◽

The Time Domain ◽

Nonlinear Autoregressive ◽

Regression Correlation

The loss of mobility function and sensory information from the arm, hand, and fingertips hampers the activities of daily living (ADL) of patients. A modern bionic prosthetic hand can compensate for the lost functions and realize multiple degree of freedom (DoF) movements. However, the commercially available prosthetic hands usually have limited DoFs due to limited sensors and lack of stable classification algorithms. This study aimed to propose a controller for finger joint angle estimation by surface electromyography (sEMG). The sEMG data used for training were gathered with the Myo armband, which is a commercial EMG sensor. Two features in the time domain were extracted and fed into a nonlinear autoregressive model with exogenous inputs (NARX). The NARX model was trained with pre-selected parameters using the Levenberg–Marquardt algorithm. Comparing with the targets, the regression correlation coefficient (R) of the model outputs was more than 0.982 over all test subjects, and the mean square error was less than 10.02 for a signal range in arbitrary units equal to [0, 255]. The study also demonstrated that the proposed model could be used in daily life movements with good accuracy and generalization abilities.

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Development of a multi-DOF prosthetic hand with intrinsic actuation, intuitive control and sensory feedback

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-11-2013-417 ◽

2014 ◽

Vol 41 (4) ◽

pp. 381-392 ◽

Cited By ~ 22

Author(s):

Hong Liu ◽

Dapeng Yang ◽

Li Jiang ◽

Shaowei Fan

Keyword(s):

Sensory Feedback ◽

Sensory Information ◽

Myoelectric Control ◽

Human Hand ◽

Prosthetic Hand ◽

Linkage Mechanism ◽

Content Type ◽

Loop Control ◽

Human In The Loop ◽

Control Scheme

Purpose – The purpose of this paper is to present a five-fingered, multisensory prosthetic hand integrating both intuitive myoelectric control and sensory feedback. Design/methodology/approach – The artificial hand’s palm has a three-arcuate configuration and the thumb can move along a cone surface, improving the resemblance with the biological hand. By using a coupling linkage mechanism, each finger is independently actuated by a direct current motor. Both torque and position sensors are embedded in the finger to sense the hand’s status and its interaction with the outer environment. The proposed human-in-the-loop control system consists of an internal motion control scheme and an external human–machine interface. The pattern recognition-based electromyography (EMG) control scheme is adopted to control the motion of the hand, and the transcutaneous electrical nerve stimulation (TENS) is utilized to feedback the hand’s sensory information to its user. Findings – The hand prototype shows that it has an anthropomorphic appearance (85 per cent to an average human hand), low weight (420 g), great power (10 N on the fingertip) and eligible dexterity. Clinical evaluation of the prosthetic hand on transradial amputees also approves the hand design. Originality/value – From a systematic view, the paper details the design concepts of the HIT–DLR prosthetic hand IV, especially on its appearance, mechanism, myoelectric control and sensory feedback.

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Biomimetic Prosthetic Hand Enabled by Liquid Crystal Elastomer Tendons

Micromachines ◽

10.3390/mi12070736 ◽

2021 ◽

Vol 12 (7) ◽

pp. 736

Author(s):

Haiqing Lu ◽

Zhanan Zou ◽

Xingli Wu ◽

Chuanqian Shi ◽

Yimeng Liu ◽

...

Keyword(s):

Liquid Crystal ◽

Joule Heating ◽

Temperature Increase ◽

Human Hand ◽

Prosthetic Hand ◽

Linear Contraction ◽

Liquid Crystal Elastomer ◽

Prosthetic Hands ◽

Prosthetic Implants ◽

Contraction Stress

As one of the most important prosthetic implants for amputees, current commercially available prosthetic hands are still too bulky, heavy, expensive, complex and inefficient. Here, we present a study that utilizes the artificial tendon to drive the motion of fingers in a biomimetic prosthetic hand. The artificial tendon is realized by combining liquid crystal elastomer (LCE) and liquid metal (LM) heating element. A joule heating-induced temperature increase in the LCE tendon leads to linear contraction, which drives the fingers of the biomimetic prosthetic hand to bend in a way similar to the human hand. The responses of the LCE tendon to joule heating, including temperature increase, contraction strain and contraction stress, are characterized. The strategies of achieving a constant contraction stress in an LCE tendon and accelerating the cooling for faster actuation are also explored. This biomimetic prosthetic hand is demonstrated to be able to perform complex tasks including making different hand gestures, holding objects of different sizes and shapes, and carrying weights. The results can find applications in not only prosthetics, but also robots and soft machines.

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Design and Implementation of Arch Function for Adaptive Multi-Finger Prosthetic Hand

Sensors ◽

10.3390/s19163539 ◽

2019 ◽

Vol 19 (16) ◽

pp. 3539

Author(s):

Xu Yong ◽

Xiaobei Jing ◽

Xinyu Wu ◽

Yinlai Jiang ◽

Hiroshi Yokoi

Keyword(s):

Human Hand ◽

Prosthetic Hand ◽

Prosthetic Hands ◽

Design And Implementation ◽

Carpometacarpal Joints

Although arch motions of the palm substantially contribute to frequent hand grasping, they are usually neglected in the development of prosthetic hands which focuses on digit movements. We designed the arch function for its implementation on an adaptive multi-finger prosthetic hand. The digits from the developed hand can perform adaptive grasping, and two carpometacarpal joints enable the palm of the prosthetic hand to form an arch with the thumb. Moreover, the arch posture can be passively released, mimicking the human hand switching between sphere and medium wrap grasps according to the situation. Other requirements such as weight, cost, and size limitations for hand prostheses were also considered. As a result, we only used three actuators fully embedded in the palm through a novel tendon-driven transmission. Although the prosthetic hand is almost the same size of an adult hand, it weighs only 146 g and can perform 70% of the 10 most frequent grasps.

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Control of Hand Prostheses: A Literature Review

Volume 6A: 37th Mechanisms and Robotics Conference ◽

10.1115/detc2013-13349 ◽

2013 ◽

Cited By ~ 5

Author(s):

Aimee Cloutier ◽

James Yang

Keyword(s):

Nervous System ◽

Sensory Feedback ◽

Recent Progress ◽

Control Method ◽

Control Strategies ◽

Human Hand ◽

Prosthetic Hand ◽

Natural Control ◽

Prosthetic Hands ◽

And Control

In recent years, there has been a steep rise in the quality of prostheses for patients with upper limb amputations. One common control method, using electromyographic (EMG) signals generated by muscle contractions, has allowed for an increase in the degrees of freedom (DOFs) of hand designs and a larger number of available grip patterns with little added complexity for the wearer. However, it provides little sensory feedback and requires non-natural control which must be learned by the user. Another recent improvement in prosthetic hand design instead employs electroneurographic (ENG) signals, requiring an interface directly with the peripheral nervous system (PNS) or the central nervous system (CNS) to control a prosthetic hand. While ENG methods are more invasive than using surface EMG for control, an interface with the PNS has the potential to provide more natural control and creates an avenue for both efferent and afferent sensory feedback. Despite the recent progress in design and control strategies, however, prosthetic hands are still far more limited than the actual human hand. This review outlines the recent progress in the development of EMG and ENG controlled prosthetic hands, discussing advancements in the areas of sensory feedback and control. The potential benefits and limitations of both control strategies, in terms of signal classification, invasiveness, and sensory feedback, are examined. A brief overview of interfaces with the CNS is provided, and potential future developments for these control methods are discussed.

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Human Hand Anatomy-Based Prosthetic Hand

Sensors ◽

10.3390/s21010137 ◽

2020 ◽

Vol 21 (1) ◽

pp. 137

Author(s):

Larisa Dunai ◽

Martin Novak ◽

Carmen García Espert

Keyword(s):

3D Printing ◽

Degrees Of Freedom ◽

Use Of Force ◽

Hand Movements ◽

Human Hand ◽

Prosthetic Hand ◽

Object Surface ◽

Hand Phalanges ◽

High Level

The present paper describes the development of a prosthetic hand based on human hand anatomy. The hand phalanges are printed with 3D printing with Polylactic Acid material. One of the main contributions is the investigation on the prosthetic hand joins; the proposed design enables one to create personalized joins that provide the prosthetic hand a high level of movement by increasing the degrees of freedom of the fingers. Moreover, the driven wire tendons show a progressive grasping movement, being the friction of the tendons with the phalanges very low. Another important point is the use of force sensitive resistors (FSR) for simulating the hand touch pressure. These are used for the grasping stop simulating touch pressure of the fingers. Surface Electromyogram (EMG) sensors allow the user to control the prosthetic hand-grasping start. Their use may provide the prosthetic hand the possibility of the classification of the hand movements. The practical results included in the paper prove the importance of the soft joins for the object manipulation and to get adapted to the object surface. Finally, the force sensitive sensors allow the prosthesis to actuate more naturally by adding conditions and classifications to the Electromyogram sensor.

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Recent Advances in Myoelectric Control for Finger Prostheses for Multiple Finger Loss

Applied Sciences ◽

10.3390/app11104464 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4464

Author(s):

Viritpon Srimaneepong ◽

Artak Heboyan ◽

Azeem Ul Yaqin Syed ◽

Hai Anh Trinh ◽

Pokpong Amornvit ◽

...

Keyword(s):

Web Of Science ◽

Myoelectric Control ◽

Original Research ◽

Prosthetic Hand ◽

Precise Control ◽

Prosthetic Hands ◽

Prosthesis Retention ◽

Finger Prosthesis ◽

Artificial Hand

The loss of one or multiple fingers can lead to psychological problems as well as functional impairment. Various options exist for replacement and restoration after hand or finger loss. Prosthetic hand or finger prostheses improve esthetic outcomes and the quality of life for patients. Myoelectrically controlled hand prostheses have been used to attempt to produce different movements. The available articles (original research articles and review articles) on myoelectrically controlled finger/hand prostheses from January 1922 to February 2021 in English were reviewed using MEDLINE/PubMed, Web of Science, and ScienceDirect resources. The articles were searched using the keywords “finger/hand loss”, “finger prosthesis”, “myoelectric control”, and “prostheses” and relevant articles were selected. Myoelectric or electromyography (EMG) signals are read by myoelectrodes and the signals are amplified, from which the muscle’s naturally generated electricity can be measured. The control of the myoelectric (prosthetic) hands or fingers is important for artificial hand or finger movement; however, the precise control of prosthetic hands or fingers remains a problem. Rehabilitation after multiple finger loss is challenging. Implants in finger prostheses after multiple finger loss offer better finger prosthesis retention. This article presents an overview of myoelectric control regarding finger prosthesis for patients with finger implants following multiple finger loss.

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Hand Prosthetic Design for Transradial Amputee by Using 3D Printing Technology to Enhance Life Quality

Jurnal Teknokes ◽

10.35882/teknokes.v14i2.7 ◽

2021 ◽

Vol 14 (2) ◽

pp. 87-94

Author(s):

Triwiyanto Triwiyanto ◽

Torib Hamzah ◽

Sari Luthfiyah ◽

Bedjo Utomo

Keyword(s):

3D Printing ◽

Life Quality ◽

Monitoring And Evaluation ◽

Banana Peel ◽

Physical Parameters ◽

Prosthetic Hand ◽

Printing Technology ◽

3D Printing Technology ◽

Glucose Levels ◽

Prosthetic Hands

The target for this community service program is a resident of Jl. Parikesit RT 05 RW 03 Dusun Picis, Balongdowo Village, Candi District, Sidoarjo Regency. He had a work accident in one of the industries in the city of Sidoarjo in 2010 on the left wrist up to the fingers, so the doctor suggested amputation. He is actually still in his productive age (36 years old) but because of this situation, he is unable to carry out activities in the world of work and has decreased confidence in himself and avoids socializing in society. The purpose of this community partnership program (PKM) activity is to apply 3d printing technology in the manufacture of prosthetic hands for people who have transradial amputations as an effort to improve the quality of life. The implementation methods used are: a) the measurement of several physical parameters on the amputee such as the diameter of the arm circumference, the length of the amputated part, weight and height. In addition to physical parameters, we also carry out medical measurements, including obtaining information on health conditions such as blood pressure, heart health and blood glucose levels, b) designing prosthetic hands using 3D application programs and 3D printers, c) mechanical and functional testing for perform basic movements in the form of opening and closing the palms, d) monitoring and evaluation of the use of prosthetic hands. The results obtained from this activity are that the patient can use the prosthetic hand to assist with activities in carrying out daily activities. In this PKM activity, amputees have been tested, namely the movement of holding a mineral water bottle, holding a banana, peeling a banana peel and driving a two-wheeled motorized vehicle. Monitoring shows that patients need regular exercise in using prosthetic hands so that they are able to control and condition their use. In the future, several developments can be made, including in terms of control and size of the prosthetic hand so that patients can feel the benefits of a prosthetic hand that functions like a normal hand.

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Design and multichannel electromyography system-based neural network control of a low-cost myoelectric prosthesis hand

Mechanical Sciences ◽

10.5194/ms-12-69-2021 ◽

2021 ◽

Vol 12 (1) ◽

pp. 69-83

Author(s):

Saygin Siddiq Ahmed ◽

Ahmed R. J. Almusawi ◽

Bülent Yilmaz ◽

Nuran Dogru

Keyword(s):

Neural Network ◽

Control Method ◽

Low Cost ◽

Hand Movement ◽

Cost Effective ◽

Network Control ◽

Human Hand ◽

Prosthetic Hand ◽

Myoelectric Prosthesis ◽

System File

Abstract. This study introduces a new control method for electromyography (EMG) in a prosthetic hand application with a practical design of the whole system. The hand is controlled by a motor (which regulates a significant part of the hand movement) and a microcontroller board, which is responsible for receiving and analyzing signals acquired by a Myoware muscle device. The Myoware device accepts muscle signals and sends them to the controller. The controller interprets the received signals based on the designed artificial neural network. In this design, the muscle signals are read and saved in a MATLAB system file. After neural network program processing by MATLAB, they are then applied online to the prosthetic hand. The obtained signal, i.e., electromyogram, is programmed to control the motion of the prosthetic hand with similar behavior to a real human hand. The designed system is tested on seven individuals at Gaziantep University. Due to the sufficient signal of the Mayo armband compared to Myoware sensors, Mayo armband muscle is applied in the proposed system. The discussed results have been shown to be satisfactory in the final proposed system. This system was a feasible, useful, and cost-effective solution for the handless or amputated individuals. They have used the system in their day-to-day activities that allowed them to move freely, easily, and comfortably.

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