Biomimetic Prosthetic Hand Enabled by Liquid Crystal Elastomer Tendons

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.

Download Full-text

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.

Download Full-text

Next-Generation Prosthetic Hand: from Biomimetic to Biorealistic

Research ◽

10.34133/2021/4675326 ◽

2021 ◽

Vol 2021 ◽

pp. 1-4

Author(s):

Ning Lan ◽

Manzhao Hao ◽

Chuanxin M. Niu ◽

He Cui ◽

Yu Wang ◽

...

Keyword(s):

Sensory Information ◽

Human Hand ◽

Prosthetic Hand ◽

Grand Challenge ◽

Sensorimotor System ◽

Next Generation ◽

Ongoing Research ◽

Sensory Awareness ◽

Prosthetic Hands ◽

Significant Step

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.

Download Full-text

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.

Download Full-text

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.

Download Full-text