scholarly journals Can Prosthetic Hands Mimic a Healthy Human Hand?

Prosthesis ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 11-23
Author(s):  
Ka Ho Ng ◽  
Vaheh Nazari ◽  
Monzurul Alam
Keyword(s):  
Standard Of Living ◽  
Human Hand ◽  
Mechanical Device ◽  
Historical Evidence ◽  
Healthy Human ◽  
Prosthetic Hands ◽  
Ancient Egyptian ◽  
Prosthetic Limbs ◽  
Advanced Science ◽  
Open Question

Historical evidence suggests that prostheses have been used since ancient Egyptian times. Prostheses were usually utilized for function and cosmetic appearances. Nowadays, with the advancement of technology, prostheses such as artificial hands can not only improve functional, but have psychological advantages as well and, therefore, can significantly enhance an individual’s standard of living. Combined with advanced science, a prosthesis is not only a simple mechanical device, but also an aesthetic, engineering and medical marvel. Prosthetic limbs are the best tools to help amputees reintegrate into society. In this article, we discuss the background and advancement of prosthetic hands with their working principles and possible future implications. We also leave with an open question to the readers whether prosthetic hands could ever mimic and replace our biological hands.

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

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.

scholarly journals A novel energy-motion model for continuous sEMG decoding: from muscle energy to motor pattern

2020 ◽  
Author(s):  
Gang Liu ◽  
Lu Wang ◽  
Jing Wang
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Motor Pattern ◽  
Human Hand ◽  
Motion Model ◽  
Real Time Control ◽  
Prosthetic Hands ◽  
Time Control ◽  
Energy Mode ◽  
Muscle Energy

Myoelectric prosthetic hands create the possibility for amputees to control their prosthetics like native hands. However, user acceptance of the extant myoelectric prostheses is low. Unnatural control, lack of sufficient feedback, and insufficient functionality are cited as primary reasons. Recently, although many multiple degrees-of-freedom (DOF) prosthetic hands and tactile-sensitive electronic skins have been developed, no non-invasive myoelectric interfaces can decode both forces and motions for five-fingers independently and simultaneously. This paper proposes a myoelectric interface based on energy allocation and fictitious forces hypothesis by mimicking the natural neuromuscular system. The energy-based interface uses a kind of continuous “energy mode” in the level of the entire hand. According to tasks itself, each energy mode can adaptively and simultaneously implement multiple hand motions and exerting continuous forces for a single finger. Also, a few learned energy modes could extend to the unlearned energy mode, highlighting the extensibility of this interface. We evaluate the proposed system through off-line analysis and operational experiments performed on the expression of the unlearned hand motions, the amount of finger energy, and real-time control. With active exploration, the participant was proficient at exerting just enough energy to five fingers on “fragile” or “heavy” objects independently, proportionally, and simultaneously in real-time. The main contribution of this paper is proposing the bionic energy-motion model of hand: decoding a few muscle-energy modes of the human hand (only ten modes in this paper) map massive tasks of bionic hand.

scholarly journals Next-Generation Prosthetic Hand: from Biomimetic to Biorealistic

Research ◽  
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.

Reading Greek Literature

2013 ◽  
Author(s):  
Thomas A. Schmitz
Keyword(s):  
Literary Texts ◽  
Oral Poetry ◽  
Greek Literature ◽  
Ancient Greek ◽  
Clear Cut ◽  
Ancient Egyptian ◽  
Special Quality ◽  
Egyptian Literature ◽  
Open Question

This chapter looks at Ancient Greek texts as a foil for Ancient Egyptian literature. Scholars who work on cultural products of premodern societies will always be faced with the question whether, by using modern terminology, they are unconsciously importing anachronistic and thus inappropriate concepts into their research. The word ‘literature’ implies literacy, but it is an open question whether the fundamental qualities of writing can reside in texts which have been produced and received as written and read texts. The chapter argues that the awareness of the special quality of literary texts can indeed be found in the earliest Greek texts. It compares the ways in which speaker and addressee are constructed in early oral poetry (such as lyrics and epic) and early written texts (such as epigrams) and argues that there is no clear-cut boundary between the two modes.

scholarly journals Top-Down Modulation of Motor Priming by Belief About Animacy

2010 ◽  
Vol 57 (3) ◽  
pp. 221-227 ◽  
Author(s):  
Roman Liepelt ◽  
Marcel Brass
Keyword(s):  
Priming Effect ◽  
Stimulus Display ◽  
Human Hand ◽  
Human Beings ◽  
Top Down ◽  
Motor Priming ◽  
Priming Task ◽  
Contradictory Evidence ◽  
Intentional Agents ◽  
Open Question

There is recent evidence that we directly map observed actions of other agents onto our own motor repertoire, referred to as direct matching (Iacoboni et al., 1999). This was shown when we are actively engaged in joint action with others’ (Sebanz et al. 2003) and also when observing irrelevant movements while executing congruent or incongruent movements (Brass et al., 2000). However, an open question is whether direct matching in human beings is limited to the perception of intentional agents. Recent research provides contradictory evidence with respect to the question whether the direct matching system has a biological bias possibly emerging from perceptual differences of the stimulus display. In this study all participants performed a motor priming task observing the identical animation showing finger lifting movements of a hand in a leather glove. Before running the experiment we presented either a human hand or a wooden analog hand wearing the leather glove. We found a motor priming effect for both human and wooden hands. However, motor priming was larger when participants believed that they interacted with a human hand than when they believed to interact with a wooden hand. The stronger motor priming effect for the biological agent suggests that the “direct matching system” is tuned to represent actions of animate agents.

Dextrous Hands: Human, Prosthetic, and Robotic

1997 ◽  
Vol 6 (1) ◽  
pp. 29-56 ◽  
Author(s):  
Lynette Jones
Keyword(s):  
Sensory Processing ◽  
Human Hand ◽  
Robotic Hands ◽  
Prosthetic Hands ◽  
Robot Hands ◽  
Natural Sense ◽  
Manual Skills ◽  
Sense Of Touch ◽  
Manual Performance ◽  
Dextrous Hands

The sensory and motor capacities of the human hand are reviewed in the context of providing a set of performance characteristics against which prosthetic and dextrous robot hands can be evaluated. The sensors involved in processing tactile, thermal, and proprioceptive (force and movement) information are described, together with details on their spatial densities, sensitivity, and resolution. The wealth of data on the human hand's sensory capacities is not matched by an equivalent database on motor performance. Attempts at quantifying manual dexterity have met with formidable technological difficulties due to the conditions under which many highly trained manual skills are performed. Limitations in technology have affected not only the quantifying of human manual performance but also the development of prosthetic and robotic hands. Most prosthetic hands in use at present are simple grasping devices, and imparting a “natural” sense of touch to these hands remains a challenge. Several dextrous robot hands exist as research tools and even though some of these systems can outperform their human counterparts in the motor domain, they are still very limited as sensory processing systems. It is in this latter area that information from studies of human grasping and processing of object information may make the greatest contribution.

scholarly journals Age-related changes in cutaneous sensation in the healthy human hand

AGE ◽  
2012 ◽  
Vol 35 (4) ◽  
pp. 1077-1089 ◽  
Author(s):  
Jocelyn L. Bowden ◽  
Penelope A. McNulty
Keyword(s):  
Human Hand ◽  
Healthy Human ◽  
Cutaneous Sensation ◽  
Age Related ◽  
Age Related Changes

Android Hands: A State-of-the-Art Report

2014 ◽  
Author(s):  
Evgenios Vlachos ◽  
Henrik Schärfe
Keyword(s):  
Literature Review ◽  
State Of The Art ◽  
Structure Functions ◽  
Social Robot ◽  
The State ◽  
Human Hand ◽  
Prosthetic Hands ◽  
Available Technology ◽  
And Performance ◽  
Humanoid Hand

Humans have adjusted their space, their actions, and their performed tasks according to their morphology, abilities, and limitations. Thus, the properties of a social robot should fit within these predetermined boundaries when, and if it is beneficial for the user, and the notion of the task. On such occasions, android and humanoid hand models should have similar structure, functions, and performance as the human hand. In this paper we present the anatomy, and the key functionalities of the human hand followed by a literature review on android/humanoid hands for grasping and manipulating objects, as well as prosthetic hands, in order to inform roboticists about the latest available technology, and assist their efforts to describe the state-of-the-art in this field.

Biomimetic Tactile Sensor

2007 ◽  
Author(s):  
Nicholas Wettels ◽  
Djordje Popovic ◽  
Gerald E. Loeb
Keyword(s):  
Tactile Sensor ◽  
Robotic Manipulators ◽  
Human Hand ◽  
Force Sensors ◽  
Tactile Information ◽  
Prosthetic Hands ◽  
Sharp Edges

The performance of prosthetic hands and robotic manipulators is severely limited by their having little or no tactile information compared to the human hand. Technologies such as MEMS, microfluidics, and nanoparticles have been used to produce arrays of force sensors, but these are generally not robust enough to mount on curved, deformable finger pads or to use in environments that include dust, fluids, sharp edges and wide temperature swings. Furthermore, it is not clear how the prosthetic controller will use the tactile information, so it is difficult to generate specifications for these sensors.

Human-Inspired Representation of Object-Specific Grasps for Anthropomorphic Hands

2020 ◽  
Vol 17 (02) ◽  
pp. 2050008 ◽  
Author(s):  
Julia Starke ◽  
Christian Eichmann ◽  
Simon Ottenhaus ◽  
Tamim Asfour
Keyword(s):  
Direct Synthesis ◽  
Three Dimensional ◽  
Compact Representation ◽  
Human Hand ◽  
Robotic Hands ◽  
Prosthetic Hands ◽  
Latent Space ◽  
Efficient Control ◽  
Anthropomorphic Hands ◽  
Grasp Type

The human hand is a complex, highly-articulated system, which has been the source of inspiration in designing humanoid robotic and prosthetic hands. Understanding the functionality of the human hand is crucial for the design, efficient control and transfer of human versatility and dexterity to such anthropomorphic robotic hands. Although research in this area has made significant advances, the synthesis of grasp configurations, based on observed human grasping data, is still an unsolved and challenging task. In this work we derive a novel, constrained autoencoder model, that encodes human grasping data in a compact representation. This representation encodes both the grasp type in a three-dimensional latent space and the object size as an explicit parameter constraint allowing the direct synthesis of object-specific grasps. We train the model on 2250 grasps generated by 15 subjects using 35 diverse objects from the KIT and YCB object sets. In the evaluation we show that the synthesized grasp configurations are human-like and have a high probability of success under pose uncertainty.

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