Learning from the Human Hand: Force Control and Perception Using a Soft-Synergy Prosthetic Hand and Noninvasive Haptic Feedback

Author(s):  
Qiushi Fu ◽  
Marco Santello
Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 137
Author(s):  
Larisa Dunai ◽  
Martin Novak ◽  
Carmen García Espert

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.


2021 ◽  
Vol 12 (1) ◽  
pp. 69-83
Author(s):  
Saygin Siddiq Ahmed ◽  
Ahmed R. J. Almusawi ◽  
Bülent Yilmaz ◽  
Nuran Dogru

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.


Actuators ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 24
Author(s):  
Guan-Yang Liu ◽  
Yi Wang ◽  
Chao Huang ◽  
Chen Guan ◽  
Dong-Tao Ma ◽  
...  

The goal of haptic feedback in robotic teleoperation is to enable users to accurately feel the interaction force measured at the slave side and precisely understand what is happening in the slave environment. The accuracy of the feedback force describing the error between the actual feedback force felt by a user at the master side and the measured interaction force at the slave side is the key performance indicator for haptic display in robotic teleoperation. In this paper, we evaluate the haptic feedback accuracy in robotic teleoperation via experimental method. A special interface iHandle and two haptic devices, iGrasp-T and iGrasp-R, designed for robotic teleoperation are developed for experimental evaluation. The device iHandle integrates a high-performance force sensor and a micro attitude and heading reference system which can be used to identify human upper limb motor abilities, such as posture maintenance and force application. When a user is asked to grasp the iHandle and maintain a fixed position and posture, the fluctuation value of hand posture is measured to be between 2 and 8 degrees. Based on the experimental results, human hand tremble as input noise sensed by the haptic device is found to be a major reason that results in the noise of output force from haptic device if the spring-damping model is used to render feedback force. Therefore, haptic rendering algorithms should be independent of hand motion information to avoid input noise from human hand to the haptic control loop in teleoperation. Moreover, the iHandle can be fixed at the end effector of haptic devices; iGrasp-T or iGrasp-R, to measure the output force/torque from iGrasp-T or iGrasp-Rand to the user. Experimental results show that the accuracy of the output force from haptic device iGrasp-T is approximately 0.92 N, and using the force sensor in the iHandle can compensate for the output force inaccuracy of device iGrasp-T to 0.1 N. Using a force sensor as the feedback link to form a closed-loop feedback force control system is an effective way to improve the accuracy of feedback force and guarantee high-fidelity of feedback forces at the master side in robotic teleoperation.


Sensor Review ◽  
2016 ◽  
Vol 36 (2) ◽  
pp. 158-168 ◽  
Author(s):  
Drew van der Riet ◽  
Riaan Stopforth ◽  
Glen Bright ◽  
Olaf Diegel

Purpose This paper aims to explore the electronic design of the Touch Hand: a low-cost electrically powered prosthetic hand. The hand is equipped with an array of sensors allowing for position control and haptic sensation. Pressure sensors are used on the fingertips to detect grip force. A temperature sensor placed in the fingertip is used to measure the contact temperature of objects. Investigations are made into the use of cantilever vibration sensors to detect surface texture and object slippage. The hand is capable of performing a lateral grip of 3.7 N, a power grip of 19.5 N and to passively hold a weight of up to 8 kg with a hook grip. The hand is also tested on an amputee and used to perform basic tasks. The amputee took 30 min to learn how to operate the hands basic gripping functions. Design/methodology/approach Problems of previous prosthetic hands were investigated, followed by ways to improve or have similar capabilities, yet keeping in mind to reduce the price. The hand was then designed, simulated, developed and then tested. The hand was then displayed to public and tested with an amputee. Findings The Touch Hand’s capabilities with the usage of the low-cost materials, components and sensory system was obtained in the tests that were conducted. The results are shown in this paper to identify the appropriateness of the sensors for a usage while the costs are reduced. Furthermore, models were developed from the results obtained to take into account factors such as the non-slip material. Research limitations/implications The research was restricted to a US$1,000 budget to allow the availability of a low-cost prosthetic hand. Practical implications The Touch Hand had to have the ability to supply the amputee with haptic feedback while allowing the basic grasping of objects. The commercial value is the availability of an affordable prosthetic hand that can be used by amputees in Africa and other Lower-Income countries, yet allowing a more advanced control system compared to the pure mechanical systems currently available. Social implications The Touch Hand has the ability to give amputees affected in war situations the ability to grasp objects in a more affordable manner compared to the current available options. Feedback from amputees about the current features of the Touch Hand was very positive and it proves to be a way to improve society in Lower-Income countries in the near future. A sponsorship program is being developed to assist amputees with the costs of the Touch Hand. Originality/value The contributions of this research is a low-cost prototype system than can be commercialized to allow amputees in the Lower-Income countries to have the ability of a prosthetic hand. A sensory system in the hand is also explained which other low-cost prosthetic hands do not have, which includes temperature, force and vibration. Models of the sensors used that are developed and calibrated to the design of the hand are also described.


Author(s):  
Esme Abbot ◽  
Amanda de Oliveira Barros ◽  
James Yang

Abstract Human hands play a key role in almost all activities of daily living (ADLs) because it is an incredibly versatile tool capable of complex motion. For individuals who have had a complete loss of the hand, the ability to perform ADLs is impaired. Effective prosthetics accurately simulate the movements of a human hand by providing a high number of degrees of freedom, an efficient control system, and an anthropomorphic appearance. In this paper, the design and construction process of a highly anthropomorphic soft robotic prosthetic hand is outlined. The design specifications of the hand are based on feedback from current and former prosthetic users. The hand endoskeleton was 3D printed using fused deposition modeling techniques and was enclosed in a silicone coating modeled, after a real human hand. The hand presents anthropomorphic design in its realistic bone shapes and in its external covering that is like skin in texture and mechanical properties. The hand utilizes the flexibility of silicone instead of antagonistic tendons which would otherwise add complexity and weight to the prosthetic design. The prototype also includes adduction/abduction of the fingers, which is a common omitted movement in other prosthetics. Testing showed that the hand is capable of effective power and precision grasping.


2019 ◽  
Vol 16 (2) ◽  
pp. 026034 ◽  
Author(s):  
Francesco Clemente ◽  
Giacomo Valle ◽  
Marco Controzzi ◽  
Ivo Strauss ◽  
Francesco Iberite ◽  
...  

2019 ◽  
Vol 5 (1) ◽  
pp. 207-210
Author(s):  
Tolgay Kara ◽  
Ahmad Soliman Masri

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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