A novel grasping force control strategy for multi-fingered prosthetic hand

A grasping force control strategy is proposed in order to complete various free manipulations by using anthropomorphic prosthetic hand. The position-based impedance control and force-tracking impedance control are used in free and constraint spaces, respectively. The fuzzy observer is adopted in transition in order to switch control mode. Two control modes use one position-based impedance controller. In order to achieve grasping force track, reference force is added to the impedance controller in the constraint space. Trajectory tracking in free space and torque tracking in constrained space are realized, and reliability of mode switch and stability of system are achieved. An adaptive sliding mode friction compensation method is proposed. This method makes use of terminal sliding mode idea to design sliding mode function, which makes the tracking error converge to zero in finite time and avoids the problem of conventional sliding surface that tracking error cannot converge to zero. Based on the characteristic of the exponential form friction, the sliding mode control law including the estimation of friction parameter is obtained through terminal sliding mode idea, and the online parameter update laws are obtained based on Lyapunov stability theorem. The experiments on the HIT Prosthetic Hand IV are carried out to evaluate the grasping force control strategy, and the experiment results verify the effectiveness of this control strategy.

HIT prosthetic hand based on tendon-driven mechanism

An underactuated finger structure actuated by tendon-driven system is presented.Kinematics and static analysis of the finger is done,and the results indicate that the prosthetic finger structure is effective and feasible.Based on the design of finger,a prosthetic hand is designed.The hand is composed of 5 independent fingers and it looks more like humanoid.Its size is about 85% of an adult's hand and weights about 350 g.Except the thumb finger,each finger is actuated by one DC motor,gear head and a tendon,and has three curling/extension joints.The thumb finger which is different from other existing prostheses is a novel design scheme.The thumb finger has four joints including three curling/extension joints and a joint which is used to realize the motion of the thumb related to the palm,and these joints are also driven by one DC motor,harmonic drive and a tendon.The underactuation and adaptive curling/extension motion of the finger are realized by joint torsion springs.A high-powered chip of digital signal processing(DSP)is the main part of the electrical system which is used for the motors control,data collection,communication with external controlling source,and so on.To improve the reliability of the hand,structures and sensors are designed and made as simply as possible.The hand has strong manipulation capabilities that have been verified by finger motion and grasping tests and it can satisfy the daily operational needs and psychological needs of deformities.

Development of an underactuated prosthetic hand with the step motor

We present the development of a novel prosthetic hand based on the underactuated mechanism. The aim is focused on increasing its dexterity while keeping the same dimension and weight of a traditional prosthetic device. The hybrid step motor is used as the actuator, which enables the finger to keep enough high contact torque on the grasped object with less energy consumption provided by the holding torque. The grasping force of the finger is estimated from the base joint torque, and the adoption of impedance control has provided compliance in the grasping. Also a parallel observer is used to switch over between the impedance control and the torque holding mode. The experimental results show the effectiveness of the design and control strategy.

A five-fingered underactuated prosthetic hand:hardware and its control scheme

A five-fingered underactuated prosthetic hand controlled by surface EMG (electromyographic) signals is presented in this paper. The prosthetic hand was designed with simplicity, lightweight and dexterity on the requirement of anthropomorphic hands. Underactuated self-adaptive theory was adopted to decrease the number of motors and weight. The control part of the prosthetic hand was based on a surface EMG motion pattern classifier which combines LM-based (Levenberg-Marquardt) neural network with the parametric AR (autoregressive) model. This motion pattern classifier can successfully identify the flexions of the thumb, the index finger and the middle finger by measuring the surface EMG signals through two electrodes mounted on the flexor digitorum profundus and flexor pollicis longus. Furthermore, via continuously controlling a single finger's motion, the five-fingered underactuated prosthetic hand can achieve more prehensile postures such as power grasp, centralized grip, fingertip grasp, cylindrical grasp, etc. The experimental results show that the classifier has a great potential application to the control of bionic man-machine systems because of its fast learning speed, high recognition capability and strong robustness.

Development of Multi-Fingered Prosthetic Hand Using Shape Memory Alloy Type Artificial Muscle

A new prosthetic hand with a fixed thumb and four fingers actuated by Shape Memory Alloy （SMA） type artificial muscle has been developed in this paper. Different from typical geared motor, SMA actuator is lightweight and silent, however shows a little short stroke and small attracting force per each unit. In order to achieve enough output force and motion range of each finger, multiple SMA type artificial muscles with special device which facilitates enough length are equipped in the hand. The fundamental properties of the SMA type artificial muscle including output force and electrical response were determined experimentally and considered for the design of hand mechanism. Besides, the structure of each finger and whole system has been designed based on observation of human hand. The electrical hardware to control multiple shape memory alloy type artificial muscles has been also developed. Finally, the usefulness of the prosthetic hand has been investigated through experiments for grasping several types of objects.

Design and Myoelectric Control of an Anthropomorphic Prosthetic Hand

This paper presents an anthropomorphic prosthetic hand using flexure hinges, which is controlled by the surface electromyography （sEMG） signals from 2 electrodes only. The prosthetic hand has compact structure with 5 fingers and 4 Degree of Freedoms （DoFs） driven by 4 independent actuators. Helical springs are used as elastic joints and the joints of each finger are coupled by tendons. The myoelectric control system which can classify 8 prehensile hand gestures is built. Pattern recognition is employed where Mean Absolute Value （MAV）, Variance （VAR）, the fourth-order Autoregressive （AR） coefficient and Sample Entropy （SE） are chosen as the optimal feature set and Linear Discriminant Analysis （LDA） is utilized to reduce the dimension. A decision of hand gestures is generated by LDA classifier after the current projected feature set and the previous one are ＂pre-smoothed＂, and then the final decision is obtained when the current decision and previous decisions are ＂post-smoothed＂ from the decisions flow. The prosthetic hand can perform prehensile postures for activities of daily living and carry objects under the control of EMG signals.

A Synthetic Framework for Evaluating and Designing an Anthropomorphic Prosthetic Hand

The mimic of aesthetics, fianction, and rehabilitation application makes the prosthetic hand design an interdisciplinary, synthetic work. Prosthetic hands should be designed in a comprehensive consideration with a synthetic framework from multiple areas. In this case, a synthetic framework containing 12 anthropomorphism indexes is established and utilized to understand the human hand characteristic and quantifiably evaluate the anthropomorphism of a prosthetic hand. Our quantified evaluation results show that a Global Anthropomorphic Score （GAS） of the current commercial prosthetic hands is only 45.2%. The compliance, coupling speed ratio and configuration of the Degrees Of Freedom （DOF） are found to be the lowest three anthropomorphism evaluation indexes in all 12 indexes. In addition, a design priority is proposed based on the quantified evaluation results and contributes to a prosthetic hand design. Moreover, our correlation analysis results between each index and GAS show that, compared with the conventional evaluation index-grasp gesture, the rotation axis distribution index has a stronger distinguishing capability to the hand performance. Finally, a flowchart of prosthetic hand design was presented for a designer to design a prosthetic hand with a high anthropomorphism.

A Smart and Hybrid Composite Finger with Biomimetic Tapping Motion for Soft Prosthetic Hand

This paper introduces the design and fabrication of a smart and Hybrid Composite Finger(HCF)to achieve finger-like motions,such as holding and tapping motions.Bionic research on tapping motion of the index finger was conducted to obtain its structural and tapping parameters.The HCF,actuated by Shape Memory Alloy(SMA)wires,possesses a hybrid structure which is composed of a rigid structure to be its metacarpal part and a deformable structure to produce bending movement just like the function of the finger.Owing to an adhesive bonding technology,the HCF was fabricated with a composite structure which is reliable under impulsive responses,and had a worklife of more than 630000 times.A bending model was built by synthesizing the phase transformation dynamic model of the SMA wires and quasi-static analysis of the HCF.Structural optimization of the HCF was conducted by synthesizing the bending model together with experimental analyses.To produce a holding motion like as the finger,a holding heating strategy was proposed to adaptively heat the HCF to keep holding state based on the resistance feedback of SMA wires and a Proportion Differentiation(PD)algorithm.Besides,we used an impulsive heating method to heat the HCF to produce a high fidelity tapping motion with a maximum tapping force(6.83 N)at a response time(43 ms)which considerably coincided with those(about 5.8 N,45 ms)from tapping bionics of the index finger.Finally,a soft prosthetic hand system which had a hand-like appearance was manufactured based on the HCFs and several tests like as anthropomorphic gesture motions and human-like tapping motions to tap a keyboard were conducted to prove potential application of the HCF.

Grasping Force Planning and Control for Tendon-driven Anthropomorphic Prosthetic Hands

A force planning and control method is proposed for a tendon-driven anthropomorphic prosthetic hand. It is necessary to consider grasping stability for the anthropomorphic prosthetic hand with multi degrees of freedom which aims to mimic human hands with dexterity and stability. The excellent grasping performance of the anthropomorphic prosthetic hand mainly depends on the accurate computation of the space position of finger tips and an appropriate grasping force planning strategy. After the dynamics model of the tendon-driven anthropomorphic prosthetic hand is built, the space positions of the finger tips are calculated in real time by solving the dynamic equations based on the Newton iteration algorithm with sufficient accuracy. Then, the balance of internal grasping force on the thumb is adopted instead of force closure of the grasped objects to plan the grasping forces of other fingers based on the method of the linear constraint gradient flow in real time. Finally, a fuzzy logic controller is used to control the grasping force of the prosthetic hand. The proposed force planning and control method is implemented on the tendon-driven anthropomorphic prosthetic hand and the experimental results dem- onstrate the feasibility and effectiveness of the proposed method.

Control of myoelectric prosthetic hand with a novel proximity-tactile sensor

Currently, prosthetic hands can only achieve several prespecified and discrete hand motion patterns from popular myoelectric control schemes using electromyography(EMG) signals. To achieve continuous and stable grasping within the discrete motion pattern, this paper proposes a control strategy using a customized, flexible capacitance-based proximity-tactile sensor. This sensor is integrated at the fingertip and measures the distance and force before and after contact with an object. During the pregrasping phase, each fingertip’s position is controlled based on the distance between the fingertip and the object to make all fingertips synchronously approach the object at the same distance. Once contact is established, the sensor turns to output the tactile information, by which the contact force of each fingertip is finely controlled. Finally, the method is introduced into the human-machine interaction control for a myoelectric prosthetic hand. The experimental results demonstrate that continuous and stable grasping could be achieved by the proposed control method within the subject’s discrete EMG motion mode. The subject also obtained tactile feedback through the transcutaneous electrical nerve stimulation after contact.

Review on Tactile Sensory Feedback of Prosthetic Hands for the Upper-Limb Amputees by Sensory Afferent Stimulation

Loss of sensory function for upper-limb amputees inevitably devastates their life qualities, and lack of reliable sensory feedback is the biggest defect to sophisticated prosthetic hands, greatly hindering their usefulness and perceptual embodiment. Thus, it is extremely necessary to accomplish an intelligent prosthetic hand with effective tactile sensory feedback for an upper-limb amputee. This paper presents an overview of three kinds of existing sensory feedback approaches, including cutaneous mechanical stimulation(CMS), transcutaneous electrical nerve stimulation(TENS) and direct peripheral nerve electrical stimulation(DPNES). The emphasis concentrates on major scientific achievements, advantages and disadvantages. The TENS on the skin areas with evoked finger sensation(EFS) at upper-limb amputees' residual limbs might be one of the most promising approaches to realize natural sensory feedback.

Function-oriented optimization design method for underactuated tendon-driven humanoid prosthetic hand

The loss of hand functions in upper limb amputees severely restricts their mobility in daily life.Wearing a humanoid prosthetic hand would be an effective way of restoring lost hand functions.In a prosthetic hand design,replicating the natural and dexterous grasping functions with a few actuators remains a big challenge.In this study,a function-oriented optimization design(FOD)method is proposed for the design of a tendon-driven humanoid prosthetic hand.An optimization function of different functional conditions of full-phalanx contact,total contact force,and force isotropy was constructed based on the kinetostatic model of a prosthetic finger for the evaluation of grasping performance.Using a genetic algorithm,the optimal geometric parameters of the prosthetic finger could be determined for specific functional requirements.Optimal results reveal that the structure of the prosthetic finger is significantly different when designed for different functional requirements and grasping target sizes.A prosthetic finger was fabricated and tested with grasping experiments.The mean absolute percentage error between the theoretical value and the experimental result is less than 10%,demonstrating that the kinetostatic model of the prosthetic finger is effective and makes the FOD method possible.This study suggests that the FOD method enables the systematic evaluation of grasping performance for prosthetic hands in the design stage,which could improve the design efficiency and help prosthetic hands meet the design requirements.

Design, kinematic modeling and evaluation of a novel soft prosthetic hand with abduction joints

This paper presents a novel tendon-driven soft prosthetic hand with 5 fingers and 9 independent actuators.A special notched structure was used as the finger joint,which brings adequate compliance to grasping.The soft finger has two kinds of vertically arranged joints that can produce flexion/extension and abduction/adduction motions under tension and release,enabling a three-dimensional workspace of the finger and improving the dexterity of the hand.The design and manufacture of the finger and soft hand are described in detail.An openloop kinematic model based on piecewise constant curvature of the finger was established and verified experimentally.The results show that the model could precisely predict finger movement.The slip resistance of the soft hand was tested,and the capacity to grasp objects was evaluated based on power grasp and precision grasp.With abduction joints,the proposed hand can perform various gestures and in-hand manipulations,which indicate high dexterity.This work provides a way to realize high dexterity for soft prosthetic hands.

A relation spectrum inheriting Taylor series:muscle synergy and coupling for hand

There are two famous function decomposition methods in math:the Taylor series and the Fourier series.The Fourier series developed into the Fourier spectrum,which was applied to signal decomposition and analysis.However,because the Taylor series function cannot be solved without a definite functional expression,it has rarely been used in engineering.We developed a Taylor series using our proposed dendrite net(DD),constructed a relation spectrum,and applied it to decomposition and analysis of models and systems.Specifically,knowledge of the intuitive link between muscle activity and finger movement is vital for the design of commercial prosthetic hands that do not need user pre-training.However,this link has yet to be understood due to the complexity of the human hand.In this study,the relation spectrum was applied to analyze the muscle—finger system.One single muscle actuates multiple fingers,or multiple muscles actuate one single finger simultaneously.Thus,the research was focused on muscle synergy and muscle coupling for the hand.The main contributions are twofold:(1)The findings concerning the hand contribute to the design of prosthetic hands;(2)The relation spectrum makes the online model human-readable,which unifies online performance and offline results.Code is available at https://github.com/liugang1234567/Gang-neuron.

An anthropomorphic controlled hand prosthesis system

Based on HIT/DLR(Harbin Institute of Technology/Deutsches Zentrum für Luft-und Raumfahrt) Prosthetic Hand II,an anthropomorphic controller is developed to help the amputees use and perceive the prosthetic hands more like people with normal physiological hands.The core of the anthropomorphic controller is a hierarchical control system.It is composed of a top controller and a low level controller.The top controller has been designed both to interpret the amputee's intensions through electromyography(EMG) signals recognition and to provide the subject-prosthesis interface control with electro-cutaneous sensory feedback(ESF),while the low level controller is responsible for grasp stability.The control strategies include the EMG control strategy,EMG and ESF closed loop control strategy,and voice control strategy.Through EMG signal recognition,10 types of hand postures are recognized based on support vector machine(SVM).An anthropomorphic closed loop system is constructed to include the customer,sensory feedback system,EMG control system,and the prosthetic hand,so as to help the amputee perform a more successful EMG grasp.Experimental results suggest that the anthropomorphic controller can be used for multi-posture recognition,and that grasp with ESF is a cognitive dual process with visual and sensory feedback.This process while outperforming the visual feedback process provides the concept of grasp force magnitude during manipulation of objects.

Application of Forearm FMG signals in Closed Loop Modality-matched Sensory Feedback Stimulation

This study is aimed at exploring a technology that can use the human physiological information,such as Force Myography(FMG)signals to provide sensory feedback to prosthetic hand users.This is based on the principle that with the intent to move the prosthetic hand,the existing limbs in the arm recruit specific group of muscles.These muscles react with a change in the cross-sectional area;piezoelectric sensors placed on these muscles will generate a voltage(FMG signals),in response to the change in muscle volume.The correlation between the amplitude of the FMG signals and intensity of pressure on fingertips during grasping is then computed and a dynamic relation(model)is established through system identification in MATLAB.The estimated models generated a fitting accuracy of more than 80%.The model is then programmed into the Arduino microcontroller,so that a real-time and proportional force feedback is channeled to amputees through a micro actuator.Obtaining such percentages of accuracy in sensory feedback without relying on touch sensors on the prosthetic hand that could be affected by mechanical wear and other interaction factors is promising.Applying advanced signal processing and classification techniques may also refine the findings to better capture and correlate the force variations with the sensory feedback.