Underactuated Prosthetic Hand Research Articles

Mechanical assessment of novel compliant mechanisms for underactuated prosthetic hands.

This paper proposes novel compliant mechanisms for constructing hand prostheses based on soft robotics. Two models of prosthetic hands are developed in this work. Three mechanical evaluations are performed to determine the suitability of the two designs for carrying out activities of daily living (ADLs). The first test measures the grip force that the prosthesis can generate on objects. The second determines the energy required and dissipated from the prosthesis to operate. The third test identifies the maximum traction force that the prosthesis can support. The tests showed that the PrHand1 prosthesis has a maximum grip force of 23.38 ± 1.5 N, the required energy is 0.76 ± 0.13 J, and the dissipated energy is 0.21 ± 0.17 J. It supports a traction force of 173.31 ± 5.7 N. The PrHand2 prosthesis has a maximum grip force of 36.13 ± 2.3 N, the required energy is 1.28 ± 0.13 J, the dissipated energy is 0.96 ± 0.12 J, and it supports a traction force of 78.48 ± 0 N. In conclusion, the PrHand1 prosthesis has a better performance in terms of energy and tensile force supported. The difference between the energy and traction force results is related to two design features of the PrHand2: fully silicone-coated fingers and a unifying mechanism that requires more force on the tendons to close the prosthesis. The grip force of the PrHand2 prosthesis was more robust than the PrHand1 due to its silicone coating, which allowed for an improved grip.

Development of a Multisensory Underactuated Prosthetic Hand With Fully Integrated Electronics

The compliance and manipulability are the crucial properties for prosthetic hands design, especially considering both the usefulness and versatility. This study presents a novel mechatronic design of an underactuated prosthetic hand named HIT-VI hand. It consists of four modular underactuated fingers, one opposite thumb, and a set of multisensory embedded control system. Each modular finger uses one dc motor to drive its two active joints and one passive joint. Due to the use of an underactuated nine-bar mechanism, it can execute anthropomorphic coupled motion and self-adaptive motion. The hand contains 39 distributed force sensors, 10 angular position sensors, 6 current sensors, 1 temperature sensor, and 1 inertial measurement unit (IMU). The multisensory system enables the prosthetic hand to achieve intelligent position/force/current control. The fully integrated mechatronic design makes the prosthetic hand similar to an adult hand in size, weight, and appearance. Based on the kinematics and statics, the stability analysis of the prosthetic hand is carried out. Furthermore, the experiments executing the activities of daily living validate that the proposed hand has a respectable compliance and manipulability.

Stiffness-Estimation-Based Grasping Force Fuzzy Control for Underactuated Prosthetic Hands

Human hands can rapidly perceive the stiffness of an object and quickly adapt to different soft and hard objects by adjusting the grasp force of each finger. However, patients with upper-limb loss have difficulty in outputting accurate grasp force based on objects stiffness information, as the efferent and afferent feedback of nerve channels was losing. To realize stiffness-based force control on a prosthetic hand, it is necessary to know the stiffness of the object to be grasped in advance. This article proposed a novel method to estimate the stiffness of the grasped object based on a kinematics model of prosthetic fingers. Using underactuated mechanisms, the stiffness of the grasped object can be derived based on the contact stiffness information that is obtained upon contact between the prosthetic hand and the target object. Based on the estimation of the stiffness of the grasped object, we developed a control strategy to adjust the inappropriate surface electromyography decoding force of the prosthetic hand, which simulated the motion of a human hand. The selected objects in experiments were representative and common objects used in daily life, with stiffness ranging from soft to hard. The proposed method was proven to be effective and feasible during experimental tests, where such a method can be used to quickly differentiate objects with different stiffness values and thus replicate the controllable stiffness-based force of a human hand with a prosthetic hand.

Exploring Stiffness Modulation in Prosthetic Hands and Its Perceived Function in Manipulation and Social Interaction.

To physically interact with a rich variety of environments and to match situation-dependent requirements, humans adapt both the force and stiffness of their limbs. Reflecting this behavior in prostheses may promote a more natural and intuitive control and, consequently, improve prostheses acceptance in everyday life. This pilot study proposes a method to control a prosthetic robot hand and its impedance, and explores the utility of variable stiffness when performing activities of daily living and physical social interactions. The proposed method is capable of a simultaneous and proportional decoding of position and stiffness intentions from two surface electro-myographic sensors placed over a pair of antagonistic muscles. The feasibility of our approach is validated and compared to existing control modalities in a preliminary study involving one prosthesis user. The algorithm is implemented in a soft under-actuated prosthetic hand (SoftHand Pro). Then, we evaluate the usability of the proposed approach while executing a variety of tasks. Among these tasks, the user interacts with other 12 able-bodied subjects, whose experiences were also assessed. Several statistically significant aspects from the System Usability Scale indicate user's preference of variable stiffness control over low or high constant stiffness due to its reactivity and adaptability. Feedback reported by able-bodied subjects reveal a general tendency to favor soft interaction, i.e., low stiffness, which is perceived more human-like and comfortable. These combined results suggest the use of variable stiffness as a viable compromise between firm control and safe interaction which is worth investigating further.

Design of a Novel Locking Ratcheting Mechanism for a Body-Powered Underactuated Hand

AbstractAs affordable and efficient three-dimensional (3D) printers became widely available, researchers are focusing on developing prosthetic hands that are reasonably priced and effective at the same time. By allowing anyone with a 3D printer to build a body-powered prosthetic hand, many people could build their own prosthetic hand. However, one of the major problems with the current designs is the users must bend and hold their wrist in an awkward position to grasp an object. The primary goal of this work is to present the design process and analysis of a body-powered underactuated prosthetic hand with a novel ratcheting mechanism that locks the finger automatically at a desired position. To estimate how a compliant finger behaves on the actual system with the ratcheting mechanism, the preshaping analysis and the preshaping experiment were conducted. From the experiment, the presence of elastic hysteresis was observed. Additionally, the contact force analysis was performed to see the effects of joint angles and applied tension force. To test how well the hand can grasp, a cup with various weights was lifted and various objects with different shapes were grasped to prove how well the compliant finger can adapt to the shape of the objects. Based on the experiment, the hand had a higher success rate of grasping objects that are lightweight (less than 500 g) and cylindrical or circular shaped.

Modeling and simulation of an anthropomorphic hand prosthesis with an object interaction

Background and ObjectiveKinematic and dynamic modeling of any physical process is critical especially for the design phase of associated control units and the prediction of their performance levels. In this paper, a dynamical model and a development frame including interactions with the objects for a tendon-driven underactuated hand are developed and examined. Using the proposed dynamic model, free movement and the object interaction of the underactuated hand can be simulated with a single, integrated simulation step in the simulation frame. MethodsLagrangian Method is used to model the dynamic behavior of the underactuated fingers and the thumb under tendon dependency in a 3D coordinate system. Then, as an important extension to the modeling studies that can be found in the literature, the interaction of the hand with an object that co-exists in its workspace is modeled in terms of contact forces acting on the joints of the fingers. The unified dynamic model is simulated by using the Simulink platform. ResultsThe simulations showed that the adaptability of the underactuated mechanism and joint torque levels are modeled and examined realistically. The flexion movement of the fingers resulted in realistic torque levels which can be handled by commercially-off-the-shelf actuators. Various tendon forces were examined in terms of the distance of the individual phalanx to the object and their contact instants. Applying an increasing input force with 1.617 N/s ramp slope, finger flexion movement was obtained in 1s. In another simulation scenario, compliance of the underactuated mechanism to an object was examined. With 0.66 N/s tendon force input ramp, proximal, middle and distal phalanx contacted an object in 1.3 s, 2.35 s and 2.75 s, respectively. ConclusionsPresented features obtained by the simulation platform are especially useful to researchers working on the development of control methods for underactuated prosthetic hands and robot manipulators. Through the simulations of experimental scenarios, a detailed analysis of dynamic responses of each finger phalanges can be carried out properly in any level of the design phase.

Fuzzy force control based on grasped objects stiffness of tendon-driven underactuated prosthetic hand system

The design of an fuzzy force based on grasped objects stiffness method for tendon-driven underactuated prosthetic hand system are addressed in this study. First, a mathematical model of tendon-driven underactuated prosthetic hand is developed for force control. Next, fuzzy force based on grasped objects stiffness was discussed to improve the control performance. Finally, the proposed control strategy for underactuated prosthetic hand is simulated to six different stiffness objects. The results shown that the controller is suit for prosthetic hand grasp objects with different stiffness. The simulation results verify the effectiveness of the force control method based on grasped objects stiffness.

Stiffness-gradient-based Grasping Force Control for an Underactuated Prosthetic Hand

Stiffness-gradient-based Grasping Force Control for an Underactuated Prosthetic Hand

An Underactuated Prosthetic Hand with Coupled Metacarpophalangeal Joints

The design of a comfortable and functional prosthetic hand is still a challenge. This paper presents the design of a tendon-driven, 3D-printed, underactuated prosthetic hand. An improved structural design was developed to make the hand more flexible. Three fingers are equipped with abduction freedom at the metacarpophalangeal joints (MCP) to ensure natural enveloping for both cylinder and sphere-like objects. A force-sensing resistor (FSR) is adopted to measure the fingertip force of each finger. Experiments show that this type of structure design provides the hand with excellent dexterity, as the added abduction ensures natural enveloping grasp gestures for both cylinder and sphere-like objects. Moreover, a myoelectric control paradigm is implemented in the control system to demonstrate the feasibility.

On Policy Learning Robust to Irreversible Events: An Application to Robotic In-Hand Manipulation

In this letter, we present an approach for learning in-hand manipulation skills with a low-cost, underactuated prosthetic hand in the presence of irreversible events. Our approach combines reinforcement learning based on visual perception with low-level reactive control based on tactile perception, which aims to avoid slipping. The objective of the reinforcement learning level consists not only in fulfilling the in-hand manipulation goal, but also in minimizing the intervention of the tactile reactive control. This way, the occurrence of object slipping during the learning procedure, which we consider an irreversible event, is significantly reduced. When an irreversible event occurs, the learning process is considered failed. We show the performance in two tasks, which consist in reorienting a cup and a bottle only using the fingers. The experimental results show that the proposed architecture allows reaching the goal in the Cartesian space and reduces significantly the occurrence of object slipping during the learning procedure. Moreover, without the proposed synergy between reactive control and reinforcement learning it was not possible to avoid irreversible events and, therefore, to learn the task.

Prototyping of EMG-Controlled Prosthetic Hand with Sensory System

This paper presents a highly integrated underactuated prosthetic hand equipped with feedback system for performing man-machine interference. The prosthetic hand is composed of five fingers. The hand is actuated by six DC motors, one for each finger plus one for thumb opposition. Motors are inside the palm, while sensors spread all over the construction. The integrated control system is consist of motion control subsystem and sensory subsystem. The motion control subsystem is crucial as the sensory subsystem for both the amputee using prosthetic hand and its control algorithms. Thanks to numerous sensors it is possible to achieve better controlability of phalanges and, especially, the fingertip. For getting the knowledge of grasping force of the prosthetic hand a sensory feedback system between amputee and device is proposed. Force sensor transmits the data about force of grasp to controller, potentiometers and hall effect sensors transmit information about phalanx position and joint angles, while controller convent these signals into vibration intensity of vibromotors, sound signals given by the piezospeaker about hand state. In addition, visual information helps amputee to control the prosthetic hand. Vibromotors located on the surface of amputee arm in special wristband. Thus data input consisting of 3 independent channels of information, makes the control of the hand much easier. Thanks to vibration signals the amputee is able to feel how strong he hold a object. At the end of this paper, the control system is described.

파지성능 평가에 기반한 의수용 핸드의 설계 개선

파지성능 평가에 기반한 의수용 핸드의 설계 개선

Underactuated anthropomorphic hands: Actuation strategies for a better functionality

This paper aims to analyze the number of actuators as well as the actuation strategy for underactuated prosthetic hands. Two comprehensive analyses were performed for this purpose. 16 possible actuation strategies in five categories of one to five actuators were defined. Based on these 16 strategies two analyses were performed: grasp diversity and grasp functionality. In the first analysis, we defined a performance metric based on all possible grasps by the human hand, while in the second analysis only the top grasps with the highest frequency of usage were considered. By comparing the performance of these strategies we obtained some interesting results regarding the best actuation strategies for the under-actuated anthropomorphic hands. Such study can be useful for designers in the early stages of designing a prosthetic terminal, for deciding the number of actuators and how such actuators are allocated to the DOFs of the hand. In other words, this study shows which joints of the hands should be coupled together and driven by a single actuator, in order to get the best performance with minimum number of actuators. This is important for developing hands, which have a small number of actuators (i.e. less than 5 actuators), and thus benefit from a simple electromechanical structure.

A Fuzzy PID Control Method for the Grasping Force of an Underactuated Prosthetic Hand

The prosthetic hand which is the auxiliary equipment of the disabled people in the daily life must ensure stable grasping. Therefore, grasping force control with high accuracy and fast response is the most significant demand. With a conventional PID control, nonlinear dynamic and modeling error of prosthetic hand highly affect the control performance, causing deviation of desired force and slow response. A fuzzy PID control strategy is proposed for eliminating the influence of modeling error and implementing the grasping force control. The PID controller parameters are tuned automatically, on-line, to improve the control performance of the prosthetic hand system. The simulation and experimental results are presented to demonstrate the reliability and effectiveness of the proposed control scheme.

Dynamic Modeling and Analysis of Underactuated Prosthetic Hand

Based on the kinematic equation of index finger, the trajectory space of fingertip is analyzed, and the structural parameters of underactuated prosthetic hand have been optimized by ADAMS, which compare the trajectory space with the index-finger. Using the modeling methods of Lagrange dynamics equation, the dynamic model is established for the three-joint underactuated prosthetic finger, whose kinematic and dynamic characteristics also are analyzed. Finally, by the construction of the virtual prototype and its introduction into ADAMS for the dynamics simulation, the correctness of kinematics and dynamics model is verified by the dynamics simulation of virtual prototype.

Evaluation of a Neural Network-Based Control Strategy for a Cost-Effective Externally-Powered Prosthesis

ABSTRACT This paper presents a control strategy that compensates for the nonlinearity in the inexpensive sensors and hardware of a cost effective prosthetic hand. The control strategy uses neural network-based force control and sensory feedback to detect disturbance induced by slippage. The neural network approach is chosen over other nonlinear models because it is easy to implement and it offered the additional advantage of having its parameters easily adjusted over the life span of the device. The proposed strategy was evaluated on a functional multi-digit underactuated prosthetic hand. The initial and incremental forces exerted from each finger were adjusted to balance the amount of disturbance and the deformation of the objects. Experiments were conducted to test the performance of the protocol in situations encountered in activities of daily living. The displacement of each object under three grasping configurations was measured as a performance criterion while the object's mass was changed. The results showed that with the adjusted parameters for each grasping configuration, the control strategy was able to detect the dynamic changes in mass of the object and was also able to successfully adjust the grasping force before the object drops from the hand.

A Novel Approach for Classification of Underactuated Mechanism in Myoelectric Hand

Concept of underactuation makes it possible to create such robotic hands that automatically adapt to the shape of the grasped object without using a complex control system or a large number of actuators. In underactuated hand prostheses, depending upon control strategy used, one can get more and more degree of freedoms (DOFs) to make its prosthetic device more versatile and easy to control. In spite of all the great work done by the researchers on underactuated prosthetic hands, no one has given any relationship between the number of motors (or actuators) and the number of degree of freedoms (DOFs). This novel concept named as “Coefficient of UAM” (CoUAM) is “the ratio between numbers of motors to the number of DOFs”. By reviewing various known studies, CoUAM of randomly selected prosthetic hands is calculated separately and analyzed merits/demerits, cost, weight, appearance, ease of controllability and their functionality to make this approach more objective and useful for the future researchers. Hence target of this paper is to assess a Coefficient of UAM (CoUAM) of different types of prostheses available and then classify them into red, green and yellow zones.

Task-Based Method for Designing Underactuated Mechanisms

In this paper we introduce a task-based method for designing underactuated multi-joint prosthetic hands for specific grasping tasks. The designed robotic hands or prosthetic hands contain fewer independent actuators than joints. We chose a few specific grasping tasks that are frequently repeated in everyday life and analysed joint motions of the hand during the completion of each task and the level of participation of each joint. The information was used for the synthesis of dedicated underactuated mechanisms that can operate in a low dimensional task coordinate space. We propose two methods for reducing the actuators' number. The kinematic parameters of the synthesized mechanism are determined by using a numerical approach. In this study the joint angles of the synthesized hand are considered as linearly dependent on the displacements of the actuators. We introduced a special error index that allowed us to compare the original trajectory and the trajectory performed by the synthesized mechanism, and to select the kinematic parameters of the new kinematic structure as a way to reduce the error. The approach allows the design of simple gripper mechanisms with good accuracy for the preliminary defined tasks.

Principal components analysis based control of a multi-DoF underactuated prosthetic hand.

BackgroundFunctionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user.MethodsA Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand) with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs). Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control.ResultsTrials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture) may be achieved.ConclusionsThis work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.

On the Shared Control of an EMG-Controlled Prosthetic Hand: Analysis of User–Prosthesis Interaction

An anthropomorphic underactuated prosthetic hand, endowed with position and force sensors and controlled by means of myoelectric commands, is used to perform experiments of hierarchical shared control. Three different hierarchical control strategies combined with a vibrotactile feedback system have been developed and tested by able-bodied subjects through grasping tasks used in activities of daily living (ADLs). The first goal is to find a good tradeoff between good grasping capabilities and low attention required by the user to complete grasping tasks, without addressing advanced algorithm for electromyographic processing. The second goal is to understand whether a vibrotactile feedback system is subjectively or objectively useful and how it changes users' performance. Experiments showed that users were able to successfully operate the device in the three control strategies, and that the grasp success increased with more interactive control. Practice has proven that when too much effort is required, subjects do not do their best, preferring, instead, a less-interactive control strategy. Moreover, the experiments showed that when grasping tasks are performed under visual control, the enhanced proprioception offered by a vibrotactile system is practically not exploited. Nevertheless, in subjective opinion, feedback seems to be quite important.