Posts Tagged Hand exoskeleton
[ARTICLE] Advanced Myoelectric Control for Robotic Hand-Assisted Training: Outcome from a Stroke Patient – Full Text
A hand exoskeleton driven by myoelectric pattern recognition was designed for stroke rehabilitation. It detects and recognizes the user’s motion intent based on electromyography (EMG) signals, and then helps the user to accomplish hand motions in real time. The hand exoskeleton can perform six kinds of motions, including the whole hand closing/opening, tripod pinch/opening, and the “gun” sign/opening. A 52-year-old woman, 8 months after stroke, made 20×2-hour visits over 10 weeks to participate in robot-assisted hand training. Though she was unable to move her fingers on her right hand before the training, EMG activities could be detected on her right forearm. In each visit, she took 4×10-minute robot-assisted training sessions, in which she repeated the aforementioned six motion patterns assisted by our intent-driven hand exoskeleton. After the training, her grip force increased from 1.5 kg to 2.7 kg, her pinch force increased from 1.5 kg to 2.5 kg, her score of Box & Block test increased from 3 to 7, her score of Fugl-Meyer (Part C) increased from 0 to 7, her hand function increased from Stage 1 to Stage 2 in Chedoke-McMaster assessment. The results demonstrate the feasibility of robot-assisted training driven by myoelectric pattern recognition after stroke.
Robot-assisted upper limb training is considered to be more efficient (1) and economic (2) than conventional therapy in neurorehabilitation. Controlling the robot with the user’s own electromyography (EMG) signals connects the user’s intended motion and his actual movements. It can therefore enhance therapeutic effects and promote motor learning (3–5). Various EMG-driven robots and exoskeletons have been developed for neurorehabilitation (6–8), primarily based on one-to-one mapping, which typically maps one channel of EMG signal to a corresponding single degree-of-freedom (DOF) or variable such as speed and torque using a conventional “on-off” or proportional strategy. Robots based on such control strategy work well on training joints with only a few DOFs such as elbow and wrist. However, a human hand has up to 27 DOFs (9) and is controlled by complex temporal and spatial coordination of multiple muscles. It is therefore not feasible to regain hand dexterity through conventional control strategies. Myoelectric pattern-recognition techniques have been developed to extract motion intentions from EMG signals (10, 11). The extracted intentions can then be used to control a multiple-DOF robot such as a prosthesis (12). Previous studies have also shown that motion intentions can still be extracted after neurological impairment (13–15). We therefore developed an intent-driven hand training system. The system employs an exoskeleton hand, which is controlled by myoelectric pattern recognition. As soon as the user’s intention is detected (usually within 250 ms), the system is able to assist to accomplish the intended motions (16).
A 52-year-old woman participated in this robotic hand-assisted training 8 months after stroke. She was right-handed before stroke and had hemiplegia on her right side after her stroke. She was able to walk independently with an ankle foot orthosis but had difficulties in moving her right arm. Her fingers were flexed naturally. She was unable to move any of the fingers on her right hand, but EMG signals were able to be recorded from her forearm. Her Fugl–Meyer score (Part A–D, max 66) was 16, with a 0 in Part C (Hand, max 14). She had no pain when her whole hand was passively opened or closed. She did not receive any other hand or upper limb therapies while participating in this study. During her visits, she was able to understand and follow all the instructions.
The exoskeleton hand, Hand of Hope (Rehab-Robotics, Hong Kong), was used in this study to help the subject move her hand (Figure 1). The exoskeleton hand has five individual fingers. Each finger is actuated by a linear actuator that can pull and push linearly. The mechanical design of the fingers converts these linear movements into the rotations of a virtual metacarpophalangeal (MCP) joint and a virtual proximal interphalangeal (PIP) joint. Both joints rotate together to help the hand perform closing and opening movements (7). The motion range is 55° and 65° for MCP and PIP joints, respectively. The subject’s palm and five fingers are fixed to the exoskeleton hand with Velcro belts. Each finger can be bent or straightened individually by the exoskeleton hand. The exoskeleton hand stands on a brace, which also supports the subject’s forearm, so that the subject can be totally relaxed when attached to the exoskeleton. The exoskeleton hand used in this study can perform six different motion patterns, including hand closing (HC); hand opening (HO); thumb, index, and middle fingers closing (TIMC or tripod pinch); thumb, index, and middle fingers opening; middle, ring, and little fingers closing (MRLC or the “gun” sign); and middle, ring, and little fingers opening. The exoskeleton hand can perform HC, TIMC, or MRLC when it is open. However, after performing any one from these three patterns, it can only return to the original open status (e.g., there is no direct way from the “tripod pinch” to the “gun” sign).
The hand is an organ of grasping as well as sensation, communication, and fine dexterity. Since the 80’s, many researchers have been attempting to develop robotic devices aiming at replicating the functions of the human hand in the fields of industrial robotics, tele-manipulation, humanoid robotics, and upper limb prosthetics.
A special kind of robotic hand is the hand exoskeleton, that is directly attached to the human hand with the aim of providing assistance in motion/power generation. Hand exoskeletons are increasingly widespread in robot-based rehabilitation of patients suffering from different pathologies (in particular neurological diseases).
This paper reviews the state-of-the-art of hand exoskeletons developed for rehabilitation purposes and proposes a new systematic classification according to three key points related to the kinematic architecture: (i) mobility of a single finger exoskeleton, (ii) number of physical connections between the exoskeleton and the human finger phalanges, and (iii) way of integration of the exoskeleton mechanism with the human parts.
The discussion based upon the classification can be helpful to understand the reasons of adopting certain solutions for specific applications and the advantages and drawbacks of different designs, based on the work already done by other researchers.
The final purpose of the proposed classification is then to provide guidelines useful for the design of new hand exoskeletons on the basis of a systematic analysis. As an example, the solution designed, manufactured and clinically tested by the authors is reported.
[ARTICLE] Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation – Full Text PDF/HTML
Vision-based Pose Estimation (VPE) represents a non-invasive solution to allow a smooth and natural interaction between a human user and a robotic system, without requiring complex calibration procedures. Moreover, VPE interfaces are gaining momentum as they are highly intuitive, such that they can be used from untrained personnel (e.g., a generic caregiver) even in delicate tasks as rehabilitation exercises.
In this paper, we present a novel master–slave setup for hand telerehabilitation with an intuitive and simple interface for remote control of a wearable hand exoskeleton, named HX. While performing rehabilitative exercises, the master unit evaluates the 3D position of a human operator’s hand joints in real-time using only a RGB-D camera, and commands remotely the slave exoskeleton. Within the slave unit, the exoskeleton replicates hand movements and an external grip sensor records interaction forces, that are fed back to the operator-therapist, allowing a direct real-time assessment of the rehabilitative task.
Experimental data collected with an operator and six volunteers are provided to show the feasibility of the proposed system and its performances. The results demonstrate that, leveraging on our system, the operator was able to directly control volunteers’ hands movements.
[Abstract] A novel motion-coupling design for a jointless tendon-driven finger exoskeleton for rehabilitation
We have designed a new jointless tendon-driven exoskeleton plan for the human hand that provides a correct and stable motion sequence while keeping the structure lightweight, compact and portable. Before the development, anatomy analysis and a kinematics study of the human finger were performed, and bending angle relationships among the metacarpophalangeal (MCP), proximal interphalangeal (PIP) and distal interphalangeal (DIP) joints were analyzed. Detailed implementation is discussed, including the basic theory of the joint motion coupling method, related formula derivations and mechanical design of an experimental device. An experimental setup was built, and series of experiments was conducted to examine and evaluate the developed joint motion coupling plan.The results indicated that the new plan worked correctly as desired, that an incorrect finger motion sequence did not occur and that the new coupled tendon driven plan can drive finger bending as naturally as a human. The compactness and light weight of the entire structure of the device means that its parts can be arranged for a hand glove or fingerstall more easily than most bar-linkage exoskeleton structures.
[ARTICLE] An index finger exoskeleton with series elastic actuation for rehabilitation: Design, control and performance characterization
Rehabilitation of the hands is critical for the restoration of independence in activities of daily living for individuals exhibiting disabilities of the upper extremities. There is initial evidence that robotic devices with force-control-based strategies can help in effective rehabilitation of human limbs. However, to the best of our knowledge, none of the existing hand exoskeletons allow for accurate force or torque control.
In this work, we present a novel index finger exoskeleton with Bowden-cable-based series elastic actuation allowing for bidirectional torque control of the device with high backdrivability and low reflected inertia. We present exoskeleton and finger joint torque controllers along with an optimization-based offline parameter estimator. Finally, we carry out tests with the developed prototype to characterize its kinematics, dynamics, and controller performance.
Results show that the device preserves the characteristics of natural motion of finger and can be controlled to achieve both exoskeleton and finger joint torque control. Finally, dynamic transparency tests show that the device can be controlled to offer minimal resistance to finger motion. Beyond the present application of the device as a hand rehabilitation exoskeleton, it has the potential to be used as a haptic device for teleoperation.
[ARTICLE] Experiments and kinematics analysis of a hand rehabilitation exoskeleton with circuitous joints – OPEN ACCESS
Aiming at the hand rehabilitation of stroke patients, a wearable hand exoskeleton with circuitous joint is proposed. The circuitous joint adopts the symmetric pinion and rack mechanism (SPRM) with the parallel mechanism. The exoskeleton finger is a serial mechanism composed of three closed-chain SPRM joints in series. The kinematic equations of the open chain of the finger and the closed chains of the SPRM joints were built to analyze the kinematics of the hand rehabilitation exoskeleton.
The experimental setup of the hand rehabilitation exoskeleton was built and the continuous passive motion (CPM) rehabilitation experiment and the test of human-robot interaction force measurement were conducted. Experiment results show that the mechanical design of the hand rehabilitation robot is reasonable and that the kinematic analysis is correct, thus the exoskeleton can be used for the hand rehabilitation of stroke patients.
[ARTICLE] Exo-Glove: A Soft Wearable Robot for the Hand with a Soft Tendon Routing System – Full Text PDF
…This article describes a soft wearable hand robot called the Exo-Glove that uses a soft tendon routing system and an underactuation adaptive mechanism. The proposed system can be used to develop other types of soft wearable robots. The glove part of the system is compact and weighs 194 g.
Results conducted using a healthy subject showed sufficient performance for the execution of daily life activities, namely, a pinch force of 20 N, a wrap grasp force of 40 N, and a maximum grasped object size of 76 mm. Use of an underactuation mechanism enabled the grasping of objects of various shapes without active control.
A subject suffering from paralysis of the hands due to spinal cord injury was able to use the glove to grasp objects of various shapes…
[ARTICLE] Design and development of a hand exoskeleton for rehabilitation following stroke – Full Text PDF
In Australia, a major cause of disability is the stroke and it is the second highest cause of death after coronary heart disease. Studies have predicted that form 2008 to 2017 more than 0.5 million people is likely to suffer from stroke in Australia. In addition, after stroke 88 % of the patients suffer from disability and stays at home.
In this paper, a post stroke therapeutic device has been designed for hand motor function rehabilitation that a stroke survivor can use for bilateral movement practice. Out of twenty-one degrees of freedom of hand fingers, the prototype of the hand exoskeleton allowed fifteen degrees of freedom. The device is designed to be portable so that the user can engage in other activities while using the device. A prototype of the device is fabricated to provide complete flexion and extension motion of individual fingers of the left hand (impaired hand) based on the movements of the right hand (healthy hand) fingers. In addition, testing of the device on a healthy subject was conducted to validate if the design met the requirements.