Effect of Tendon Vibration on Hemiparetic Arm Stability in Unstable Workspaces

Sensory stimulation of wrist musculature can enhance stability in the proximal arm and may be a useful therapy aimed at improving arm control post-stroke. Specifically, our prior research indicates tendon vibration can enhance stability during point-to-point arm movements and in tracking tasks. The goal of the present study was to investigate the influence of forearm tendon vibration on endpoint stability, measured at the hand, immediately following forward arm movements in an unstable environment. Both proximal and distal workspaces were tested. Ten hemiparetic stroke subjects and 5 healthy controls made forward arm movements while grasping the handle of a two-joint robotic arm. At the end of each movement, the robot applied destabilizing forces. During some trials, 70 Hz vibration was applied to the forearm flexor muscle tendons. 70 Hz was used as the stimulus frequency as it lies within the range of optimal frequencies that activate the muscle spindles at the highest response rate. Endpoint position, velocity, muscle activity and grip force data were compared before, during and after vibration. Stability at the endpoint was quantified as the magnitude of oscillation about the target position, calculated from the power of the tangential velocity data. Prior to vibration, subjects produced unstable, oscillating hand movements about the target location due to the applied force field. Stability increased during vibration, as evidenced by decreased oscillation in hand tangential velocity

Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis

The study describes the design and development of a single degree-of-freedom haptic robot, Haptic Theradrive, for post-stroke arm rehabilitation for in-home and clinical use. The robot overcomes many of the weaknesses of its predecessor, the TheraDrive system, that used a Logitech steering wheel as the haptic interface for rehabilitation. Although the original TheraDrive system showed success in a pilot study, its wheel was not able to withstand the rigors of use. A new haptic robot was developed that functions as a drop-in replacement for the Logitech wheel. The new robot can apply larger forces in interacting with the patient, thereby extending the functionality of the system to accommodate low-functioning patients. A new software suite offers appreciably more options for tailored and tuned rehabilitation therapies. In addition to describing the design of the hardware and software, the paper presents the results of simulation and experimental case studies examining the system\u27s performance and usability

Training modalities in robot-mediated upper limb rehabilitation in stroke : A framework for classification based on a systematic review

© 2014 Basteris et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The work described in this manuscript was partially funded by the European project ‘SCRIPT’ Grant agreement no: 288698 (http://scriptproject.eu). SN has been hosted at University of Hertfordshire in a short-term scientific mission funded by the COST Action TD1006 European Network on Robotics for NeuroRehabilitationRobot-mediated post-stroke therapy for the upper-extremity dates back to the 1990s. Since then, a number of robotic devices have become commercially available. There is clear evidence that robotic interventions improve upper limb motor scores and strength, but these improvements are often not transferred to performance of activities of daily living. We wish to better understand why. Our systematic review of 74 papers focuses on the targeted stage of recovery, the part of the limb trained, the different modalities used, and the effectiveness of each. The review shows that most of the studies so far focus on training of the proximal arm for chronic stroke patients. About the training modalities, studies typically refer to active, active-assisted and passive interaction. Robot-therapy in active assisted mode was associated with consistent improvements in arm function. More specifically, the use of HRI features stressing active contribution by the patient, such as EMG-modulated forces or a pushing force in combination with spring-damper guidance, may be beneficial.Our work also highlights that current literature frequently lacks information regarding the mechanism about the physical human-robot interaction (HRI). It is often unclear how the different modalities are implemented by different research groups (using different robots and platforms). In order to have a better and more reliable evidence of usefulness for these technologies, it is recommended that the HRI is better described and documented so that work of various teams can be considered in the same group and categories, allowing to infer for more suitable approaches. We propose a framework for categorisation of HRI modalities and features that will allow comparing their therapeutic benefits.Peer reviewedFinal Published versio

Effects of Wrist Tendon Vibration on Targeted Upper-Arm Movements in Poststroke Hemiparesis

Background. Impaired motor control of the upper extremity after stroke may be related to lost sensory, motor, and integrative functions of the brain. Artificial activation of sensory afferents might improve control of movement by adding excitatory drive to sensorimotor control structures. The authors evaluated the effect of wrist tendon vibration (TV) on paretic upper-arm stability during point-to-point planar movements. Methods. TV (70 Hz) was applied to the forearm wrist musculature of 10 hemiparetic stroke patients as they made center-out planar arm movements. End-point stability, muscle activity, and grip pressure were compared as patients stabilized at the target position for trials completed before, during, and after the application of the vibratory stimulus. Results. Prior to vibration, hand position fluctuated as participants attempted to maintain the hand at the target after movement termination. TV improved arm stability, as evidenced by decreased magnitude of hand tangential velocity at the target. Improved stability was accompanied by a decrease in muscle activity throughout the arm as well as a mean decrease in grip pressure. Conclusions. These results suggest that vibratory stimulation of the distal wrist musculature enhances stability of the proximal arm and can be studied further as a mode for improving end-point stability during reaching in hemiparetic patients

Performance adaptive training control strategy for recovering wrist movements in stroke patients: a preliminary, feasibility study

<p>Abstract</p> <p>Background</p> <p>In the last two decades robot training in neuromotor rehabilitation was mainly focused on shoulder-elbow movements. Few devices were designed and clinically tested for training coordinated movements of the wrist, which are crucial for achieving even the basic level of motor competence that is necessary for carrying out ADLs (activities of daily life). Moreover, most systems of robot therapy use point-to-point reaching movements which tend to emphasize the pathological tendency of stroke patients to break down goal-directed movements into a number of jerky sub-movements. For this reason we designed a wrist robot with a range of motion comparable to that of normal subjects and implemented a self-adapting training protocol for tracking smoothly moving targets in order to facilitate the emergence of smoothness in the motor control patterns and maximize the recovery of the normal RoM (range of motion) of the different DoFs (degrees of Freedom).</p> <p>Methods</p> <p>The IIT-wrist robot is a 3 DoFs light exoskeleton device, with direct-drive of each DoF and a human-like range of motion for Flexion/Extension (FE), Abduction/Adduction (AA) and Pronation/Supination (PS). Subjects were asked to track a variable-frequency oscillating target using only one wrist DoF at time, in such a way to carry out a progressive splinting therapy. The RoM of each DoF was angularly scanned in a staircase-like fashion, from the "easier" to the "more difficult" angular position. An Adaptive Controller evaluated online performance parameters and modulated both the assistance and the difficulty of the task in order to facilitate smoother and more precise motor command patterns.</p> <p>Results</p> <p>Three stroke subjects volunteered to participate in a preliminary test session aimed at verify the acceptability of the device and the feasibility of the designed protocol. All of them were able to perform the required task. The wrist active RoM of motion was evaluated for each patient at the beginning and at the end of the test therapy session and the results suggest a positive trend.</p> <p>Conclusion</p> <p>The positive outcomes of the preliminary tests motivate the planning of a clinical trial and provide experimental evidence for defining appropriate inclusion/exclusion criteria.</p

Upper extremity rehabilitation using interactive virtual environments

Stroke affects more than 700,000 people annually in the U.S. It is the leading cause of major disability. Recovery of upper extremity function remains particularly resistant to intervention, with 80% to 95% of persons demonstrating residual upper extremity impairments lasting beyond six months after the stroke. The NJIT Robot Assistive Virtual Rehabilitation (NJIT-RAVR) system has been developed to study optimal strategies for rehabilitation of arm and hand function. Several commercial available devices, such as HapticMaster™, Cyberglove™, trakSTAR™ and Cybergrasp™, have been integrated and 11 simulations were developed to allow users to interact with virtual environments. Visual interfaces used in these simulations were programmed either in Virtools or in C++ using the Open GL library. Stereoscopic glasses were used to enhance depth perception and to present movement targets to the subjects in a 3-dimensional stereo working space. Adaptive online and offline algorithms were developed that provided appropriate task difficulty to optimize the outcomes. A pilot study was done on four stroke patients and two children with cerebral palsy to demonstrate the usability of this robot-assisted VR system. The RAVR system performed well without unexpected glitches during two weeks of training. No subjects experienced side effects such as dizziness, nausea or disorientation while interacting with the virtual environment. Each subject was able to finish the training, either with or without robotic adaptive assistance. To investigate optimal therapeutic approaches, forty stroke subjects were randomly assigned to two groups: Hand and Arm training Together (HAT) and Hand and Arm training Separately (HAS). Each group was trained in similar virtual reality training environments for three hours a day, four days a week for two weeks. In addition, twelve stroke subjects participated as a control group. They received conventional rehabilitation training of similar intensity and duration as the HAS and HAT groups. Clinical outcome measurements included the Jebsen Test of Hand Function, the Wolf Motor Function Test, and the ReachGrasp test. Secondary outcome measurements were calculated from kinematic and kinetic data collected during training in real time at 100 Hz. Both HAS and HAT groups showed significant improvement in clinical and kinematic outcome measurements. Clinical improvement compared favorably to the randomized clinical trials reported in the literature. However, there was no significant improvement difference between the two groups. Subjects from the control group improved in clinical measurements and in the ReachGrasp test. Compared to the control group, the ReachGrasp test showed a larger increase in movement speed during reaching and in the efficiency of lifting an object from the table in the combined HAS and HAT group. The NJIT-RAVR system was further modified to address the needs of children with hemiplegia due to Cerebral Palsy. Thirteen children with cerebral palsy participated in the total of nine sessions of one hour training that lasted for three weeks. Nine of the children were trained using the RAVR system alone, and another four had training with the combined Constraint-Induced Movement therapy and RAVR therapy. As a group, the children demonstrated improved performance across measurements of the Arm Range of Motion (AROM), motor function, kinematics and motor control. While subjects\u27 responses to the games varied, they performed each simulation while maintaining attention sufficient to improve in both robotic task performance and in measures of motor function

Development of a hybrid robotic system based on an adaptive and associative assistance for rehabilitation of reaching movement after stroke

Stroke causes irreversible neurological damage. Depending on the location and the size of this brain injury, different body functions could result affected. One of the most common consequences is motor impairments. The level of motor impairment affectation varies between post-stroke subjects, but often, it hampers the execution of most activities of daily living. Consequently, the quality of life of the stroke population is severely decreased. The rehabilitation of the upper-limb motor functions has gained special attention in the scientific community due the poor reported prognosis of post-stroke patients for recovering normal upper-extremity function after standard rehabilitation therapy. Driven by the advance of technology and the design of new rehabilitation methods, the use of robot devices, functional electrical stimulation and brain-computer interfaces as a neuromodulation system is proposed as a novel and promising rehabilitation tools. Although the uses of these technologies present potential benefits with respect to standard rehabilitation methods, there still are some milestones to be addressed for the consolidation of these methods and techniques in clinical settings. Mentioned evidences reflect the motivation for this dissertation. This thesis presents the development and validation of a hybrid robotic system based on an adaptive and associative assistance for rehabilitation of reaching movements in post-stroke subjects. The hybrid concept refers the combined use of robotic devices with functional electrical stimulation. Adaptive feature states a tailored assistance according to the users’ motor residual capabilities, while the associative term denotes a precise pairing between the users’ motor intent and the peripheral hybrid assistance. The development of the hybrid platform comprised the following tasks: 1. The identification of the current challenges for hybrid robotic system, considering twofold perspectives: technological and clinical. The hybrid systems submitted in literature were critically reviewed for such purpose. These identified features will lead the subsequent development and method framed in this work. 2. The development and validation of a hybrid robotic system, combining a mechanical exoskeleton with functional electrical stimulation to assist the execution of functional reaching movements. Several subsystems are integrated within the hybrid platform, which interact each other to cooperatively complement the rehabilitation task. Complementary, the implementation of a controller based on functional electrical stimulation to dynamically adjust the level of assistance is addressed. The controller is conceived to tackle one of the main limitations when using electrical stimulation, i.e. the highly nonlinear and time-varying muscle response. An experimental procedure was conducted with healthy and post-stroke patients to corroborate the technical feasibility and the usability evaluation of the system. 3. The implementation of an associative strategy within the hybrid platform. Three different strategies based on electroencephalography and electromyography signals were analytically compared. The main idea is to provide a precise temporal association between the hybrid assistance delivered at the periphery (arm muscles) and the users’ own intention to move and to configure a feasible clinical setup to be use in real rehabilitation scenarios. 4. Carry out a comprehensive pilot clinical intervention considering a small cohort of patient with post-stroke patients to evaluate the different proposed concepts and assess the feasibility of using the hybrid system in rehabilitation settings. In summary, the works here presented prove the feasibility of using the hybrid robotic system as a rehabilitative tool with post-stroke subjects. Moreover, it is demonstrated the adaptive controller is able to adjust the level of assistance to achieve successful tracking movement with the affected arm. Remarkably, the accurate association in time between motor cortex activation, represented through the motor-related cortical potential measured with electroencephalography, and the supplied hybrid assistance during the execution of functional (multidegree of freedom) reaching movement facilitate distributed cortical plasticity. These results encourage the validation of the overall hybrid concept in a large clinical trial including an increased number of patients with a control group, in order to achieve more robust clinical results and confirm the presented herein.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Ramón Ceres Ruiz.- Secretario: Luis Enrique Moreno Lorente.- Vocal: Antonio Olivier

Robotics for rehabilitation of hand movement in stroke survivors

This article aims to give an overall review of research status in hand rehabilitation robotic technology, evaluating a number of devices. The main scope is to explore the current state of art to help and support designers and clinicians make better choices among varied devices and components. The review also focuses on both mechanical design, usability and training paradigms since these parts are interconnected for an effective hand recovery. In order to study the rehabilitation robotic technology status, the devices have been divided in two categories: end-effector robots and exoskeleton devices. The end-effector robots are more flexible than exoskeleton devices in fitting the different size of hands, reducing the setup time and increasing the usability for new patients. They suffer from the control of distal joints and haptic aspects of object manipulation. In this way, exoskeleton devices may represent a new opportunity. Nevertheless their design is complex and a deep investigation of hand biomechanics and physical human–robot interaction is required. The main hand exoskeletons have been developed in the last decade and the results are promising demonstrated by the growth of the commercialized devices. Finally, a discussion on the complexity to define which design is better and more effective than the other one is summarized for future investigations

Parametric motion control of robotic arms: A biologically based approach using neural networks

A neural network based system is presented which is able to generate point-to-point movements of robotic manipulators. The foundation of this approach is the use of prototypical control torque signals which are defined by a set of parameters. The parameter set is used for scaling and shaping of these prototypical torque signals to effect a desired outcome of the system. This approach is based on neurophysiological findings that the central nervous system stores generalized cognitive representations of movements called synergies, schemas, or motor programs. It has been proposed that these motor programs may be stored as torque-time functions in central pattern generators which can be scaled with appropriate time and magnitude parameters. The central pattern generators use these parameters to generate stereotypical torque-time profiles, which are then sent to the joint actuators. Hence, only a small number of parameters need to be determined for each point-to-point movement instead of the entire torque-time trajectory. This same principle is implemented for controlling the joint torques of robotic manipulators where a neural network is used to identify the relationship between the task requirements and the torque parameters. Movements are specified by the initial robot position in joint coordinates and the desired final end-effector position in Cartesian coordinates. This information is provided to the neural network which calculates six torque parameters for a two-link system. The prototypical torque profiles (one per joint) are then scaled by those parameters. After appropriate training of the network, our parametric control design allowed the reproduction of a trained set of movements with relatively high accuracy, and the production of previously untrained movements with comparable accuracy. We conclude that our approach was successful in discriminating between trained movements and in generalizing to untrained movements