A reward–punishment feedback control strategy based on energy information for wrist rehabilitation (original) (raw)
Related papers
ASME/ISCIE 2012 International Symposium on Flexible Automation, 2012
TheraDrive is an effective system for post-stroke upper extremity rehabilitation. This system uses off-the-shelf computer gaming wheels with force feedback to help reduce motor impairment and improve function in the arms of stroke survivors. Preliminary results show that the TheraDrive system lacks a robust mechanical linkage that can withstand the large forces exerted by patients, and it lacks a patient-specific adaptive controller to deliver personalized therapy. It is also not capable of delivering effective therapy to severely low-functioning patients. A new low-cost, high-force haptic robot with a single degree of freedom has been developed to address these concerns. The resulting TheraDrive consists of an actuated hand crank with a compliant transmission. Actuation is provided by a brushed DC motor, geared to output up to 23 kgf at the end effector. To enable a human to interact with this system safely, a special compliant element was developed to double as a failsafe torque limiter. A set of strain gauges in the handle of the crank are used to determine the interaction forces between human and robot for use by the robot's impedance controller. The impedance controller is used to render a one-dimensional force field that attracts or repels the end effector from a moving target point that the human must track during therapy exercises. As exercises are performed, an adaptive controller monitors patient performance and adjusts the force field accordingly. This allows the robot to compen-* Address all correspondence to this author. sate for gravity, variable mechanical advantage, limited range of motion, and other factors. More importantly, the adaptive controller ensures that exercises are difficult but doable, which is important for maintaining patient motivation. Experiments with a computer model of human and robot show the adaptive controller's ability to maintain difficulty of exercises after a period of initial calibration.
A Nonlinear Adaptive Compliance Controller for Rehabilitation
IEEJ Journal of Industry Applications, 2016
In the last few decades, the increase in the worldwide elderly population and the progress in the treatment of severe and chronic pathologies have led to a growing demand for rehabilitation therapies. Meanwhile, rehabilitation robotics has started to grow and to evolve, in order to develop suitable robotics devices and control strategies to better assist patients during training and to promote rehabilitation processes. In particular, some control strategies are designed to assist patients in completing the desired movements while applying the minimum force necessary. As a result, an "assist-as-needed" behavior can be achieved. A novel nonlinear adaptive compliance controller, that aims to achieve such "assist-as-needed" behavior, has been developed and is presented in this paper. In addition to promote the active participation of patients, the proposed control also provides a tool to estimate and evaluate patient's state and therapeutic improvements. The proposed controller is obtained by appropriately merging a PD (proportional and derivative) control and an adaptive learning control. The latter is driven by the errors made by patients while performing the assigned exercise. As a result, the PD controller parameters are adapted according to different patient injuries and degrees of impairments and may be used to evaluate the improvements during training sessions. The paper presents an overview of the novel control algorithm and some preliminary clinical trials with real patients, demonstrating benefits of the controller.
Comparison of Three Control Strategies for an Upper Arm Rehabilitation Device
2018
The RETRAINER S1 system is an upper limb rehabilitation device designed to be used in repetitive task-oriented training. While the device itself is intrinsically controlled by the wearer, the execution of the training exercises is automatically controlled by a finite-state machine. This contribution discusses three different control strategies tested in a clinical environment.
State-of-the-Art Robotic Devices for Wrist Rehabilitation: Design and Control Aspects
IEEE Transactions on Human-Machine Systems, 2020
Robot assisted physical therapy of the upper limb is becoming popular among the rehabilitation community. The wrist is the second most complicated joint in the upper limb after shoulder in terms of degrees of freedom. Several robotic devices have been developed during the past three decades for wrist joint rehabilitation. Intensive physical therapy and repetitive selfpractice, with objective measurement of performance could be provided by using these wrist rehabilitation robots at a low cost. There has been an increasing trend in the development of wrist rehabilitation robots to provide safe and customized therapy according to the disability level of patients. The mechanical design and control paradigms are two active fields of research undergoing rapid developments in the field of robot assisted wrist rehabilitation. The mechanical design of these robots could be divided into the categories of end-effector based robots and wearable robotic orthoses. The control for these wrist rehabilitation robots could also be divided into the conventional trajectory tracking control mode and the Assist-as-Needed control mode for providing customized robotic assistance. This paper presents a review of the mechanical design and control aspects of wrist rehabilitation robots. Experimental evaluations of these robots with healthy and neurologically impaired are also discussed along with the future directions of research in the design and control domains of wrist rehabilitation robots.
Development of an Arm Rehabilitation System with Different Control Approaches
2017
Stroke rehabilitation plays a vital role for people with limb disability because of stroke attack. Due to gradually increasing medical prices, the cost of rehabilitation devices existed in the hospital and rehab centre are simultaneously increased. These devices also lack the features that help to ease and increase the spirit of patients during the rehabilitation process. Thus, this paper aim to create an arm platform-based for upper limb rehabilitation, where the interactive game features also created by using Unity 2D software for the purpose of motivating patients during the rehabilitation process. The main target is to develop an arm platform, which is focused on proper controller design for the active exercises in early-stage therapy. The performance of the arm platform is examined in term of range of motion. Therefore, it will reduce patient’s pressure during the exercise and gradually improve their agility. In the proper control of the muscle tension, the designed upper limb ...
Design of Smart Robot for Wrist Rehabilitation
International Journal on Smart Sensing and Intelligent Systems
Generally, the rehabilitation process needs a physical interactions between patients and therapists. Based on the principles governing such human-human interactions (HHI), the design of rehabilitation robots received several attempts in order to abstract the HHI in human-robot interaction (HRI). To achieve this goal, the rehabilitation robot should be smart and provides a useful and comprehensive platform to track the patient status. In this paper, a biofeedback-based high fidelity smart robot for wrist rehabilitation is designed. This robot is intended for repetitive exercises without therapist intervention. Hold the two sets of wrist movement: flexion/extension and radial/ulnar derivation. Distinguished by its compact mechanism design, the developed wrist rehabilitation robot (HRR) offers high stiffness with a total absence of any friction and backlash. Based on EMG signal, the smart robot can understand the patient pain degree. Two features extractions are used to estimate the pain level. A fuzzy logic controller is implemented in the LabVIEW-based human-machine interface (HMI) to determine the desired angle and velocity in real time. Parameters and results of each exercise can be stored and operated later in analysis and evolution of patient progress.
Journal of NeuroEngineering and Rehabilitation, 2009
Background: 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).
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2000
Despite distal arm impairment after brain injury is an extremely disabling consequence of neurological damage, most studies on robotic therapy are mainly focused on recovery of proximal upper limb motor functions, routing the major efforts in rehabilitation to shoulder and elbow joints. In the present study we developed a novel therapeutic protocol aimed at restoring wrist functionality in chronic stroke patients. A haptic three DoFs (degrees of freedom) robot has been used to quantify motor impairment and assist wrist and forearm articular movements: flexion/ extension (FE), abduction/adduction (AA), pronation/supination (PS). This preliminary study involved nine stroke patients, from a mild to severe level of impairment. Therapy consisted in ten 1-hour sessions over a period of five weeks. The novelty of the approach was the adaptive control scheme which trained wrist movements with slow oscillatory patterns of small amplitude and progressively increasing bias, in order to maximize the recovery of the active range of motion. The primary outcome was a change in the active RoM (range of motion) for each DoF and a change of motor function, as measured by the Fugl-Meyer assessment of arm physical performance after stroke (FMA). The secondary outcome was the score on the Wolf Motor Function Test (WOLF). The FMA score reported a significant improvement (average of points), revealing a reduction of the upper extremity motor impairment over the sessions; moreover, a detailed component analysis of the score hinted at some degree of motor recovery transfer from the distal, trained parts of the arm to the proximal untrained parts. WOLF showed an improvement of points, highlighting an increase in functional capability for the whole arm. The active RoM displayed a remarkable improvement. Moreover, a three-months follow up assessment reported long lasting benefits in both distal and proximal arm functionalities. The experimental results of this preliminary clinical study provide enough empirical evidence for introducing the novel progressive, adaptive, gentle robotic assistance of wrist movements in the clinical practice, consolidating the evaluation of its efficacy by means of a controlled clinical trial.
IEEE Access, 2020
Demand for robot-assisted therapy has increased at every stage of the neurorehabilitation recovery. This paper presents a controller that is suitable for the assist-as-needed (AAN) training of the wrist when performing the spatial motion. A compact wrist exoskeleton robot is presented to realize the AAN controller. This wrist robot includes series elastic actuators with high torque-to-weight ratios to provide accurate force control required for the AAN controller. In addition to assist-as-needed rehabilitation, the parameters of the AAN controller can be adjusted to deliver passive, active, or resistive rehabilitation. Experimental results demonstrate that the proposed AAN controller can provide the total solution to cover each stage of wrist spatial-motion rehabilitation.
International Journal of Robotic Research, 2008
This paper presents the design, control and performance of a high fidelity four degree-of-freedom wrist exoskeleton robot, RiceWrist, for training and rehabilitation. The RiceWrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension and radial and ulnar deviation in a compact parallel mechanism design with low friction, zero backlash and high stiffness. As compared to other exoskeleton devices, the RiceWrist allows easy measurement of human joint angles and independent kinesthetic feedback to individual human joints. In this paper, joint-space as well as task-space position controllers and an impedance-based force controller for the device are presented. The kinematic performance of the device is characterized in terms of its workspace, singularities, manipulability, backlash and backdrivability. The dynamic performance of RiceWrist is characterized in terms of motor torque output, joint friction, step responses, behavior under closed loop set-point and trajectory tracking control and display of virtual walls. The device is singularity-free, encompasses most of the natural workspace of the human joints and exhibits low friction, zero-backlash and high manipulability, which are kinematic properties that characterize a highquality impedance display device. In addition, the device displays fast, accurate response under position control that matches human actuation bandwidth and the capability to display sufficiently hard contact with little coupling between controlled degrees-of-freedom.