Michelle J. Johnson

Advances in upper limb stroke rehabilitation: a technology push.

Strokes affect thousands of people worldwide leaving sufferers with severe disabilities affecting their daily activities. In recent years, new rehabilitation techniques have emerged such as constraint-induced therapy, biofeedback therapy and robot-aided therapy. In particular, robotic techniques allow precise recording of movements and application of forces to the affected limb, making it a valuable tool for motor rehabilitation. In addition, robot-aided therapy can utilise visual cues conveyed on a computer screen to convert repetitive movement practice into an engaging task such as a game. Visual cues can also be used to control the information sent to the patient about exercise performance and to potentially address psychosomatic variables influencing therapy. This paper overviews the current state-of-the-art on upper limb robot-mediated therapy with a focal point on the technical requirements of robotic therapy devices leading to the development of upper limb rehabilitation techniques that facilitate reach-to-touch, fine motor control, whole-arm movements and promote rehabilitation beyond hospital stay. The reviewed literature suggest that while there is evidence supporting the use of this technology to reduce functional impairment, besides the technological push, the challenge ahead lies on provision of effective assessment of outcome and modalities that have a stronger impact transferring functional gains into functional independence.

Potential of a suite of robot/computer-assisted motivating systems for personalized, home-based, stroke rehabilitation

BackgroundThere is a need to improve semi-autonomous stroke therapy in home environments often characterized by low supervision of clinical experts and low extrinsic motivation. Our distributed device approach to this problem consists of an integrated suite of low-cost robotic/computer-assistive technologies driven by a novel universal access software framework called UniTherapy. Our design strategy for personalizing the therapy, providing extrinsic motivation and outcome assessment is presented and evaluated.MethodsThree studies were conducted to evaluate the potential of the suite. A conventional force-reflecting joystick, a modified joystick therapy platform (TheraJoy), and a steering wheel platform (TheraDrive) were tested separately with the UniTherapy software. Stroke subjects with hemiparesis and able-bodied subjects completed tracking activities with the devices in different positions. We quantify motor performance across subject groups and across device platforms and muscle activation across devices at two positions in the arm workspace.ResultsTrends in the assessment metrics were consistent across devices with able-bodied and high functioning strokes subjects being significantly more accurate and quicker in their motor performance than low functioning subjects. Muscle activation patterns were different for shoulder and elbow across different devices and locations.ConclusionThe Robot/CAMR suite has potential for stroke rehabilitation. By manipulating hardware and software variables, we can create personalized therapy environments that engage patients, address their therapy need, and track their progress. A larger longitudinal study is still needed to evaluate these systems in under-supervised environments such as the home.

Development of ADLER: The Activities of Daily Living Exercise Robot

Robot-assisted therapy devices are being used in the physical and neurological rehabilitation of persons after stroke, which is the leading cause of disability among adults in the United States. Motor gains after robot-assisted therapy may not transfer to functioning on activities of daily living. It is conceivable that carryover after training may be improved through the use of training activities that are patient-centered, engaging and focused on daily living activities. We have developed the activities of daily living exercise robot (ADLER) stroke training environment to test this idea. This environment permits the consistent and repeated practice of daily living tasks such as drinking. This paper describes the ADLER training system

Quantifying kinematics of purposeful movements to real, imagined, or absent functional objects: Implications for modelling trajectories for robot-assisted ADL tasks**

BackgroundRobotic therapy is at the forefront of stroke rehabilitation. The Activities of Daily Living Exercise Robot (ADLER) was developed to improve carryover of gains after training by combining the benefits of Activities of Daily Living (ADL) training (motivation and functional task practice with real objects), with the benefits of robot mediated therapy (repeatability and reliability). In combining these two therapy techniques, we seek to develop a new model for trajectory generation that will support functional movements to real objects during robot training. We studied natural movements to real objects and report on how initial reaching movements are affected by real objects and how these movements deviate from the straight line paths predicted by the minimum jerk model, typically used to generate trajectories in robot training environments. We highlight key issues that to be considered in modelling natural trajectories.MethodsMovement data was collected as eight normal subjects completed ADLs such as drinking and eating. Three conditions were considered: object absent, imagined, and present. This data was compared to predicted trajectories generated from implementing the minimum jerk model. The deviations in both the plane of the table (XY) and the saggital plane of torso (XZ) were examined for both reaches to a cup and to a spoon. Velocity profiles and curvature were also quantified for all trajectories.ResultsWe hypothesized that movements performed with functional task constraints and objects would deviate from the minimum jerk trajectory model more than those performed under imaginary or object absent conditions. Trajectory deviations from the predicted minimum jerk model for these reaches were shown to depend on three variables: object presence, object orientation, and plane of movement. When subjects completed the cup reach their movements were more curved than for the spoon reach. The object present condition for the cup reach showed more curvature than in the object imagined and absent conditions. Curvature in the XZ plane of movement was greater than curvature in the XY plane for all movements.ConclusionThe implemented minimum jerk trajectory model was not adequate for generating functional trajectories for these ADLs. The deviations caused by object affordance and functional task constraints must be accounted for in order to allow subjects to perform functional task training in robotic therapy environments. The major differences that we have highlighted include trajectory dependence on: object presence, object orientation, and the plane of movement. With the ability to practice ADLs on the ADLER environment we hope to provide patients with a therapy paradigm that will produce optimal results and recovery.

TheraDrive: a new stroke therapy concept for home-based, computer-assisted motivating rehabilitation

Stroke results in functional arm impairments that persist even after rehabilitation training. The increasing numbers of persons at-risk in the population for stroke creates an increased need for therapy programs that can be effectively administered in both home and outpatient clinics. The aim of this work is to create a low-cost, commercially-viable, home-based rehabilitation system that can capitalize on computer-assisted motivating rehabilitation concepts of game therapy and skill training with functional training related to real activities to induce user-dependent CNS plasticity. The TheraDrive concept combines the motivational elements of relearning steering tasks with playing driving video games using commercial force-feedback steering wheels to create an upper arm stroke therapy environment that is usable at home or in the clinic. This paper presents the concept and reports on investigations to evaluate the main commercial building blocks for the prototype: the steering wheel and driving software. Evaluation results of three force-feedback steering wheels and the driving gaming software called SmartDriver are presented. Future evaluation trials with stroke subjects will be completed.

Collaborative tele-rehabilitation and robot-mediated therapy for stroke rehabilitation at home or clinic

Successful home-rehabilitation should reduce cost, facilitate virtual therapeutic visits, and motivate stroke survivors to engage in under-supervised therapeutic activity at levels necessary for motor learning and generalization to occur. We explored long-distance collaborative “play” using two 6DOF robot-mediated environments and examined the influence on the motivation of able-bodied persons to engage in therapy, sustain play, and relate during a shared task, tic-tac-toe. A clear positive trend existed in favor of the collaborative robot-mediated environment, which subjects found more valuable, interesting, and enjoyable, and was therefore willing to spend more time at the task. Kinematic metrics such as mean velocity of movement and movement smoothness were sensitive to the changes in the level of collaboration in the environment in that sub-movements from rest to the piece were slower and less directed than movements to place the piece at the target tic-tac-toe location. We discuss our experiment, results and its application to stroke rehabilitation and to the development of collaborative tele-rehabilitation at home.

Design and validation of low-cost assistive glove for hand assessment and therapy during activity of daily living-focused robotic stroke therapy

Hand and arm impairment is common after stroke. Robotic stroke therapy will be more effective if hand and upper-arm training is integrated to help users practice reaching and grasping tasks. This article presents the design, development, and validation of a low-cost, functional electrical stimulation grasp-assistive glove for use with task-oriented robotic stroke therapy. Our glove measures grasp aperture while a user completes simple-to-complex real-life activities, and when combined with an integrated functional electrical stimulator, it assists in hand opening and closing. A key function is a new grasp-aperture prediction model, which uses the position of the end-effectors of two planar robots to define the distance between the thumb and index finger. We validated the accuracy and repeatability of the glove and its capability to assist in grasping. Results from five nondisabled subjects indicated that the glove is accurate and repeatable for both static hand-open and -closed tasks when compared with goniometric measures and for dynamic reach-to-grasp tasks when compared with motion analysis measures. Results from five subjects with stroke showed that with the glove, they could open their hands but without it could not. We present a glove that is a low-cost solution for in vivo grasp measurement and assistance.

Guest Editorial Special Issue on Rehabilitation Robotics

The 16 papers in this special section have been logically organized into four different groups: enabling technologies for rehabilitation robotics; two robotic systems used for assisted diagnosis of pathologies of interest in the rehabilitation domain; different robotic systems applied to assisted physical rehabilitation; and robotic systems used for assisted psychophysiological rehabilitation.

Remote vibrotactile noise improves light touch sensation in stroke survivors’ fingertips via stochastic resonance

Background and purposeStroke rehabilitation does not often integrate both sensory and motor recovery. While subthreshold noise was shown to enhance sensory signal detection at the site of noise application, having a noise-generating device at the fingertip to enhance fingertip sensation and potentially enhance dexterity for stroke survivors is impractical, since the device would interfere with object manipulation. This study determined if remote application of subthreshold vibrotactile noise (away from the fingertips) improves fingertip tactile sensation with potential to enhance dexterity for stroke survivors.MethodsIndex finger and thumb pad sensation was measured for ten stroke survivors with fingertip sensory deficit using the Semmes-Weinstein Monofilament and Two-Point Discrimination Tests. Sensation scores were measured with noise applied at one of three intensities (40%, 60%, 80% of the sensory threshold) to one of four locations of the paretic upper extremity (dorsal hand proximal to the index finger knuckle, dorsal hand proximal to the thumb knuckle, dorsal wrist, volar wrist) in a random order, as well as without noise at beginning (Pre) and end (Post) of the testing session.ResultsVibrotactile noise of all intensities and locations instantaneously and significantly improved Monofilament scores of the index fingertip and thumb tip (p < .01). No significant effect of the noise was seen for the Two-Point Discrimination Test scores.ConclusionsRemote application of subthreshold (imperceptible) vibrotactile noise at the wrist and dorsal hand instantaneously improved stroke survivors’ light touch sensation, independent of noise location and intensity. Vibrotactile noise at the wrist and dorsal hand may have enhanced the fingertips’ light touch sensation via stochastic resonance and interneuronal connections. While long-term benefits of noise in stroke patients warrants further investigation, this result demonstrates potential that a wearable device applying vibrotactile noise at the wrist could enhance sensation and grip ability without interfering with object manipulation in everyday tasks.

Bilateral assessment of functional tasks for robot-assisted therapy applications

This article presents a novel evaluation system along with methods to evaluate bilateral coordination of arm function on activities of daily living tasks before and after robot-assisted therapy. An affordable bilateral assessment system (BiAS) consisting of two mini-passive measuring units modeled as three degree of freedom robots is described. The process for evaluating functional tasks using the BiAS is presented and we demonstrate its ability to measure wrist kinematic trajectories. Three metrics, phase difference, movement overlap, and task completion time, are used to evaluate the BiAS system on a bilateral symmetric (bi-drink) and a bilateral asymmetric (bi-pour) functional task. Wrist position and velocity trajectories are evaluated using these metrics to provide insight into temporal and spatial bilateral deficits after stroke. The BiAS system quantified movements of the wrists during functional tasks and detected differences in impaired and unimpaired arm movements. Case studies showed that stroke patients compared to healthy subjects move slower and are less likely to use their arm simultaneously even when the functional task requires simultaneous movement. After robot-assisted therapy, interlimb coordination spatial deficits moved toward normal coordination on functional tasks.