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Background: Continued and frequent use of the affected arm can result in increased function after stroke. However, long-term access to therapy is often limited, and home exercise compliance is low. While rehabilitation gaming is becoming increasingly prevalent, concerns about therapeutic method, safety, and usability for independent home use remain largely unaddressed., Objective: The following paper presents usability evaluation of a game based home therapy program called Home Arm Movement Stroke Training Environment (HAMSTER), which is focused on retraining normal arm kinematics and preventing compensation strategies that limit recovery., Methods: Kinect games were created with special consideration for the stroke population and retraining normal movement kinematics. Ten individuals with stroke evaluated the games in focused interviews and one individual with chronic stroke completed one month of independent HAMSTER use in the home., Results: The focused interviews showed the need for motivational upper extremity home interventions. Usability evaluation showed the ability for individuals with stroke to interact with the kinematics focused Kinect games after a short exposure time. The single participant evaluation of home use showed good compliance and improvement on all of the clinical outcome measures after the one month of HAMSTER use., Conclusions: These positive results merit further evaluation of kinematic-focused home gaming interventions like HAMSTER to reduce the use of compensation strategies during home exercise and provide a supplement to conventional care to improve exercise compliance and upper extremity function after stroke.

Abnormal kinematics and the use of compensation strategies during training limit functional improvement from therapy. The Kinect is a low cost ($100) sensor that does not require any markers to be placed on the user. Integration of this sensor into currently used therapy systems can provide feedback about the user's movement quality, and the use of compensatory strategies to complete tasks. This paper presents a novel technique of adding the Kinect to an end effector robot to limit compensation strategies and to train normal joint coordination during movements with an end effector robot. This methodology has wider implications for other robotic and passively actuated end effector rehabilitation devices.

Many robotic systems have been developed to provide assistance to individuals with disabilities. Most of these systems require the individual to interact with the robot via a joystick or keypad, though some utilize techniques such as speech recognition or selection of objects with a laser pointer. In this paper, we describe a prototype system using a novel method of interaction with an assistive robot. A touch-sensitive skin enables the user to directly guide a robotic arm to a desired position. When the skin is released, the robot remains fixed in position. The target population for this system is individuals with hemiparesis due to chronic stroke. The system can be used as a substitute for the paretic arm and hand in bimanual tasks such as holding a jar while removing the lid. This paper describes the hardware and software of the prototype system, which includes a robotic arm, the touch-sensitive skin, a hook-style prehensor, and weight compensation and speech recognition software.

In this study, a robotic orthotic device with one degree of freedom was used for assessment of individuals with chronic stroke and resultant hemiparesis. The specific aim was to investigate the effect of visual feedback distortion on range of motion (ROM) at the elbow and wrist joints as measured by the Arm IntelliStretch platform from Rehabtek LLC. It was hypothesized that introducing visual feedback distortion in increments under the just noticeable difference of two degrees would directly correspond to an increase in ROM at both the wrist and elbow joints when compared to ROM measured by the IntelliStretch system without visual feedback distortion. Ten individuals an average of 11 years post stroke (SD: 9.7) participated in this study. At the elbow joint, repeated measures ANOVA showed a significant effect of distortion (F(4, 36) = 2.69, p < 0.047). Similar trends were seen at the wrist joint, though these results were not statistically significant.

Background and Purpose: Motor symptoms of Parkinson's disease (PD) are typically assessed using clinical scales such as the Unified Parkinson's Disease Rating Scale, but clinical scales are insensitive to subtle changes early in the disease process. The goal of this project was to use current sensing technology to develop a quantitative assessment tool to document fine motor deficits in PD based on the ability to control grip force output. The assessment was designed to challenge deficits commonly encountered as a result of PD, including dual-task performance of a motor task and a cognitive task simultaneously., Methods: Two force sensors were used to measure the isometric pinch grip force between the thumb and index finger in 30 individuals with PD and 30 control participants of similar age without disability. Participants performed a target force tracking task with each of two different target waveforms (sinusoidal or pseudorandom) under each of three different cognitive load conditions (none, subtract 1, and subtract 3). Dependent variables calculated from the force sensor data included root mean square error, tremor integral, and lag., Results: In general, individuals with PD showed significantly less accuracy in generating the target forces as shown by larger root mean square error compared with controls (P < 0.001). They also showed greater amounts of tremor and lag compared with controls (P = 0.001 and <0.001, respectively). Deficits were more pronounced during the cognitive multitasking component of the test., Discussion and Conclusions: These results will serve as a preliminary work for the development of a clinical biomarker for PD that may help to identify subtle deficits in fine motor control early in the disease process and facilitate tracking of disease progression with time.

This review explores recent trends in the development and evaluation of assistive robotic arms, both prosthetic and externally mounted. Evaluations have been organized according to the CATOR taxonomy of assistive device outcomes, which takes into consideration device effectiveness, social significance, and impact on subjective well-being. Questions that have informed the review include: (1) Are robotic arms being comprehensively evaluated along axes of the CATOR taxonomy? (2) Are definitions of effectiveness in accordance with the priorities of users? (3) What gaps in robotic arm evaluation exist, and how might these best be addressed? (4) What further advances can be expected in the next 15 years? Results highlight the need for increased standardization of evaluation methods, increased emphasis on the social significance (i.e., social cost) of devices, and increased emphasis on device impact on quality of life. Several open areas for future research, in terms of both device evaluation and device development, are also discussed.

Effective clinical trials for neuroprotective interventions for Parkinson's disease (PD) require a way to quantify an individual's motor symptoms and analyze the change in these symptoms over time. Clinical scales provide a global picture of function but cannot precisely measure specific aspects of motor control. We have used commercially available sensors to create a protocol called Advanced Sensing for Assessment of Parkinson's disease (ASAP) to obtain a quantitative and reliable measure of motor impairment in early to moderate PD. The ASAP protocol measures grip force as an individual tracks a sinusoidal or pseudorandom target force under three conditions of increasing cognitive load. Thirty individuals with PD have completed the ASAP protocol. The ASAP data for 26 of these individuals were summarized in terms of 36 variables, and modified regression techniques were used to predict an individual's score on the Unified Parkinson Disease Rating Scale based on ASAP data. We observed a mean prediction error of approximately 3.5 UPDRS points, and the predicted score accounted for approximately 76% of the variability of the UPDRS. These results demonstrate that the ASAP protocol can measure differences for individuals who are clinically different. This indicates that the ASAP protocol may be able to measure changes with time in the motor signs of an individual with PD.

Robotic devices for therapy have the potential to enable intensive, fully customized home rehabilitation over extended periods for individuals with stroke and traumatic brain injury, thus empowering them to maximize their functional recovery. For robotic rehabilitation to be most effective, systems must have the capacity to assign performance goals to the user and to increment those goals to encourage performance improvement. Otherwise, individuals may plateau at an artificially low level of function. Frequent goal change is needed to motivate improvements in performance by individuals with brain injury; but because of entrenched habits, these individuals may avoid striving for goals that they perceive as becoming ever more difficult. For this reason, implicit, undetectable goal change (distortion) may be more effective than explicit goal change at optimizing the motor performance of some individuals with brain injury. This paper reviews a body of work that provides a basis for incorporating implicit goal change into a robotic rehabilitation paradigm. This work was conducted with individuals without disability to provide foundational knowledge for using goal change in a robotic environment. In addition, we compare motor performance with goal change to performance with no goal or with a static goal for individuals without brain injury. Our results show that goal change can improve motor performance when participants attend to visual feedback. Building on these preliminary results can lead to more effective robotic paradigms for the rehabilitation of individuals with brain injury, including individuals with cerebral palsy.

Assistive robots for persons with physical limitations need to interact with humans in a manner that is safe to the user and the environment. Early work in this field centered on task specific robots. Recent work has focused on the use of the MANUS ARM and the development of different interfaces. The most intuitive interaction with an object is through touch. By creating a skin for the robot arm which will directly control its movement compliance, we have developed a novel and intuitive method of interaction. This paper describes the development of a skin which acts as a switch. When activated through touch, the skin will put the arm into compliant mode allowing it to be moved to the desired location safely, and when released will put the robot into non-compliant mode thereby keeping it in place. We investigated four conductive materials and four insulators, selecting the best combination based on our design goals of the need for a continuous activation surface, the least amount of force required for skin activation, and the most consistent voltage change between the conductive surfaces measured during activation.

Although the use of robotic devices to address neuromuscular rehabilitative goals represents a promising technological advance in medical care, the large number of systems being developed and varying levels of clinical study of the devices make it difficult to follow and interpret the results in this new field. This article is a review of the current state-of-the-art in robotic applications in poststroke therapy for the upper extremity, written specifically to help clinicians determine the differences between various systems. We concentrate primarily on systems that have been tested clinically. Robotic systems are grouped by rehabilitation application (e.g., gross motor movement, bilateral training, etc.), and, where possible, the neurorehabilitation strategies employed by each system are described. We close with a discussion of the benefits and concerns of using robotics in rehabilitation and an indication of challenges that must be addressed for therapeutic robots to be applied practically in the clinic.

Background: It is common for individuals with chronic disabilities to continue using the compensatory movement coordination due to entrenched habits, increased perception of task difficulty, or personality variables such as low self-efficacy or a fear of failure. Following our previous work using feedback distortion in a virtual rehabilitation environment to increase strength and range of motion, we address the use of visual feedback distortion environment to alter movement coordination patterns., Methods: Fifty-one able-bodied subjects participated in the study. During the experiment, each subject learned to move their index finger and thumb in a particular target pattern while receiving visual feedback. Visual distortion was implemented as a magnification of the error between the thumb and/or index finger position and the desired position. The error reduction profile and the effect of distortion were analyzed by comparing the mean total absolute error and a normalized error that measured performance improvement for each subject as a proportion of the baseline error., Results: The results of the study showed that (1) different coordination pattern could be trained with visual feedback and have the new pattern transferred to trials without visual feedback, (2) distorting individual finger at a time allowed different error reduction profile from the controls, and (3) overall learning was not sped up by distorting individual fingers., Conclusion: It is important that robotic rehabilitation incorporates multi-limb or finger coordination tasks that are important for activities of daily life in the near future. This study marks the first investigation on multi-finger coordination tasks under visual feedback manipulation.

Imperceptible visual distortion, in the form of a disguised progression of performance goals, may be a helpful addition to rehabilitation after stroke and other brain injuries. This paper describes work that has been done to lay the groundwork for testing this hypothesis. We have constructed and validated an experimental environment that provides controllable visual distortion and allows precise force and position measurements. To estimate the amount of visual distortion that should be imperceptible, we measured the limits for force and distance/position perception in our rehabilitation environment for young and elderly unimpaired subjects and for a single traumatic brain injury (TBI) patient. We found the Just Noticeable Difference (JND) for produced force to be 19.7% (0.296 N) and the JND for movement distance/finger position to be 13.0% (3.99 mm) for young subjects (ages 18-35). For elderly subjects (ages 61-80), the JND for force was measured to be 31.0% (0.619 N) and the JND for distance/po'sition was 16.1% (5.01 mm). JNDs of 46.0% (0.920 N) and 45.0% (14.8 mm) were found for the motor-impaired individual. In addition, a subject's rating of effort was found to be profoundly influenced by visual feedback concerning the force magnitude. Even when this feedback was distorted, it accounted for 99% of the variance of the effort rating. These results indicate that substantial visual distortions should be imperceptible to the subject, and that visual feedback can be used to influence the subject's perceived experience in our robotic environment. This means that we should be able to use imperceptible visual distortion to alter a patient's perception of therapeutic exercise in a robotic environment.