Abstract-Stroke patients often have flexor hypertonia and finger extensor weakness, which makes it difficult to open their affected hand for functional grasp. Because of this impairment, hand rehabilitation after stroke is essential for restoring functional independent lifestyles. The goal of this study is to develop a passive, lightweight, wearable device to assist with hand function during performance of activities of daily living. The device, Hand Spring Operated Movement Enhancer (HandSOME), assists with opening the patient's hand using a series of elastic cords that apply extension torques to the finger joints and compensates for the flexor hypertonia. Device design and calibration are described as well as functional and usability testing with stroke subjects with a wide range of hand impairments. In initial testing with eight stroke subjects with finger flexor hypertonia, use of the HandSOME significantly increased range of motion and functional ability . There was some decrease in grip strength with the HandSOME device at the subject's ideal setting, however this was not statistically significant and did not seem to have a significant effect on function. Overall HandSOME shows promise as a training tool to facilitate repetitive task practice for improving hand function in stroke patients. HandSOME can be used as part of a home-based therapy program, or as an orthotic for replacing lost function.

This technology could provide insight on motor fluctuations in the context of daily life to guide clinical management and aid in development of new therapies.

The goal of this review was to discuss the impairments in hand function after stroke and present previous work on robot-assisted approaches to movement neurorehabilitation. Robotic devices offer a unique training environment that may enhance outcomes beyond what is possible with conventional means. Robots apply forces to the hand, allowing completion of movements while preventing inappropriate movement patterns. Evidence from the literature is emerging that certain characteristics of the human-robot interaction are preferable. In light of this evidence, the robotic hand devices that have undergone clinical testing are reviewed, highlighting the authors' work in this area. Finally, suggestions for future work are offered. The ability to deliver therapy doses far higher than what has been previously tested is a potentially key advantage of robotic devices that needs further exploration. In particular, more efforts are needed to develop highly motivating home-based devices, which can increase access to high doses of assisted movement therapy.

In previous work, we developed a lightweight wearable hand exoskeleton (HandSOME) that improves range of motion and function in laboratory testing. In this pilot study, we added the ability to log movement data for extended periods and recruited 10 chronic stroke subjects to use the device during reach and grasp task practice at home for 1.5 hours/day, 5 days per week, for 4 weeks. Seven subjects completed the study, performing 448±651 hand movements per training day. After training, impairment was reduced (Fugl-Meyer Test; gain=4.9±4.1; p=.039) and function was improved (Action Research Arm Test; gain=3.3±2.6; p=.032). There was a significant correlation between gains in the Action Research Arm Test and the number of movements during training (r=0.90; p=.005). Proximal arm control also improved, as evidenced by a significant reduction in the reach path ratio (p=0.038). Five subjects responded well to the treatment, having gains of 6 points or more on the Fugl-Meyer or Action Research Arm Test, and achieving significant gains in digit extension (gain=19.8±10.2 degrees; p=0.024). However, all of the gains that were significant immediately after training were no longer significant at the 3 month follow-up. This treatment approach appears promising, but longer periods of home training may be needed to achieve sustainable gains.

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 HAM-STER 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.

Data suggest that robotic therapy can elicit improvements in arm function that are distinct from conventional therapy and supplements conventional methods to improve outcomes. Results from this pilot study should be confirmed in a larger study.

Abstract-We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

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.