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Godfrey S.B.,Catholic University of America | Holley R.J.,Center for Applied Biomechanics and Rehabilitation Research | Lum P.S.,Catholic University of America
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2011

Robotic rehabilitation techniques have the capacity to provide high dosage therapy without the labor burden of conventional methods. The most effective means of using robots to retrain function is not yet known, though many studies now support providing assistance to movement while the user actively participates in that movement. In this study, we compare, in three chronic stroke subjects, a novel Tone assistance mode to a Spring assistance method commonly used in other robots. The Tone mode provides assistance comparable to the subject's own resistance to extension while Spring mode provides a spring-like force to pull the subject to the target. All three subjects produced larger finger movements with robotic assistance, but they also produced much more positive work with the Tone assistance compared to the Spring assistance. This demonstrates that subjects were actively driving the movements in Tone mode to a greater extent than in Spring mode. Two out of three subjects showed similar results in the thumb. In the third subject, work was comparable across all modes. With Tone assistance, subjects produced movement and torque profiles more similar to that of Unassisted movement than Spring-assisted movement for both fingers and thumb. These results suggest that providing assistance tailored to the user's own tone profile may be an effective means of enhancing range of motion to ultimately enable gains in hand function. © 2011 IEEE. Source


Hidler J.,Aretech, Llc | Hidler J.,Center for Applied Biomechanics and Rehabilitation Research | Sainburg R.,Pennsylvania State University
Topics in Spinal Cord Injury Rehabilitation | Year: 2011

Over the past decade, rehabilitation hospitals have begun to incorporate robotics technologies into the daily treatment schedule of many patients. These interventions hold greater promise than simply replicating traditional therapy, because they allow therapists an unprecedented ability to specify and monitor movement features such as speed, direction, amplitude, and joint coordination patterns and to introduce controlled perturbations into therapy. We argue that to fully realize the potential of robotic devices in neurorehabilitation, it is necessary to better understand the specific aspects of movement that should be facilitated in rehabilitation. In this article, we first discuss neurorecovery in the context of motor control and learning principles that can provide guidelines to rehabilitation professionals for enhancing recovery of motor function. We then discuss how robotic devices can be used to support such activities. © 2011 Thomas Land Publishers, Inc. Source


Lee S.W.,Catholic University of America | Lee S.W.,Center for Applied Biomechanics and Rehabilitation Research | Wilson K.M.,University of Pittsburgh | Lock B.A.,Rehabilitation Institute of Chicago | And 2 more authors.
IEEE Transactions on Neural Systems and Rehabilitation Engineering | Year: 2011

In this study, we developed a robust subject-specific electromyography (EMG) pattern classification technique to discriminate intended manual tasks from muscle activation patterns of stroke survivors. These classifications will enable volitional control of assistive devices, thereby improving their functionality. Twenty subjects with chronic hemiparesis participated in the study. Subjects were instructed to perform six functional tasks while their muscle activation patterns were recorded by ten surface electrodes placed on the forearm and hand of the impaired limb. In order to identify intended functional tasks, a pattern classifier using linear discriminant analysis was applied to the EMG feature vectors. The classification accuracy was mainly affected by the impairment level of the subject. Mean classification accuracy was 71.3% for moderately impaired subjects (Chedoke Stage of Hand 4 and 5), and 37.9% for severely impaired subjects (Chedoke Stage of Hand 2 and 3). Most misclassification occurred between grip tasks of similar nature, for example, among pinch, key, and three-fingered grips, or between cylindrical and spherical grips. EMG signals from the intrinsic hand muscles significantly contributed to the inter-task variability of the feature vectors, as assessed by the inter-task squared Euclidean distance, thereby indicating the importance of intrinsic hand muscles in functional manual tasks. This study demonstrated the feasibility of the EMG pattern classification technique to discern the intent of stroke survivors. Future work should concentrate on the construction of a subject-specific EMG classification paradigm that carefully considers both functional and physiological impairment characteristics of each subject in the target task selection and electrode placement procedures. © 2011 IEEE. Source


Lee S.W.,Catholic University of America | Lee S.W.,Center for Applied Biomechanics and Rehabilitation Research | Triandafilou K.,Rehabilitation Institute of Chicago | Lock B.A.,Rehabilitation Institute of Chicago | And 2 more authors.
PLoS ONE | Year: 2013

Significant functional impairment of the hand is commonly observed in stroke survivors. Our previous studies suggested that the inability to modulate muscle coordination patterns according to task requirements may be substantial after stroke, but these limitations have not been examined directly. In this study, we aimed to characterize post-stroke impairment in the ability to modulate muscle coordination patterns across tasks and its correlation with hand impairment. Fourteen stroke survivors, divided into a group with severe hand impairment (8 subjects) and a group with moderate hand impairment (6 subjects) according to their clinical functionality score, participated in the experiment. Another four neurologically intact subjects participated in the experiment to serve as a point of comparison. Activation patterns of nine hand and wrist muscles were recorded using surface electromyography while the subjects performed six isometric tasks. Patterns of covariation in muscle activations across tasks, i.e., muscle modules, were extracted from the muscle activation data. Our results showed that the degree of reduction in the inter-task separation of the multi-muscle activation patterns was indicative of the clinical functionality score of the subjects (mean value = 26.2 for severely impaired subjects, 38.1 for moderately impaired subjects). The values for moderately impaired subjects were much closer to those of the impaired subjects (mean value = 46.1). The number of muscle modules extracted from the muscle activation patterns of a subject across six tasks, which represents the degree of motor complexity, was found to be correlated with the clinical functionality score (R = 0.68). Greater impairment was also associated with a change in the muscle module patterns themselves, with greater muscle coactivation. A substantial reduction in the degrees-of-freedom of the multi-muscle coordination post-stroke was apparent, and the extent of the reduction, assessed by the stated metrics, was strongly associated with the level of clinical impairment. © 2013 Lee et al. Source


Lee S.W.,Catholic University of America | Lee S.W.,Center for Applied Biomechanics and Rehabilitation Research | Landers K.A.,Catholic University of America | Landers K.A.,Systems In Motion | And 2 more authors.
IEEE Transactions on Neural Systems and Rehabilitation Engineering | Year: 2014

Significant functional impairment of the hand is common among stroke survivors and restoration of hand function should be prioritized during post-stroke rehabilitation. The goal of this study was to develop a novel biomimetic device to assist patients in producing complex hand movements with a limited number of actuators. The Biomimetic Hand Exoskeleton Device (BiomHED) is actuated by exotendons that mimic the geometry of the major tendons of the hand. Ten unimpaired subjects and four chronic stroke survivors participated in experiments that tested the efficacy of the system. The exotendons reproduced distinct spatial joint coordination patterns similar to their target muscle-tendon units for both subject groups. In stroke survivors, the exotendon-produced joint angular displacements were smaller, but not significantly different, than those of unimpaired subjects (p = 0.15-0.84). Even with limited use of the BiomHED, the kinematic workspace of the index finger increased by 63%-1014% in stroke survivors. The device improved the kinematics of the tip-pinch task in stroke survivors and resulted in a significant reduction in the fingertip-thumb tip distance (17.9 ± 15.3 mm). This device is expected to enable effective "task-oriented" training of the hand post-stroke. © 2001-2011 IEEE. Source

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