In recent years, the field of neurological rehabilitation has been reinvigorated with the finding that the central nervous system retains plasticity even into adulthood. Interventions utilizing massed practice neurorehabilitation provide a setting in which an individual with upper motor neuron lesions performs hundreds of repetitions of a behavior per session using the affected extremity(ies); the goal is to develop skill (motor relearning) in the performance of the behavior. In this context, the ability of the spinal cord to reorganize to produce improvements in function appears to be highly sensitive to the appropriate training environment. For example, patients that received body-weight supported treadmill training, following spinal cord injury and stroke, showed improved EMG activation patterns, more natural walking characteristics, and were able to bear more weight on their legs and had higher returns in functional walking ability when compared to patients who received standard physiotherapy. One limitation with these gait training protocols is that a number of key training variables are not well controlled for or understood, yet presumably play an instrumental role in functional recovery. For example, walking speed, level of body-weight support, and leg kinematics have all been shown to be important in eliciting and sustaining locomotor patterns in animals, yet we currently lack quantitative techniques for determining how to customize these parameters for individual patients. One possible solution to identifying the set of optimal gait training parameters is by integrating active assistance and quantitative assessment that would allow the systematic exploration of walking across various conditions. Recent modifications to the Lokomat (Hocoma, Switzerland), a fully programmable gait trainer, allow us to develop assessment algorithms that make it possible to study peripheral conditions which directly mediate sensory afferent drive to the spinal cord. The specific goal of this Phase I SBIR project is to develop analytical tools for neurorehabilitation of gait for individuals with spinal cord injury or stroke directed at facilitating experiments for optimizing training conditions that promote the highest returns in motor recovery. Our guiding premise is that quantitative tools for assessing motor function will aid both clinical diagnoses and guidance of rehabilitation strategies to improve motor function. We believe that patients with neurological injuries who are trained at conditions that result in the most appropriate joint moments and muscle activation patterns will achieve higher levels of functional recovery than those trained at conditions chosen using heuristic methods. Rehabilitation from stroke or spinal cord injury is labor-intensive, relying on therapy and assessments that often require direct contact between physical therapist and patient. Physical therapy techniques encouraging correct movement patterns and discouraging incorrect movement patterns have been shown to promote recovery, however, because reimbursement for physical therapy time for stroke patients has decreased substantially robotic devices may be of substantial value for rehabilitation to free therapists from repetitive tasks such as moving a patients' plegic arm to simulate independent reaching, to provide objective, quantitative assessment of motor performance, and to explore the possibility of delivering regular, meaningful therapy independent of the constant attention of the therapist. The specific goal of this Phase I SBIR project is to develop analytical tools for neurorehabilitation of gait for individuals with spinal cord injury or stroke directed at facilitating experiments for optimizing training conditions that promote the highest returns in motor recovery.
Thesaurus Terms: Assistive Device /Technology, Biomechanics, Biomedical Equipment Development, Computational Neuroscience, Data Collection Methodology /Evaluation, Gait, Nervous System Disorder Therapy Biofeedback, Functional Ability, Musculoskeletal Regeneration, Nervous System Regeneration, Psychomotor Function, Three Dimensional Imaging /Topography Bioengineering /Biomedical Engineering, Clinical Research, Human Data, Medical Rehabilitation Related Tag
