innovative gait biofeedback strategies for stroke rehabilitation

Conditions: Stroke, Cardiovascular; Gait, Hemiplegic

Summary: the long-term study goal is to develop a more engaging, motivating gait biofeedback methodologies specifically designed for post-stroke gait training. the current project aims to address fundamental questions regarding the optimal methodology to deliver agrf biofeedback during gait, and the feasibility and preliminary efficacy of agrf progression protocols for improved gait patterns and gait function. the study objectives are to (1) evaluate the immediate effects of biofeedback training methodology on gait biomechanics; and (2) evaluate the feasibility and short-term effects on gait performance of a real-time biofeedback protocol incorporating progression criteria (similar to those employed during clinical rehabilitative training).

even after discharge from rehabilitation, residual gait deficits are prevalent in stroke survivors, leading to decreased walking speed and endurance. because gait dysfunctions limit community mobility, stroke survivors and rehabilitation clinicians consider restoration of walking a major goal of rehabilitation. biomechanical impairments, such as reduced knee and ankle flexion during swing phase negatively affect gait function and increase the risk for falls. during the stance phase, decreased contribution of the paretic leg to forward propulsion during paretic terminal stance is a critical post-stroke gait deficit shown to be correlated with hemiparetic severity, walking speed, and gait asymmetry. these gait deficits can lead to falls, increased energy cost of gait, and decreased endurance. also, a slowed self-selected walking speed is one of the hallmarks of post-stroke gait, and greatly limits community participation in individuals post-stroke. very few interventions provide targeted practice of biomechanically appropriate movement patterns exclusively or preferentially to the paretic leg. biofeedback can enhance an individual's awareness of the impairment targeted during gait training, enabling self-correction of aberrant gait patterns. real-time biofeedback gait training has been used for modulating step length asymmetry in people post-stroke. a recent study developed a protocol combining treadmill training with visual and auditory real-time biofeedback to increase anterior ground reaction force (agrf). agrf biofeedback may be a beneficial strategy to target unilateral propulsion deficits in people post-stroke. the goal of this study is to develop improved methodologies for agrf gait biofeedback and to evaluate the feasibility and short-term effects of gait biofeedback. to achieve this goal, experiments will be performed on young able-bodied individuals as well as stroke survivors.

Eligibility criteria:
inclusion criteria: stroke participants: * age 30-90 years (stroke) or 18-50 years (able-bodied controls) * chronic stroke (\>6 months post stroke) * ambulatory with or without the use of a cane or walker * able to walk for 2 minutes at the self-selected speed without an orthoses * resting heart rate 40-100 beats per minute able-bodied participants: * age 18 to 50 years * no history of neurologic disease * no history of orthopedic disease or injury affecting the lower extremity. exclusion criteria: stroke participants: * cerebellar signs (ataxic ("drunken") gait or decreased coordination during rapid alternating hand or foot movements * history of lower extremity joint replacement * inability to communicate with investigators * neglect/hemianopia, or unexplained dizziness in last 6 months * neurologic conditions other than stroke * orthopedic problems in the lower limbs or spine (or other medical conditions) that limit walking or cause pain during walking. able-bodied controls * history of neurologic disease * history of orthopedic disease or injury to the lower extremity in the past 6 months * pain or discomfort during walking * cardiovascular or medical condition affecting ability to exercise or walk.

Keywords: gait biofeedback gait rehabilitation paretic propulsion gait motor learning