[논문]Evaluation of robot-assisted gait training using integrated biofeedback in neurologic disorders

doi:10.1016/j.gaitpost.2011.11.031

Evaluation of robot-assisted gait training using integrated biofeedback in neurologic disorders

Gait & posture, v.35 no.4, 2012년, pp.595 - 600

Stoller, Oliver (Bern University of Applied Sciences, Health, Basel, Switzerland) , Waser, Marco (Swiss Tropical and Public Health Institute (TPH), Basel, Switzerland) , Stammler, Lukas (Bern University of Applied Sciences, Health, Basel, Switzerland) , Schuster, Corina (Reha Rheinfelden, Rheinfelden, Switzerland)

Abstract ▼ AI-Helper

Highlights► This biofeedback approach cannot detect progress during robot-assisted gait training (RAGT). ► Hip flexion activity decreased following 8 RAGT sessions. ► Knee extension activity increased following 8 RAGT sessions. ► Consider these findings when refining existing or developing new biofeedback strategies for RAGT. AbstractBackgroundNeurological disorders lead to walking disabilities, which are often treated using robot-assisted gait training (RAGT) devices such as the driven gait-orthosis Lokomat. A novel integrated biofeedback system was developed to facilitate therapeutically desirable activities during walking. The aim of this study was to evaluate the feasibility to detect changes during RAGT by using this novel biofeedback approach in a clinical setting for patients with central neurological disorders.Methods84 subjects (50 men and 34 women, mean age of 58±13years) were followed over 8 RAGT sessions. Outcome measures were biofeedback values as weighted averages of torques measured in the joint drives and independent parameters such as guidance force, walking speed, patient coefficient, session duration, time between sessions and total treatment time.ResultsJoint segmented analysis showed significant trends for decreasing hip flexion activity (p≤.003) and increasing knee extension activity (p≤.001) during RAGT sessions with an intercorrelation of r=−.43 (p≤.001). Further associations among independent variables were not statistically significant.ConclusionThis is the first study that evaluates the Lokomat integrated biofeedback system in different neurological disorders in a clinical setting. Results suggest that this novel biofeedback approach used in this study is not able to detect progress during RAGT. These findings should be taken into account when refining existing or developing new biofeedback strategies in RAGT relating to appropriate systems to evaluate progress and support therapist feedback in clinical settings.

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Evaluation of robot-assisted gait training using integrated biofeedback in neurologic disorders

Abstract ▼ AI-Helper

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