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

Background: Neurological 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. Methods: 84 subjects (50 men and 34 women, mean age of 58 +/- 13 years) 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. Results: Joint 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. Conclusion: This 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. (C) 2011 Elsevier B.V. All rights reserved.