title: Assessment of walking performance in robot-assisted gait training: a novel approach based on empirical data.
abstract: Motivation and voluntary drive of patients can be improved by applying biofeedback during robot-assisted rehabilitation trainings. Biofeedback systems were traditionally based on theoretical assumptions. In this paper, we present a novel approach to calculate biofeedback during robot-assisted gait training. Our method was based on empirical data that were obtained from healthy subjects when simulating distinctive degrees of walking performance during robot-assisted gait training. This empirical data-based biofeedback (EDBF) method was evaluated with 18 subjects without gait disorders. A higher correlation between the subjects' walking performance and biofeedback values was found for the EDBF method compared to a theory-based biofeedback approach.
authors.affiliation: Balgrist University Hospital, Spinal Cord Injury Research, Zurich, Switzerland.
authors.forename: Raphael
authors.initials: R
authors.lastname: Banz
authors.forename: Robert
authors.initials: R
authors.lastname: Riener
authors.forename: Lars
authors.initials: L
authors.lastname: Lünenburger
authors.forename: Marc
authors.initials: M
authors.lastname: Bolliger
mesh_terms: D001676:Biofeedback, Psychology / Q000295:instrumentation / Q000379:methods; D001696:Biomechanical Phenomena; D001698:Biomedical Engineering; D003625:Data Collection; D005684:Gait / Q000502:physiology*; D020233:Gait Disorders, Neurologic / Q000503:physiopathology* / Q000534:rehabilitation*; D006801:Humans; D012371:Robotics / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D016138:Walking / Q000502:physiology*