Automated and Adaptive Lower Extremity Neuro-Rehabilitation for Stroke

Harvard Medical School, Boston MA

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): Through our research we aim to develop quantitative methods for the assessment of motor learning in stroke survivors using the lower extremity rehabilitation Lokomat platform (Hocoma AG, Switzerland). Accurate understanding of how the structure of a rehabilitation program affects the long-term retention of motor skills is essential for establishing the efficacy of therapeutic approaches and for comparing efficacy across strategies. Current methods are also very laborious for rehabilitation workers and in some situations strain on the therapist can be the limiting factor on the length of a session or on the number of activities conducted per session. By applying advanced engineering techniques from the fields of control theory and signal processing, we hope to develop automated and adaptive strategies for devices like the Lokomat platform that allow rehabilitation workers to provide their skills while removing much of the strain. These strategies may result in increased speed of recovery by providing patients with tasks dictated by their individual baseline and rate of improvement without the need for therapist intervention. PUBLIC HEALTH RELEVANCE: Stroke is a leading cause of serious long term disability. Of the approximately 700,000 strokes that occur annually in the US, 21-36% of stroke survivors are permanently disabled. According to a 2006 report from the American Stroke Association, more than 1,100,000 American adults report difficulty with functional limitations resulting from stroke. Resulting disabilities negatively impact individual's quality of life, hinder their productivity, and limit their independence. Given the far reaching consequences of stroke on all aspects of survivors'lives, strategies to restore functionality and limit disability via novel research approaches are imperative.