12 Labours Seminar Series (Exemplar Project 2): Personalised rehabilitation of upper limb disorders

Abstract

Movement disorders that affect the upper limb are common, and place a large burden on society. Stroke and brachial plexus injuries, for example, result in partial limb paralysis and lifelong deficits in function [1]. Rotator cuff injuries are also common in our young athletes, with long-term complications such as osteoarthritis [2]. Clinicians currently follow an ‘evidence-based’ approach, that determines the efficacy of a treatment strategy on a patient cohort, without acknowledging that individuals within that cohort respond differently to each intervention [3]. In exemplar project 2 (EP2), we propose a personalised approach to quantitatively assess, treat, and monitor upper limb disorders, using computational models [4], wearable sensors [5], and robotic devices. This talk focuses on the computational modelling aspects in EP2. Specifically; musculoskeletal model generation, statistical shape modelling [6], multi-scale neuromuscular modelling including the role motor units play in predicting joint level movements [7, 8]. Biomechanical simulations are vital to the interpretation of movement patterns and to inform data-driven machine learning classification in order to assist clinical decision-making and personalised treatment plans.