Electrical Stimulation Control System Design for Upper Limb Rehabilitation

Introduction.-Modelling and Identification.- Combined FES & Robotic Upper Limb Dynamics.- Model Identification.- Feedback Control Design.- Iterative Learning Control Design.- Clinical Application: Multiple Sclerosis.- Constrained ILC for Human Motor Control.- Clinical Application: Goal-orientated Stroke Rehabilitation.- Electrode Array-based Stimulation.- Clinical Application: Fully Functional Stroke Rehabilitation.- Conclusions and Future Research Directions.

Over the last ten years Dr. Freeman has developed new healthcare technologies combining robotics and electrical stimulation to enable people with upper limb impairments to perform functional tasks. Over this time he has worked closely with clinicians (including former IFESS president Prof Jane Burridge), patients and carers. These include five clinical trials using technology he has developed, as well as numerous smaller studies and user-led design sessions. His focus has been to understand and define clinical problems within an engineering perspective and translate this into usable solutions.
Dr. Freeman's background in adaptive and learning control of robotic structures has enabled him to rigorously tackle the challenge of designing systems that provide high performance in the face of significant model uncertainty/variability, restrictive clinical conditions, and complex dynamics/tasks. These problems have led to a productive interaction in his research between theory and practice (the latter generally providing new problems that need an algorithmic or theoretical solution). This is reflected in my publications which include 70 peer-reviewed journal papers and 130 peer-reviewed conference papers covering the spectrum from control application, control theory, rehabilitation engineering, biomechanics, clinical studies and user perspectives. The research he has led in control of ES has elicited two best conference paper awards (ICORR '09, UKACC '12), and two best journal paper awards (most recently `2013 IEEE Control Systems Society Outstanding Paper Award' based on `impact on the field of systems and control'). For example, his work using iterative learning control and adaptive control for stroke rehabilitation has met with an enthusiastic response from the research community, with invited workshops at IEEE BioRob Conference 2012, 18th IFESS Conference 2013, World Congress in NeuroRehabilitation 2014, as well as a plenary at IEEE International Workshop on nD