James FitzGerald

I work on implanted and non-invasive electronic devices that interface directly with parts of the nervous system. At present my main research focus is on the development of a novel type of interface capable of recording signals from motor axons in severed peripheral nerves after amputation, with the aim of using these signals to control sophisticated prosthetic limbs. This requires advances in several areas including polymer microfabrication techniques, implantable electrophysiological recording systems, microsurgical implantation methods, and the development of multichannel signal processing and pattern recognition algorithms. A further problem is that like virtually all surgical implants, interfaces evoke a foreign body response that leads to the deposition of scar tissue on their surfaces, which leads to gradual electrical failure of the device. A major strand of my work at present concerns the development of techniques for long term scar suppression, and I have recently shown that drug elution is a very promising approach to this (see Journal of Neural Engineering 2016;13:026006 for further details). I am also a consultant neurosurgeon in Oxford Functional Neurosurgery, which has the UK's largest clinical practice in deep brain stimulation, spinal cord and dorsal root ganglion stimulation and peripheral nerve stimulation, for the treatment of movement disorders and neuropathic pain. Alongside and closely intertwined with this clinical work we run a research programme investigating the mechanisms by which neuromodulation treatments work and how they can be improved and their use expanded to new indications. I am the President of the Neuromodulation Society of the UK and Ireland (NSUKI), and serve on the board of directors of the International Neuromodulation Scoiety, and as section editor for Brain Stimulation of the society's journal, Neuromodulation: Technology at the Neural Interface.

[2026] Rolandino G. et al, (2026), IEEE Trans Neural Syst Rehabil Eng, 34, 1219 - 1228, HD-sEMG-Based Control Using Neck Muscles and Shallow Neural Networks: Assessing Performance in Rehabilitation-Oriented Tasks. [2025] He S. et al, (2025), Brain, 148, 2093 - 2107, Cortico-thalamic tremor circuits and their associations with deep brain stimulation effects in essential tremor. [2025] L R. et al, (2025), IEEE Trans Neural Syst Rehabil Eng, 33, 298 - 309, Finite Element Modelling for Biophysical Models of Nervous System Stimulation: Best Practices for Multiscale Adaptive Meshing. [2024] Sotirakis C. et al, (2024), NPJ Digit Med, 7, Predicting future fallers in Parkinson's disease using kinematic data over a period of 5 years. [2024] Chapman TP. et al, (2024), Eur Respir J, 64, Deep brain sti