Peripheral Nerve Interfaces, Brain Computer Interfaces (BCIs), and Muscle Stimulators
oxford neural interfacing
The Oxford Neural Interfacing Group led by James FitzGerald is dedicated to designing, developing and testing new ways to connect the human nervous system to electronic devices in order to restore function or aid rehabilitation after injury. We work on peripheral nerve interfaces, brain computer interfaces (BCIs), and devices to stimulate weak or paralysed muscles.
Peripheral nerve interfacing
Very sophisticated robotic prostheses have been developed to help patients unfortunate enough to have lost an arm or hand. They are capable of a wide range of movements closely mimicking those of a real limb, but their full potential cannot be realised because the means by which the user has to control them is much more primitive.
Prosthetic limbs currently employ "myo-electric" control. Electrodes on the skin surface detect activity in muscles in the amputation stump, which the user learns to twitch voluntarily to instruct the prosthesis to, for example, open or close the hand. This method allows control of only one or two movements at any given time, users are unable to produce graded force, and the control always requires conscious effort.
To unlock the capabilities of advanced robotic prosthetics, and allow the user to fully and effortlessly control them by thought alone, direct connection to the severed nerves in the amputation stump is needed. We are using a novel type of nerve interface based upon growing nerve fibres from the nerve stump into a bundle of closely packed narrow channels (typically a tenth of a millimetre in diameter) that contain recording electrodes. The design allows both signal amplification and noise reduction, leading to reliable performance in recording nerve signals.
Some key hurdles have recently been overcome. The body reacts to medical implants by coating them with a thin layer of scar tissue, and for an interface this is a major problem as the scar layer gets in between nerve fibres and the recording electrodes. We have developed a way to suppress this scarring, using the slow release of miniscule quantities of anti-inflammatory medication from the device itself, a technique called drug elution. This will ensure stable device function for the long term. Our present focus is on methods of decoding signals recorded from the interface to turn them into servo control instructions for a prosthetic limb.
Brain computer interfaces
Approximately 500 people per year in the UK suffer a spinal cord injury in the upper neck that leaves them paralysed in all four limbs. This leads to a life of near total reliance on others, and any technological advance that can provide even modest degrees of independence can have a substantial impact on long term quality of life.
Limb movements are controlled by a specific region of the brain called the motor cortex. Brain cells here send long nerve fibres down through the spinal cord, which carry the nerve signals from the brain that control movement. These fibres are cut by the injury, but nerve cells in the brain survive and remain active. Brain-computer interfaces are devices designed to record electrical activity from the parts of the brain that used to control the paralysed areas, in order that the recorded signals can be used to control devices like electric wheelchairs or stimulate paralysed muscles.
Most current approaches to doing this use signals recorded from either electrodes on the scalp surface (electroencephalography or EEG), or electrodes implanted into the brain itself. The former are noninvasive which makes them safe but insensitive, while the latter can record very detailed information but have limited longevity of function and eventually damage the brain.
We are using an intermediate solution where electrodes are built into a flat sheet that is positioned on the surface of the brain, but do not penetrate it, a technique called electrocorticography (ECoG). ECoG affords far higher spatial resolution and sensitivity than external EEG based approaches, while avoiding electrode insertion into the brain itself.
Non-INVASIVE NERVE STIMULATION
We are developing techniques to stimulate nerves non-invasively through the skin. A particular focus presently is the phrenic nerves, which are the nerves that activate the diaphragm during breathing.
Like most muscles, the diaphragm undergoes wasting when not used. In patients in intensive care who are on ventilators, this wasting starts with 24 hours and proceeds rapidly. Once the illness that caused admission to intensive care has been treated and the patient is starting to recover, weakness of the diaphragm can lead to difficulty getting off ventilatory support. This can prolong the stay in intensive care and increase the risk of complications such as pneumonia.
By stimulating the phrenic nerves during ventilation, the diaphragm can be activated intermittently to provide a small amount of 'exercise', which is enough to prevent atrophy. We hope that maintaining diaphragm condition in this way will help in the process of returning patients to normal breathing as they recover.
Professor of Neural Interfacing and Consultant Neurosurgeon
Senior Research Fellow
Academic Clinical Fellow
The Oxford Neural Interfacing Group welcomes applications from suitably qualified individuals wishing to study with us at DPhil or MRes level. Candidates will typically come from a neuroscience, medical, or engineering background. In addition to the high academic standards expected for study in Oxford, the technological nature of our work means that earlier study that included experience in areas such as mathematical modelling/simulation, electronics, robotics, coding/computation, or AI/machine learning may be advantageous.
Projects we can offer for 2024 entry include:
- Noninvasive peripheral nerve activation and blockade for improved neuromodulation. This will include computer simulation and in vitro validation of potential neural targets, progressing to in vivo testing if time and progress allow.
- Development of an implanted peripheral nerve interface. This will be in collaboration with engineering/materials groups and continue longstanding work in microchannel based interface devices. Techniques involved will be simulation based on finite element modelling, microfabrication techniques, and signal analysis.
- Integrating EMG and motion sensor signals for advanced AI prosthetic control, with applications including to the tetraplegic hand/arm, and drop foot. A particular focus will be on ways of combining high level conscious control signals with automatic control of lower level aspects of movement.
- Electrical stimulation of denervated muscle. All muscle stimulators in clinical use work by stimulating nerves running to muscles rather than the muscles themselves (for example stimulation of the peroneal nerve for foot drop). Stimulation of muscles that have lost their nerve supply, for example after peripheral nerve injury, is a largely unsolved problem.
- Focused Brain stimulation for high resolution Brain Computer Interfaces. This will build on ongoing work looking at stimulation at the cortical surface as a less invasive alternative to intracortical microstimulation, using methods including computational modelling and study of human brain tissue, both after resection and in vivo during surgery.
The principal supervisors within the group are Professor James FitzGerald and Professor Brian Andrews, however we also collaborate extensively with groups in other Oxford departments and beyond, and principal investigators from these other groups may be part of the supervisory team where appropriate.
If you wish to discuss a possible project with us then please contact us by email. Please note the deadline of 1st December 2023 for applications if you wish to be considered for a scholarship.