Members

Pain and Autonomic regulation. Basic neurobiology to experimental medicine and clinical trials.

Developing non-invasive brain-computer interfaces with optical modalities, creating real time decoding and signal processing BCI software, building AI models to decode human intention and speech

My work focusses on the development and use of virtual reality interventions for the management of chronic pain. This includes research into brain-computer interfaces, personalised approaches using sensor-based technologies (eye tracking, EEG, ECG etc), and machine learning.

My research area of interest is in the field of neurorehabilitation technologies for supporting people with neurological conditions or injuries to learn, re-learn, and recover motor functions, with special focus on gait, postural control, and upper-limb function.

Focus areas: functional electrical stimulation systems and rehabilitation robots to support gait rehabilitation and grasping of tetraplegic and hemiparetic patients, assistive technologies, assessment technologies, gaming technologies, and their combinations. Also, mechanisms that result on sensory-motor impairments and recovery after injury, including central pattern generators and neural plasticity.

My research focuses on understanding the brain mechanisms that underpin human sensorimotor function. My research utilises a range of approaches, including state-of-the-art MR imaging and spectroscopy, magnetoencephalography, and non-invasive brain stimulation to investigate the pathophysiology of common mental/brain health conditions. A key focus is developing the next generation of novel therapeutic approaches for mental/brain health conditions based on wearable technology and non-invasive brain stimulation. To this end I am a founding Non-Executive Director, and Chief Scientific Officer, of Neurotherapeutics Ltd.

I am currently a senior postdoctoral researcher at the University of Glasgow. My research involves designing, simulating, fabricating, and testing neuromodulation devices with a diverse range of modalities, including optogenetic, magnetic, and thermal. I go from using state-of-the-art software to simulate device performance in full human body models, to cleanroom nanofabrication, and in-vivo testing of device prototypes with a broad range of talented collaborators in engineering, neuroscience, and computing science. My latest research proposal involves designing the first optogenetic brain implant for chronic pain treatment.

Dr Alex Casson is a Reader in the Materials, Devices and Systems division of the Department of Electrical and Electronic Engineering at the University of Manchester. His research focuses on non-invasive bioelectronic interfaces: the design and application of wearable sensors, and skin-conformal flexible sensors, for human body monitoring and data analysis from highly artefact prone naturalistic situations. This work is highly multi-disciplinary and he has research expertise in:
– Ultra low power microelectronic circuit design at the discrete and fully custom microchip levels.
– Sensor signal processing and machine learning for power and time constrained motion artefact rich environments.
– Manufacturing using 3D printing, screen printing, and inkjet printing.
He has particular interests in closed loop systems: those which are tailored to the individual by personalised manufacturing via printing; and tailored to the individual by adjusting non-invasive stimulation (light, sound, electrical current) using data driven responses/outputs from real-time signal processing. Dr Casson’s ultra low power sensors work is mainly for health and wellness applications, with a strong background in brain interfacing (EEG and transcranial current stimulation) and heart monitoring. Applications focus on both mental health situations including chronic pain, sleep disorders, and autism, and physical health/rehabilitation applications including diabetic foot ulceration, and chronic kidney disease.

My main interest is in understanding how our body representation changes in the brain (brain plasticity). Our primary model for brain plasticity is hand function and dysfunction, and how we could use technology to increase hand functionality in able and disabled individuals at all ages.