Members

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

I am a Rheumatologist with a clinical and research interest in musculoskeletal pain mechanisms. I use a combination of techniques, including neuroimaging and clinical pain quantification, to investigate pain related predictors of response to treatment in different forms of arthritis and fibromyalgia. My group is currently investigating the effectiveness of digital cognitive behavioural therapy for insomnia in patients with fibromyalgia. This study is using online platforms to conduct questionnaire-based surveys and collect quantitative movement and cognitive learning data.

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.

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.

Flavia Mancini is an MRC Career Development Award fellow and head of a multidisciplinary research group, called the Nox Lab, at the Department of Engineering, University of Cambridge. The Nox Lab includes a mix of computational neuroscientists, information and biomedical engineers, united by a shared passion for the development of open-source computational methods to understand brain function and improve human health. Their work is motivated by neuroscience questions relating to how neural activity generates perception and behaviour, mostly in humans. They use a combination of neuroimaging, physiological, behavioural and computational methods for the processing of neural signals and behavioural/clinical data.

The Nox Lab’s current work has a primary application to chronic pain. They take an innovative information engineering approach to understanding the neural processing and regulation of pain. Nox Lab’s research is split into a basic research line, aiming to understand the computational and neural mechanisms of pain inference, learning and control, and a translational research line in which they translate this knowledge into digital and neurotechnology tools for precision medicine, pain prevention and treatment.