Members
Dr. Alex Casson
Working in:
- Bioelectronics and sensor systems
- Digital Health
- Non-invasive brain stimulation
- Neurofeedback
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.
Prof. Tamar Makin
Working in:
- Bioelectronics and sensor systems
- Prosthetics and robotics
- Non-invasive brain stimulation
- Peripheral stimulation
- Neurofeedback
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.
Dr. Flavia Mancini
Working in:
- Computational and dynamical brain models
- Digital Health
- Neurofeedback
- Data science and biomarkers
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.
Dr. Elsa Fouragnan
Working in:
- Animal models
- Computational and dynamical brain models
- Non-invasive brain stimulation
- Neurofeedback
- Data science and biomarkers
- Other
My research focuses on the neurobiology of decision-making and learning. I use multimodal neuroimaging and neurostimulation methods to uncover the roles of multiple areas in the brain, predominantly the prefrontal cortex. Recently, I have shown that transcranial ultrasound neuromodulation can safely change neural activity in precise parts of the brain, both in non-human primates and humans. I am now working towards bringing this technology forward and apply it to mental health challenges.