AI in digital health and assistive technology

Developing intelligent systems to support individuals with disabilities and chronic conditions through adaptive, user-centric technologies
Eduardo Miranda applying brain-computer music interface equipment to a person with motor impairments in a wheelchair
Title: AI in digital health and assistive technology
Funding amount: £4,254,045
Location: UK
Dates: 2011–present
Project partners: University of Salford, University of Stirling, Glasgow School of Art, University of Glasgow, Anglia Ruskin University, University of Reading, Sussex Partnership NHS Trust, BBC R&D, BBC Radio Devon, MHA Care Homes, Alzheimer's Society.
University of Plymouth PI: Professor Eduardo Miranda  
University of Plymouth staff: Professor Stephen Hall , Dr Nicolas Farina , Hari Shaji  
 

Overview

This highly interdisciplinary research combines neuroscience, signal processing, design, AI and music technology to enhance healthcare delivery, diagnostics, patient monitoring, and assistive devices. 
Our research focuses on developing intelligent systems to personalise treatments and support individuals with disabilities or chronic conditions through adaptive, user-centric technologies. We are developing brain–computer music interfaces to enable people with severe motor impairments to make music, auditory biofeedback systems to support self-management of dysfunctional breathing, and AI to adapt live digital radio broadcasts to assist people living with dementia.
Computer music research

Objectives

Develop brain–computer music interfaces to enable individuals to create, perform, and interact with music using brain signals, typically measured via electroencephalography. 
In addition to developing this technology, the research aims to improve psychological wellbeing and a sense of agency for those with neuromotor disorders.
Develop AI to adapt live digital radio broadcasts in real-time, delivering personalised content to assist people living alone with mild to moderate dementia. This will address key causes of hospital admission for people with dementia, such as agitation and not taking medication correctly. 
As a result, it is hoped that quality of life in this sector of the ageing population will improve and enable them to live independently in their own homes for longer.
Develop multimodal biofeedback systems coupled with behaviour change techniques to positively impact those living with dysfunctional breathing. 
The project aims to support those living with health conditions such as musculoskeletal pain, mobility, anxiety-related disorders and respiratory conditions, including long COVID.
Eduardo Miranda applying an assistive technology headset to a study participant

Music of the Mind

Our ground-breaking research into brain–computer music interfacing is featured in the film 'Music of the Mind', as part of Sky Atlantic's Human Made Stories series.
This film showcases the research in a moving and personal way, illustrating the life-changing impact of the research on a musician and her ability to compose and play.
Volvo and the producers of this film funded a 12-month research project to further develop the concept.
Film credit: Volvo and Sky Atlantic
 
 

Publications

Venkatesh, S., Miranda, E. R., & Braund, E. (2022). SSVEP-based Brain-computer Interface for Music using a Low-density EEG System. Assistive Technology, 0(0). https://doi.org/10.1080/10400435.2022.2084182
Miranda, E., Venkatesh, S., Martin-Guerrero, JD., Hernani-Morales, C., Lamata, L., & Solano, E. (2022). An approach to interfacing the brain with quantum computers: practical steps and caveats. International Journal of Unconventional Computing, 17(3). https://doi.org/10.48550/arXiv.2201.00817
Shakeri, G., Brewster, S., Venkatesh, S., Moffat, D., Kirke, A., Miranda, E., Banerjee, S., Street, A., Fachner, J., & Odell-Miller, H. (2021). RadioMe: Challenges During the Development of a Real Time Tool to Support People With Dementia. Default journal, 0(0). https://doi.org/10.1145/1122445.1122456
Miranda, E., Daly, I., Nicolaou, N., Williams, D., Hwang, F., Kirke, A., & Nasuto, S. J. (2020). Neural and physiological data from participants listening to affective music. Scientific data, 7(1). https://doi.org/10.1038/s41597-020-0507-6
Daly, I., Williams, D., Hwang, F., Kirke, A., Miranda, E. R., & Nasuto, S. J. (2019). Electroencephalography reflects the activity of sub-cortical brain regions during approach-withdrawal behaviour while listening to music. Scientific Reports, 9(1), 0-0. https://doi.org/10.1038/s41598-019-45105-2
Nicolaou, N., Malik, A., Daly, I., Weaver, J., Hwang, F., Kirke, A., Roesch, E. B., Willilams, D., Miranda, E. R., & Nasuto, S. J. (2017). Directed Motor-Auditory EEG Connectivity Is Modulated by Music Tempo. Frontiers in Human Neuroscience, 11(0). https://doi.org/10.3389/fnhum.2017.00502
Miranda, ER., & Castet, J. (2014). Guide to Brain-Computer Music Interfacing. https://doi.org/10.1007/978-1-4471-6584-2

Funded by

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