Mental Illness & Neurodiverse Digital Labs
The aim of MIND Labs are to facilitate early diagnosis and more personalised treatment of mental health difficulties by establishing illness patterns across the lifespan from developmental disorders, child and adolescent mental illness, adult mental illness and neurodegenerative diseases, along with controls. By linking information on genetic, lifestyle and social factors, we aim to better predict the impact of risk factors and facilitate early diagnosis. MIND Labs’ unique approach takes advantage of opportunities in the digital sector to impact on digital healthcare along with strong partnerships with the NHS and other mental health research organisations. MIND Labs will continuously add to datasets over time to develop a comprehensive set of metrics. The MIND datasets and associated services will create a unique Digital Innovation Hub for any UK users compliant to The UK Health Data Alliance. Collaborators include University of Edinburgh and University of Strathclyde.
MIND Map aims to facilitate early diagnosis and more personalised treatment through establishing illness patterns across the lifespan from developmental disorders, child and adolescent mental illness, adult mental illness and neurodegenerative diseases. We will curate different datasets to look for patterns that may predict treatment preference, adherence and response. We are developing a database that will enable data to be collected across several studies with a network of participants to collect information about mental health across different conditions, contexts and tasks.
MIND Tools will create digital content and digital fusion through gamified interventions using VR, AR and mixed realities, bringing together a range of cross disciplinary researchers to integrate digital technologies for diagnostics, intervention and predictive analytics working together with Social Training & Anxiety Research (STAR) Lab and The Gaming for Innovation, Education, Climate and Society (GIECS) Lab.
MIND Sense will develop a muti sensory platform to provide objective metrics to quantify mental health, changes in mental state and emotion processing in condition like Parkinson’s Disease. This will be used both diagnostically and to measure change in conjunction with interventions. Non-invasive sensors will enable combined non-intrusive wearable and non-wearable measures with the user need and comfort and a central component.