Alzheimer’s disease (AD) is a major cause of the rapidly growing and crushing aging challenge that threatens to economically undermine today’s healthcare system. AD prevalence will grow to over 100 million cases in 2050. AD is incurable but can be prevented. Therefore, the most viable solution may be to detect very early signs of AD (presymptomatically) in citizens-at-risk and to intervene in time to reduce AD risk or prevent it entirely. The present project will refine and validate two breakthrough innovations for AD detection and AD prevention and commercialize them as a one-stop digital medical device, named ‘AD Detect & Prevent’. The first innovation is a highly sensitive cognitive assessment method recently pioneered by a group of researchers that has been shown to detect subtle presymptomatic stage cognitive decline specific to AD. This will be integrated with the second innovation – a digital AD prevention programme delivered on an award-winning computerized cognitive training and rehabilitation platform (app + web) that uses high intensity immersive and adaptive ‘neurogames’ and audio-based therapy for behavioural intervention, designed for strengthening core cognitive functions, building cognitive reserve, changing lifestyle and thus reducing the overall AD risk in individuals. The detection and prevention methods will undergo vigorous scientific validation, and the ambition is to create and become the global standard of care for precise presymptomatic detection of AD and effective AD prevention.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:36693 |
Date | 19 December 2019 |
Creators | Dong, Mia, Husain, Masud, Brooks, David, Wilson, Max, Craven, Michael, Destrebecq, Frédéric, Georges, Jean, Baden-Kristensen, Kim |
Publisher | TUDpress |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | 978-3-95908-183-2, urn:nbn:de:bsz:14-qucosa2-353220, qucosa:35322 |
Page generated in 0.0017 seconds