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Behavioural Sensing for the Understanding of Alzheimer's Disease Risk
Participants
Summary
In this theme the Health Technologies group in close collaboration with Norwich Medical School is conducting a range of studies in the use of ubiquitous technology such as geolocational trackers and the inertial sensors from tablet devices for assessing Alzheimer's disease risk. With this sensor data coupled with the use of machine learning techniques, our aims are to understand patterns in outdoor navigation trajectories and how they manifest within people with Alzheimer's disease as well as within control participants. In addition, we have contributed to the development of a novel tablet based vestibular rotation test within a genetic at-risk group of participants.
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Partners
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Funding
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Publications
[1] Puthusseryppady, V., Manley, E., Aung, M., Patel, M., and Hornberger, M. 2020. Alzheimer's disease patients getting lost in the community: Is road network structure a significant risk factor? Alzheimer's and Dementia, 16(S6), p.e042692.
[2] Puthusseryppady, V., Morrissey, S., Aung, M., Coughlan, G., Patel, M., and Hornberger, M. 2022. Using GPS tracking to investigate outdoor navigation patterns in patients with Alzheimer disease: cross-sectional study. JMIR Aging, 5(2), p.e28222.
[3] Hornberger M Coughlan G, Plumb W, Zhukovsky P, Aung MH. 2023. Vestibular contribution to path integration deficits in ‘at-genetic-risk’ for Alzheimer’s disease. PLoS ONE, 18(1), p.e0278239.