Diagnosis and Monitoring of Disease Progression Using Deep Neuro Signatures

Plain-language summary

Alzheimer's disease (AD) clinically characterized by the cognitive impairment and lowering of various functional abilities lead to staggering costs and suffering, which are particularly related to the social impacts of caring for increasingly disabled individuals. Some of these changes can be almost undetectable in the early stages of the disease, worsening over time often and at a varying rate of progression in different people. The traditional clinical scales or questionnaires such as ADCS (Alzheimer's Disease Cooperative Study) - ADL (Activities of Daily Living) for detecting such functional disabilities are typically blunt and rely on direct observation or caregiver recall. Digital technologies, particularly those based on the use of smart phones, wearable and/or home-based monitoring devices, here defined as 'Remote Measurement Technologies' (RMTs), provide an opportunity to change radically the way in which functional assessment is undertaken in AD, RMTs have potential to obtain better measurements of behavioral and biological parameters associated with individual Activities of Daily Living (ADL) when compared to the current subjective scales or questionnaires. Divergence from normative ADL profiles could objectively indicate the presence of incipient functional impairment at the very early stages of AD. Therefore, the main hypothesis of this study is that RMTs should allow the detection of impairments in functional components of ADLs that occur below the detection threshold of clinical scale or questionnaires.

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