Alzheimer’s Disease (AD) represents a major and rapidly growing burden to the healthcare ecosystem. In the USA alone, some 5 million people suffer from the disease that costs the managed healthcare system in excess of $250 billion. Currently the sixth leading cause of death, AD prevalence has increased by 89% since 2000, underscoring the need for interventive and preventative measures.
There is growing interest in the identification of readily accessible digital biomarkers, which leverage widely available mobile and wearable technologies.

Mobile and wearable technologies (such as smart phones, tablets, smart watches, and rings, smart suits) present a unique opportunity to massively detect neurodegenerative diseases in a timely and economical fashion due to:

a) the widespread usage of such technologies

b) the immediate access of information due to the inherent connectivity

c) the increasing sensitivity and plurality of onboard sensors

d) the nature of these sensors that are uniquely equipped to study such physical and cognitive abilities or symptoms

e) the extremely low burden on the healthcare system, since these devices are increasingly in use by large segments of the population.

Onboard sensors at the heart of these systems are able to provide metrics by means of active (prompted) or passive (unnoticed) measurements, offering considerable flexibility in approach.

The application of digital phenotyping to neurodegenerative conditions has already shown promising results. Researchers have been able to detect users with neurodegenerative conditions such as Parkinson’s and Alzheimer’s from web search data. Research at digital health company Mindstrong (Palo Alto, CA) has shown that continuous data from seven days of passive smartphone interactions can predict performance on traditional assessments of memory, language, dexterity and executive function. However, digital phenotyping in neurodegenerative conditions is still in its infancy as groups have yet to establish a clear, functional link between these passive activities and the cognitive domains of interest. Nevertheless, there are certain passive digital scenarios and evolving associated metrics that appear to tie back to cognitive areas of interest.