Wearable devices and mobile phones are equipped with increasingly sophisticated sensors and processing capacity. This technology generates large volumes of multidimensional data, which can increasingly be linked to changes in symptoms and functional status.
In this research, presented at AAIC 2016, we describe the development of cognitive testing and mood data collection capabilities on a consumer wearable device, which also allows the measurement of physiological parameters.
Wearable-based cognitive testing was carried out using a 2-back memory paradigm. This task taps into several aspects of cognition, including attention, memory updating and working memory. Each test took one minute to complete.
A mixed quadratic growth model was applied to the data, modelling learning effects over time. This allowed for random intercepts, and slopes, with fixed quadratic terms.
There was good compliance with data collection, with more than 60 n-back trials being collected over the course of each day. Initial data supports the feasibility of cognitive and mood assessment alongside physiological parameters on wearable devices. This will enable daily cognitive testing, complementing periodic in-person assessment and in-clinic research interventions.
Interested in learning more about how wearable devices can be used in the high-frequency monitoring of cognition, mood and behaviour? Download this poster.