Non-invasive Smartphone Use Monitoring to Assess Cognitive Impairment

Background: There are many tests for the early detection of Mild Cognitive Impairment (MCI) to prevent or delay the development of dementia, particularly amongst the elderly. However, many tests are complex and are required to be performed repeatedly. Cognitive assessment apps for a smartphone have emerged, but like other tests, they require the user to perform complex tasks like drawing time on a clock. Few studies have explored non-invasive ways of tracking and assessing MCI without having the user perform specific tests. Objective: This research ultimately aims to develop an app that runs in the background and collects smartphone usage data that correlates well with MCI test results. The focus of this preliminary study was to develop an app that collects usage data and common MCI questionnaires to see if usage data between people varied, and to establish associations between phone usage and cognitive tests results. Method: An android application was developed to gather data over three weeks by three volunteers (authors). Usage data collected included: SMS and call log, accelerometer, location, app usage, self-report. Cognitive tests implemented were Stroop, Go/No Go tests and absentmindedness questionnaires. Due to the small sample size and Covid-19 restrictions (October 2020), location data was not reliable. SMS text was not collected for privacy reasons. Results: App categories can differentiate people, but the app usage cannot be used to distinguish people.