Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data

Abstract

The ability to understand and visualize big data sets is of increasing interest to caregivers and clinicians as ambient home sensing can provide massive amounts of data related to the activities of residents. However, this data is only useful if it can be effectively and simply visualized for review and analysis. This paper presents the visualization of longitudinal data sets from ambient well-being sensors deployed in 3 residences that have a spousal pair dyad where 1 resident has been diagnosed with Mild Cognitive Impairment or Dementia and the spousal partner is acting as a caregiver. The paper presents the differences in activity and behaviour that can be observed in the 3 residences by comparing two 30-day periods prior to and one 30-day period during COVID-19 social isolation precautions. The work shows the potential for this circle plot based visualization technique to summarize resident activity and also to convey external factors such as the variation in solar day that can itself influence behaviour.