UNOBTRUSIVE PHONE MONITORING AS A NOVEL MEASURE OF COGNITIVE FUNCTION

Abstract

Cognitive health is key to overall function and wellbeing. However, standard assessments of cognition are time consuming, occur infrequently, and lack ecological validity. Given that cognitive status may fluctuate on varying time scales (e.g. daily, weekly, seasonally) and is context sensitive, it is important to develop methods of continuous, naturalistic assessment. In-home pervasive computing platforms, which continually monitor aspects of behavior corresponding to cognitive function, show great promise in this area. Here we examine whether phone use is related to cognition, with the goal of incorporating phone use into a broader set of metrics specifically tailored to monitor behavioral biomarkers of cognition. Phone monitors were installed in the homes of 26 independent elderly individuals from the ORCATECH Life Laboratory cohort (age 86 ± 4.5, 88% female) and used to monitor the total daily number of incoming phone calls for an average of 174 days. General cognitive status was assessed using a composite score composed of five Z-normalized cognitive domain tests. Because the daily number of incoming calls is a count variable, we used a mixed effects Poisson regression to model the effect of cognition on phone use controlling for age, sex, education, loneliness and pain. Individuals with higher cognitive function receive significantly more phone calls (β =0.41, p<0.01; 95% CI 0.141, 0.671) (Figure 1). People received fewer calls on the weekend than the weekday (β =-0.44, p<0.001; 95% CI -0.50, -0.39), and women received more calls than men (β =0.60, p<0.001; 95% CI 0.47, 0.74). Individuals reporting higher levels of pain also received more phone calls (β =0.047, p<0.05; 95% CI 0.0075, 0.086) while lonelier individuals received fewer calls, although this result was not significant (β =-0.0061, p=0.155; 95% CI -0.0144, 0.0023). Among independent elders, higher cognitive function positively influences phone activity as assessed by the number of phone calls received. Telephone activity may be used to assess subtle cognitive change in a continuous, unobtrusive manner. Incorporating such measures into in-home sensor platforms could enable earlier detection and treatment of cognitive decline. Future studies will explore these and related metrics across a wider range o f cognitive function. Probability density (color represents density; discrete probabilities were linearly interpolated for graphical clarity) of daily number of incoming calls (y-axes) as a function of cognitive Z-score, holding all other variables at their means. The mean function, μ (black trace) has been overlaid on the density to show central tendency. Number of received calls increases with cognitive function.