Applications in mental health research
In our second paper, “Evidence of Differences in Diurnal Electrodermal, Temperature, and Heart Rate Patterns by Mental Health Status in Free-Living Data”, we analyze data for a more specific context, mental health and wellbeing. EDA is a measure of sympathetic arousal that has been linked to depression in laboratory experiments. However, outside of controlled settings, the inability to measure EDA passively over time and in the real world has limited insights about EDA as an indicator of mental health status. The availability of an EDA sensor on a consumer device enabled us to conduct research (with informed consent) into mental-health applications of the device.
We used data collected with informed consent as part of a prospective, nonrandomized study to investigate patterns and relationships between digital device use patterns. This data included sensor data from phones and wearables reflecting both behavioral and physiological processes, and self-reported measures of mental health and well-being. The study protocol was four weeks long with passive sensing from a wearable (Fitbit Sense 2) for the complete four-week period. We examined the association between passively collected, diurnal variations in EDA and symptoms of depression, anxiety and perceived stress in this sample.
We found that subjects who exhibited elevated depressive and anxiety symptoms had higher SCL, skin temperature, and heart rate, despite not engaging in greater physical activity, compared to those that were not depressed or anxious. These differences were statistically significant and consistent throughout most of the day for SCL and heart rate. The elevation was most prominent in the early morning/night time hours. In contrast, subjects who only exhibited elevated stress, based on the Perceived Stress Scale (PSS), only exhibited higher skin temperature. Most strikingly, differences in EDA between those with high versus low symptoms were most prominent during the early morning, suggesting there could be a connection to early morning awakenings and sleep disorders that are linked to depressive orders. We did not observe amplitude or phase differences in the diurnal patterns. Our work suggests that electrodermal sensors may be practical and useful in measuring the physiological correlates of mental health symptoms in-situ and that recent consumer smartwatches might be a useful tool for doing so.