Using wearable measures to infer moments in workload from Electrodermal Activity and individual workload from Heart...

Physiological measures offer potential for real-time collection of data to inform understanding of the nature of work in safety critical settings. This study collected physiological data from wearable measures to assess the Mental Workload (MWL) of twenty participants whilst they completed a simulated railway signalling task. Electrodermal Activity (EDA) and Heart Rate Variability (HRV) temporal data were compared to task demand (number of trains) and subjective workload. Average HRV showed a strong negative correlation with average subjective workload. EDA peaks indicated moments in workload including moments of realisation, uncertainty, or time pressure during the task in some participants. HRV and EDA results imply individuals vary in their experience of workload and physiological data can detect variation between participants. Results suggest EDA and HRV data could supplement existing measures of MWL during continuous tasks, through detecting both the timing of individuals' changing experience of workload and underlying physiological state.