Human performance in rail: determining the potential of physiological data from wearable technologies - Fowler, Abigail (2023)
This research focuses on how personal data from wearable physiological measures can be used to assess the Mental Workload (MWL) of staff in the rail industry. Automation technologies are being implemented in the rail industry to improve operational performance and capacity. These new technologies are changing the role of staff. This research considers how temporal physiological data present an opportunity to supplement existing workload assessment methods to measure the impact of these technology changes. The research explores how wearable physiological measures could be applied in live operations to collect real-time data with minimal task interference. Whilst the research focuses on railway signallers, the research has implications for other roles in the rail industry and other industries.