Human performance in rail: determining the potential of physiological data from wearable technologies

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Human performance in rail: determining the potential of physiological data from wearable technologies

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 ar...

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Bibliographic Details
Main Author:	Fowler, Abigail
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2023
Subjects:	Wearable Physiological Measures; Human Performance; Mental Workload; EDA; HRV; Railway Signallers
Online Access:	https://eprints.nottingham.ac.uk/73986/

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