BaselineNC™ Workplace Fatigue Monitoring Wearable Assessment Reconstruction скачать в хорошем качестве

BaselineNC™ Workplace Fatigue Monitoring Wearable Assessment Reconstruction

https://www.ihf.co.uk/workplace-fatig... This video is a reconstruction — using actors — of a BaselineNC assessment that was held in a tram simulator. The driver who took part in the assessment was deliberately fatigued in order to test the wearable device. The assessment results showed the pre-emptive detection of the onset of worker fatigue by BaselineNC HOURS before two visually observed microsleeps and self-assessment by the driver. Ultimately, BaselineNC was able to highlight the driver's steady decline to a state of dangerous fatigue. 0:22: To begin the assessment, a tram driver came off shift — as they were fatigued — to conduct a 4-hour tram simulator driving session. 0:36: Before starting the assessment, the driver logged a self-assessed Karolinska Sleepiness Scale (KSS) entry of "5. Neither alert nor sleepy". 1:03: As the simulated tram driving session progressed, the Integrated Human Factors (IHF) subject-matter expert (SME) assessor asked Situation Awareness Rating Technique (SART) questions to the driver at the end of each route. 1:16: At the start and end of each run, the driver was asked to provide a KSS score by the assessor. 1:30: The assessor was observing the driver during the whole process and made notes of behavioural performance. 1:41: The driver was also asked to do a Psychomotor Vigilance Task (PVT) test at set points at the end of each route as an objective measure to test reaction time. 2:15: After the various PVT tests, the tram driving simulation was resumed. 2:21: As the assessment progressed, the driver's self-assessed KSS level gradually increased. However, the BaselineNC algorithm was pre-emptively identifying amber and red levels of fatigue hours before a level 8 score was provided by the driver. 2:41: At the later stages of the tram driving simulation, two microsleeps were visually observed by the assessor and these correlated with the BaselineNC algorithm identifying red levels of fatigue. 3:14: Another visual observation made by the assessor was that a tram stop was missed. 3:27: The BaselineNC algorithm pre-emptively identified amber and red levels of fatigue hours before a level 8 KSS score was provided by the driver and two visually observed microsleeps. 3:42: The driver first self-identified as "unfit to drive" 5 minutes after the second visually observed microsleep. 3:57: The assessment results showed the pre-emptive detection of the onset of worker fatigue by BaselineNC HOURS before two visually observed microsleeps and self-assessment by the driver. Ultimately, BaselineNC was able to highlight the driver's steady decline to a state of dangerous fatigue. The BaselineNC workplace fatigue monitoring wearable project is also ‪@EITUrbanMobility‬ funded and was recently featured as part of the Impact Stories series:    • Wearable technology for human error preven...   #ergonomics #fatigue #fatiguemanagement #fatigueriskmanagement #humanfactors #publictransport #trams #workplacefatigue