Fatigue. Edzard Boland, HF Research Exchange 6 april 2016

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1 Fatigue Edzard Boland, HF Research Exchange 6 april 2016

2 2

3 Human Factors en ETTO en keuzes... Stick and Rudder skills Procedural training Fatigue 3

4 Titel van presentatie, datum

5 5

6 6

7 Managing Fatigue 8

8 CAA UK Research question: Can fatigue be measured to predict a future deterioration in flight performance? Research goal: state of the art 9

9 Take away... 10

10 Research phases Select fatigue measurement techniques Define flying activities sensitive to fatigue Investigate fatigue measurement techniques Relate fatigue measurement and flying performance 11

11 Approach Define flying Relate fatigue Select fatigue Investigate activities measurement measurement these sensitive to and flying techniques techniques fatigue performance Select fatigue Fatigue / Sleepiness Flying Performance Psychomotor Vigilance Task (PVT) Electro-Encefalogram (EEG) Karolinska Sleepiness Scale (KSS) Heart Rate Variability (HRV) Eye parameters (blinks, pupil diameter,...)... 12

12 Approach Problem: Prediction of future performance from single timepoint Fatigue / Sleepiness PVT EEG HRV Pupil... Flying Performance Flying Performance= Relevant Fatigue fatigue? time 13

13 Approach Problem: Prediction of future performance from single timepoint Solution: Include history: multivariate autoregressive model Recent History Sleep Stress Light... Fatigue / Sleepiness PVT EEG HRV Pupil... Flying Performance Flying Performance= Relevant Fatigue fatigue? time 14

14 Approach Problem: Individual differences in the effect of fatigue on performance Recent History Sleep Stress Light... Fatigue / Sleepiness PVT EEG HRV Pupil... Flying Performance Flying Performance= Relevant Fatigue fatigue? time 15

15 Approach Problem: Individual differences in the effect of fatigue on performance Solution: Define multivariate individual profile Individual Sensitivity Recent History Fatigue / Sleepiness Flying Performance Individual Sensitivity Sleep Stress Light... PVT EEG HRV Pupil... Flying Performance= Relevant Fatigue fatigue? time 16

16 Selection of most feasible yet reliable combination Individual Sensitivity Recent History Fatigue / Sleepiness Flying Performance Individual Sensitivity Sleep Stress Light... PVT EEG HRV Pupil... Flying Performance= Relevant Fatigue fast, easy to undertake no specialist interpretation robust against falsification unambiguous socially acceptable non-invasive no learning effects 17

17 What is Fatigue? 18

18 Contributors to fatigue Expressions of fatigue Sleep Simple Circadian rhythm Behaviour Cognition Sleep latency Posture Complex Individual characteristics Fatigue Subjective fatigue Eye External conditions Physiology Brain Heart Stress Other 19

19 Contributors to fatigue Expressions of fatigue Actigraphy Sleep Derived Circadian from Actigraph rhythm Behaviour Cognition Sleep latency Posture PVT Simple 2-back Complex task Selfreporting Individual characteristics Fatigue Subjective fatigue KSS Eye movement Eye Ambient temperature and light and posture External conditions Selfreporting Stress Physiology EEG Brain Heart HRV Skin Other temp. 20

20 Competencies affected by fatigue Analysis of accidents & incidents involving flight crew fatigue How often competency-related failures contribute to the accident/incident 21

21 Assessing measurment and Assessing Performance Recent History ambulatory assessment Fatigue / Sleepiness lab assessment 7-day history: * sleep * activity * temperature * HRV * PVT * fatigue * light exposure * self-reporting Lab assessment: * light: dim vs bright * posture: supine vs upright * temperature: warm vs cool 22

22 Flight simulator: * flying activities affected by fatigue Flying Performance desktop flight simulator & full-flight simulator 23

23 Big Data ~30 files per subject >50 GB per subject 24

24 Results 1 Frequently mentioned: Problem Solving and Decision Making All core competencies are affected Self Directedness Increases resilience to effects of restricted sleep Fatigue questionnaires Are relatively reliable and simple means to estimate fatigue Subjective sleepiness Is more sensitive to sleep (disruption) than objective measures Predictors of momentary levels of sleepiness 1. Time awake 2. Posture 3. Light exposure 4. Time in bed 5. Skin temperature (DPG) 25

25 Results 2 Fit-to-Fly Test should control the time of day, skin temperature and posture Performance AIRSIM and GRACE flight simulator experiments indicated weak correlations between the fatigue measures and flight performance. much pilot performance variation that was not related to fatigue 26

26 Conclusion Fatigue assessment and prediction in an operational setting should consist of a multivariate assessment of physiology, behaviour, performance, environmental exposure, and sleep history. fast, easy to undertake no specialist interpretation robust against falsification unambiguous socially acceptable non-invasive no learning effects 27

27 Next To be published soon To be operationalised - later 28

28 29

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