## 2 Fatigue in Working Contexts
#### Technologies for Human Fatigue Estimation and Detection  
Starting from the fact that the fatigue can be detected and identified in different parts of the day for the different chronotypes, the development and validation of technologies for detecting fatigued operators on a job is an important area of development [86]. There are different technologies to detect sleepiness/fatigue, including both objective and subjective measures, but they not always are applicable in a real-world setting. A variety of subjective measures of sleepiness/fatigue and alertness are available that request ratings about the near-immediate state of the subject. These include visual analogue scales [87], Likert-type rating scales such as the Stanford Sleepiness Scale [88], and the Karolinska Sleepiness Scale [89], and certain fatigue-related subscales of standard adjective checklists such as the Activation-Deactivation Adjective Check List [90], and Profile of Mood States [91]. Despite structural differences among these scales, all self-reports of sleepiness are highly intercorrelated and because they are relative psychometrics, they are subject to several sources of variance, including different uses of the scale response range by different subjects [92]. Subjective measures are considered vulnerable to numerous confounding factors influences that can \"mask\" their circadian rhythmicity and to be influenced by expectation, mind-sets, and intentional manipulation. Although there are considerably less convincing than objective measures, it has certain usefulness to be a simple alternative in many studies to detect repeated subjective ratings of sleepiness [93]. This is particularly effective in the real-life contexts and in work hours, in which this measure need not interrupt other activities for more than 10-15 s, and may be used frequently during the day. Moreover, in a recent review, [PERSON] and colleagues, (2014) [93], comparing different studies found a diurnal U-shaped pattern of sleepiness, with high KSS value in the morning and late evening with great stability across years. Furthermore, the results concerning to relation between of both KSS and sleep deprivation, and objective measures and KSS, drive the authors to conclude that subjective ratings of sleepiness are as sensitive and valid an indicator of sleepiness as objective measures. Polysomnographical (PSG) measurement, such as electroencephalagrafy (EEG) and the multiple sleep latency test (MSLT), has been a gold standard objective measures of sleepiness [94]. However, these electrophysiological variables are difficult to implement in real-life contexts and require equipment. Vigilant attention tasks are among the most sensitive measures of sleep loss and circadian periodicity; PVT, in particular, has proven to be very sensitive to all types of sleep loss and to be an example of probed performance fitness for duty test [95]. Psychomotor vigilance performance can be measured with the psychomotor vigilance task (PVT) [96], a portable, easily usable reaction time test with a high stimulus load (visual or auditory) that can yield rapid (i.e., in 10 min) and reliable assessments of psychomotor vigilance impairment [44; 97]. The PVT has been used in the laboratory to precisely measure, at brief intervals (typically every 2 h of wakefulness), the changes in psychomotor vigilance performance caused by sleep loss and circadian rhythmicity. The standard 10 min-PVT [95], and the briefer 3-min PVT (the brief PVT: PVT-B) [98] have been extensively validated to be sensitive to both acute and chronic partial sleep deprivation, revealing the temporal dynamics of sleep homeostatic and circadian interactions. The 10 min PVT version has become the most widely used measure of behavioral alertness and it has also been validated as a reliable measure to identify fatigue in occupational settings [99].