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The sleep inertia phenomenon during the sleep-wake transition: Theoretical and operational issues



Sleep inertia (SI) defines a period of transitory hypovigilance, confusion, disorientation of behavior and impaired cognitive and sensory-motor performance that immediately follows awakening. SI, the cognitive and behavioral correlate of the transition from sleep to wakefulness, has been incorporated in several models of sleep and vigilance regulation. Monitoring of several physiological parameters during the awakening period clearly indicate that this transition process is very slow. On the cognitive and behavioral side, SI has relevant operational implications. SI is one of the most serious contraindications to the use of napping during quasi-continuous operations if the individual may be required to perform complex tasks immediately after sudden awakening at unpredictable times. The studies on SI modulating factors showed that SI is strongly affected by slow wave sleep amount and sleep depth, while the outcomes concerning the modulation of SI by circadian factors are not consistent. Cognitive tasks involving high attentional load seem to be much more affected by SI than simple motor ones, performance accuracy being more impaired than speed. Finally, some possible countermeasures against the detrimental effects of SI to be applied in operational settings have been provided.
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Department of Psychology, University of Rome "La Sapienza", Italy
Address reprint requests to:
Michele Ferrara, Ph.D.
Dipartimento di Psicologia
Università degli Studi di Roma “La Sapienza”
Via dei Marsi, 78; 00185 Roma, Italia
Tel.: +39-06-4991.7508
Fax: +39-06-44.51.667
Sleep researcher at the Sleep Psychophysiology Laboratory, Department of
Psychology, University of Rome “La Sapienza”, and consultant of Italian Air Force
Aerospace Medicine Department (C.S.V.), Pratica di Mare AFB (Rome), Italy.
This material has been partly published by the Research and Technology Agency,
North Atlantic Treaty Organization (RTO/NATO) in MP-31, Individual Differences
in the Adaptability to Irregular Rest-Work Rhythms. Status of the Use of Drugs in
Sleep-Wakefulness Management, 1999.
Running Head: Sleep Inertia: theoretical and operational issues
Sleep Inertia (SI) defines a period of transitory hypovigilance, confusion,
disorientation of behavior and impaired cognitive and sensory-motor performance
that immediately follows awakening. SI, the cognitive and behavioral correlate of the
transition from sleep to wakefulness, has been incorporated in several models of sleep
and vigilance regulation. Monitoring of several physiological parameters during the
awakening period cleary indicate that this transition process is very slow. On the
cognitive and behavioral side, SI has relevant operational implications. SI is one of the
most serious contraindications to the use of napping during quasi-continuous
operations if the individual may be required to perform complex tasks immediatly
after sudden awakening at unpredictable times. The studies on SI modulating factors
showed that SI is strongly affected by slow wave sleep amount and sleep depth, while
the outcomes concerning the modulation of SI by circadian factors are not consistent.
Cognitive tasks involving high attentional load seem to be much more affected by SI
than simple motor ones, performance accuracy being more impaired than speed.
Finally, some possible countermeasures against the detrimental effects of SI to be
applied in operational settings have been provided.
Index Terms: Sleep inertia, Sleep management, Performance upon awakening, Sleep-
wake transition
“Transitional states are among the most difficult to characterize and understand.
They occur during times of shifting priorities and constitute hybrid conditions which
borrow features from the more distinctive parent states. It follows that the more
complex and the greater the differences between the parent states, the more likely it
will be that the transitional processes will also be complex. For these reasons, there
has been a tendency to consider these states as somewhat confusional conditions to be
recognized and controlled for, but not often the subject of detailed study”(43). This
statement perfectly applies in particular to the transition from sleep to wakefulness.
In fact, while sleep onset has received increasing attention in the last two decades, the
emergence from sleep still remains a poorly understood phenomenon.
In this review we will focus our attention on Sleep Inertia (SI), a period of
transitory hypovigilance, confusion, disorientation of behavior and impaired
cognitive and behavioral performance that immediately follows awakening (30). SI
has been considered a "paradoxical" phenomenon (30) since performance upon
awakening is worse than before sleep. However, if physiological sleep phenomena
are best described by sinusoidal rather than by square-wave functions (5),
consequently the underlying behavioral states cannot readily be switched on and off
when shifting to another state. For this reason, if we consider the transition from sleep
to wakefulness as a complex process that takes some time to be completed, more than
an exact shifting point from one state of consciousness to another, SI simply becomes
the cognitive-behavioral face of this transition process.
SI has interesting theoretical and operational implications. It has been included as
an important component in several models of alertness and performance (1, 3, 20). It
integrates the influence of two other major components: a 24-h circadian component
(Process C), with a sinusoidal shape; and a homeostatic component (Process S), that
increases exponentially during wakefulness and is reversed during sleep. The
wakeup component, or Process W, was originally incorporated to take into account
the fact that people take some time to wake up properly (20). It takes the form of a
deviation from Process S that decreases in an asymptotic manner as a function of the
logarithm of hours awake, and ceases about 2-3 hours after awakening (20). Although
in the above-mentioned performance and alertness models SI acts independently of
Processes C and S, it is not possible to exclude that Process W may interact with
Process S in a non-linear manner (28). Consequently, the magnitude and/or the time
constant of the dissipation of SI may increase as a consequence of sleep deprivation
(so that S is very high).
SI is a robust phenomenon that must be taken into account in many operational
settings. The effects of sleep deprivation and chronobiological variations in
performance are undoubtedly among the most pervasive limitors of human ability in
all situations that require sustained periods of continuous performance and in
around-the-clock work settings (e.g. 12). These work scenarios are becoming
increasingly common, often involving highly skilled and dedicated personnel as in
sustained military operations, space flight preparation and launching, crisis and
catastrophe management (38). In all these situations, the negative effects of sleep loss
during sustained operations must be compared to the adverse effects of SI upon
abrupt awakening from sleep due to a possible emergency (11, 12). SI is one of the
most serious contraindications to the use of napping during quasi-continuous
operations if the individual may be required to perform complex tasks immediatly
after sudden awakening at unpredictable times (10).
Physiological Substratum
From a physiological point of view, a clear dissociation between different
parameters is evident during the awakening period. Based on the standard EEG
scoring system (44), the awake EEG is identified by a predominant alpha rhythm.
However, the EEG represent only a fraction of all the state-determining factors. In
other words, "the presence of all polygraphic features of one state does not mean that
no (unmonitored) variables of another state are present" (36). As an example,
Broughton (8) showed that visual evoked potentials (VEP) recorded upon awakening
are more similar to those obtained during sleep than to baseline waking values.
Following one-fourth of the arousals from slow-wave sleep (SWS), VEP contained an
apparent carry-over of typical SWS components. Even when there was no such carry-
over, the VEP regularly showed decreased amplitude and increased latency of 100-
300 msec components. No similar changes in visual evoked potentials were observed
after awakenings from REM sleep. The author ascribes these results to an impairment
of cerebral responsiveness ("functional deafferentation") after SWS awakenings, also
responsible for the behavioral changes (namely confusion) anecdotally reported only
after awakenings from slow-wave sleep.
Other indications of a slow shift from the sleep EEG substrate to that of
wakefulness come from the study of EEG power spectra during spontaneous sleep-
wake transitions (42). The spectral analysis (Fast Fourier Transform, FFT) of EEG
sampled during behaviorally identified (button pressing to stop a tone) spontaneous
arousals from sleep showed a non-predicted gradual and continued drop of theta
and delta power well into the first few minutes of wakefulness. Although delta
power decreased by almost 50% at the first behavioral response, there was a
statistically significant difference between sleeping and waking delta only after the
subject had responded to three consecutive tones (i.e., about 70 sec after the first
response). Theta power trend was very similar to that seen for delta frequencies.
Similarly, studies on cerebral blood flow - CBF - (e.g. 37) and cerebral blood flow
velocities - CBFV - during sleep (e.g. 24, 31) as indirect but reliable indexes of the
underlying neuronal metabolism and activity (e.g. 49), also suggest that the period
immediatly following nocturnal and morning awakenings have blood flow
characteristics that are not comparable to daytime levels. Moreover, Hajak and co-
workers (24) showed that upon morning awakening, subjects required up to half an
hour to reach CBFV values corresponding to the waking state of the previous
evening. The delayed increases in CBFV after awakening suggest an uncoupling of
cerebral electrical activity and cerebral perfusion and provide another example of
dissociation between different physiological parameters of sleep-wake transition,
further stressing the slowness of this transition.
SI and Sleep Management
SI has relevant operational implications. As already mentioned in the Introduction,
from a sleep-logistic perspective the main problem is to weigh the effects of sleep loss
on sleepiness and performance against the adverse effects of SI upon abrupt
awakening from sleep due to a possible emergency. From this point of view, one of
the most critical factors on SI concerns its duration and time course.
However, although SI has been incorporated in several models of sleep and
vigilance regulation (1, 3, 20), only a few attempts have been made to experimentally
quantify its time course. Most authors have typically made only one performance
assessment after awakening (e.g. 41), not allowing the determination of the time
course and duration of SI. Due to this methodological limitation, SI has been
generally reported to be short-lasting, being comprised between 1 and 20 minutes
(11, 26, 27, 34, 48).
Achermann and co-workers (2) addressed this issue by assessing subjective
alertness and reaction times in a memory task every 20 minutes (4 times) during the
first hour after awakening from nighttime sleep or from an evening nap, and finally
after three hours from each awakening. For both alertness and performance
measures, they found SI to persist for slightly less than one hour, and to subside
according to exponential functions with time constants of 0.45 and 0.30 hour,
respectively. More recently Jewett and coll. (28) reported that subjective alertness and
performance in an addition task show a sharp rise in the first hour after awakening
and begin to level off about 2 hours after awakening, reaching the baseline waking
values between 2 and 4 hours after awakening. Also in this case an asymptotic
dissipation of SI has been suggested, since a saturating exponential function
provided a good fit to the data for each measure. The time constants for the
dissipation of sleep inertia were 0.67 h in subjective alertness and 1.17 h in cognitive
performance (number of additions performed). Finally, in another study (17) it has
been found that performance accuracy in a subtraction task reaches the baseline level
after 30-45 minutes from the morning awakening, showing an increasing linear trend
during the first 75 minutes after awakening. On the other hand, although sensory-
motor (auditory reaction times) and simple motor (finger tapping) performances
were less affected by SI, they were still below baseline levels in the same period of
time, never reaching the baseline level during the testing period.
The differences in SI duration and time-course reported in the above-mentioned
studies (2, 28, 17) may be due to some relevant methodological differences between
them: as an example, Achermann et al. (2) did not assess SI between 1 h and 3 h after
awakening, while Ferrara et al. (17) gave no tests after the first 75 min from the
awakening. In addition, in the latter study SI was assessed upon awakenings placed
between 8 a.m. and 9 a.m. after nocturnal sleep episodes of 7.5 h characterized by
different sleep homeostasis conditions (comprising SWS deprivation and recovery
nights), while in the former SI was assessed at 7 a.m. after nocturnal sleep, as well as
at about 9 p.m. after an early evening nap. Furthermore, the Jewett et al. data (28)
were collected in an environment free of time cues, and during the third day of the
experiment subjects were exposed to very dim light during a constant routine
Differences in reported results can also be due to possible differential sensitivity of
the performance tasks used to assess SI. As an example, the time constant for the
dissipation of SI in cognitive performance (number of additions performed) found by
Jewett et al. (28) is much larger than that reported for reaction times in a short term
memory task by Achermann et al. (2), suggesting that some neurobehavioral
functions may be more sensitive to SI than others.
In conclusion, the discrepancies in the reported time-course and duration of SI are
accounted for by large differences in the experimental paradigms used, leading to
uncontrolled interactions between homeostatic and circadian (time-of-day) processes
regulating sleep and wakefulness, as well as to the use of several different tasks and
variables to assess SI.
SI: Modulating Factors
SI duration and magnitude can be modulated by several factors. There are
differential effects of REM/NREM sleep stages on performance upon awakening.
More specifically, SWS awakenings have often been reported to have greater
negative effects on subsequent performance than REM sleep awakenings. These
effects have been demonstrated with a wide array of tasks: simple motor tasks (54,
55); sensory-motor tasks (16, 47); and cognitive tasks (47, 51). However, it is not clear
whether the above-mentioned differential effects are due to neurophysiological,
psychophysiological and functional differences between REM and NREM states, or
whether to uncontrolled temporal and circadian influences (time-of-night effects), or
to an interaction between the two. All these variables should require further
exploration with a more controlled research methodology.
Furthermore, it has been claimed that sleep structure is also very important in
determining SI (11). The increased sleep depth (in terms of both amount of SWS and
sleep stage at awakening) caused by sleep deprivation dramatically exacerbate SI and
cognitive impairment upon awakening from recovery sleep (10). It has also been
found that cognitive decrements after abrupt awakenings from 1 and 2 hour naps
show a linear relationship with SWS amount during the nap (10, 15).
Moreover, the negative influence of sleep deprivation on SI seems to interact with
time-of-night or circadian factors in producing even more dramatic effects. As an
example, Naitoh (40) reported that, after a 2-hour nap taken early in the morning
(0400-0600 a.m.) following 45 hours of continuous work without sleep, both task
performance and self-rating of mood, sleepiness and fatigue remain deteriorated up
to 6 hours. This long-lasting sleep inertia effect was not observed when a nap of the
same duration was taken at 1200-1400, after 53 hours of wakefulness; in fact,
following this midday nap, sleep inertia disappeared within 1 hour and was then
replaced by improvements.
More generally, the outcomes concerning the modulation of SI by circadian factors
- mainly linked to body temperature rhythm - are not consistent. Conflicting
evidence comes from studies of napping with and without previous sleep
deprivation (e.g. 7, 41, 52), as well as from repeated awakenings during nocturnal
sleep (e.g. 4, 45, 46). As an example, Bonnet & Arand (7) reported a worsening of SI
effects following awakening at 5:00 a.m., but some other studies showed greatest
performance impairment upon awakenings placed in the first part of the night (22,
23, 52). It is evident that these approaches necessarily confound the effects of the
circadian phase with those of homeostatic variables (i.e., the amount of prior sleep or
of prior sleep loss, if sleep deprivation is involved). However, this problem is difficult
to solve, if possible at all, since both of these factors are temporal dimensions that
covary with each other (10). For these reasons, the available evidence for circadian
modulation of SI can not be considered definitive, and a more accurate description of
circadian influences on SI needs the support of further empirical data collected with
sound methodology.
Moreover, SI seems to dramatically depend on the type of task used, highly
demanding cognitive and attentional tasks being much more affected than simple
motor ones (39). As regards the impairment of simple sensory-motor performance
(auditory reaction times and finger tapping task) upon awakening, a recent study
(18) reported that it is accounted for by: a general decrement in overall response
speed (median of RT); a decrease in response speed in the "optimum response
domain"; and an increase of lapsing. Consequently, behavioral performance slowing
upon awakening is not simply due to lapses or failure to respond, but should be
ascribed to a general decline in the ability to allocate attention to the task and to give
the required motor response as fast as possible. As regards cognitive performance, at
variance with physiological sleepiness, which in self-paced tasks affects speed of
performance more than accuracy (6, 13, 14), it has been claimed that SI exerts a
negative influence on both, but particularly on the latter (4, 41). Some recent evidence
confirmed that the lowered level of brain arousal upon awakening adversely affects
cognitive performance accuracy more than performance speed. (19).
In conclusion, although it is often difficult to compare results of studies on SI, since
several different experimental designs and tasks have been used, a few clear
indications seem to emerge. The intensity of SI is strongly influenced by some
homeostatic sleep variables linked to SWS amount and, more generally, to depth of
sleep (indexed by awakening thresholds or by sleep stage at awakening). Moreover,
circadian factors and previous sleep loss exacerbate SI by adding their simple effects.
Finally, cognitive tasks involving high attentional load seem to be much more
affected by SI than simple motor ones, performance accuracy being more impaired
than speed.
Possible Countermeasures
From a review of the literature on the physiological basis and modulating factors
of SI, we will try to suggest some countermeasures against the detrimental effects of
SI on performance upon awakening, to be applied when it is possible in operational
The first countermeasure could be to reduce the probability of awakening out of
SWS, since it is well known that SWS awakenings yield the greatest performance
decrements. One possibility is to allow sleep when the occurence of SWS is very low
(e.g., in the morning). Another strategy can be to allow naps of about 80-100 minutes
(i.e., the mean range of duration of normal NREM-REM sleep cycles), or,
alternatively, of about 20 minutes, minimizing the probability of a SWS awakening.
Some experimental data confirm the usefulness of this strategy, by showing that SI
magnitude after a 20-min and a 80-min nap are very similar, while the worst
performance upon awakening is recorded after a 50-min nap (50). Obviously, a 80-
min nap should be preferred to a 20-min nap because of its greater restorative power.
Another very important strategy to minimize SI is to avoid a long period of
wakefulness before allowing a nap, since the increase of sleep depth caused by sleep
deprivation dramatically exacerbates SI (10, 40). As already suggested by others (10),
sleep opportunities should be provided before sleep loss accumulates beyond 36
hours, since longer and more severe performance decrements have been reported on
awakening from naps taken after this time as compared to naps taken within 30
hours of wakefulness (10, 40).
In addition, awakening near the circadian nadir of body temperature should also
be avoided, especially if the sleep period follows sleep deprivation (40).
It has been reported that washing one's face with cold water immediately after
awakening is a simple but effective tool to fight SI (32, 33). More generally, every
"alerting" factor (i.e., noise, light, physical exercise) should be useful in counteracting
SI, even though - at present - only few attempts have been made to assess their
effectiveness. As an example, pink noise (75 dBA) administered during the first hour
after awakening improves response speed at 0500 but not at 0800, when it has
detrimental effects on performance (53). Although the authors claimed that all
subjects experienced the same amount of prior sleep debt, since each of them slept
for three hours during the experimental night, it has to be noted that the group
woken up at 0800 possibly experienced a greater homeostatic pressure for sleep,
because their sleep time was postponed by two hours as compared to the group
woken up at 0500. Consequently, the different homeostatic pressure acted as a
possible confounding variable, casting some doubts on the interpretation of results.
More recently, it has been reported that following the "normal morning routine"
(i.e., getting out of bed, taking a shower, having breakfast) does not abolish SI as
compared to a constant routine in bed (28). In the same experiment (28), it was found
that exposure to normal room light (about 150 lux) upon awakening did not improve
performance as compared to very dim light (about 20-25 lux). However, it has to be
noted that in the above-mentioned study (28) the exposure to very dim light was
introduced on the awakening of the third experimental day together with a constant
routine condition. Consequently, it is difficult to dissociate the effects of the dim light
condition and those of the constant routine. Moreover, any question about a possible
alerting effect of bright light remains unanswered; it may be that, to detect an
alerting effect, a very bright light (i.e. 2000 lux) upon awakening should have been
used (see below).
SI: Open Questions
SI is still a poorly understood phenomenon from both the point of view of its
physiological substratum, which could be approached in the near future with
neuroimaging techniques, and of the sleep-related modulating factors and
psychological and personality variables that may influence it. However, a few
research areas that should be explored to give important answers on SI, also to be
applied in operational fields, will be pointed out.
The first unexplored topic is the role of individual differences in reactions to the
effects of SI. It is anecdotally well-known that individuals show a wide range of
variation with respect to their perceived ability to function immediately after
awakening. However, the literature on SI has definitely ignored this problem,
relegating individual differences to a role of "confusing variable" to be controlled.
The study of individual difference modulation of SI will add very important
knowledge to the definition of the psychophysiological profile of tolerance of
irregular work hours. As an example, it could be intersting to explore the relation
between diurnal type and SI, since the morningness-eveningness dimension has been
associated with the adjustment to shift work (21, 25, 29).
The same applies to the role of psychological factors, like motivation, in the
modulation of SI. As an example, one should believe that motivation can be a strong
and efficient countermeasure to SI for a fighter pilot sleeping on-call, when he is
requested to be in the cockpit at 5000-10000 metres a.s.l. just 5 minutes after abrupt
awakening. However, this topic should be specifically evaluated.
For operational purposes, the duration and time course of SI after naps taken at
different times of the day should also be further assessed, since available data are
inconclusive. Varying nap duration may also be necessary for a complete
understanding of these aspects of SI.
It would be very important to have some pharmacological countermeasures to SI,
such as very fast acting stimulants, to be used in operational settings when the need
for high levels of alertness and performance immediately after awakening should
arise. To our best knowledge, the use of stimulants to counteract SI effects has never
been tried, not even in laboratory settings.
Non-pharmacological countermeasures to SI could also be very useful,
particularly because pharmacological measures are currently lacking. Generally
speaking, any alerting factor could be assessed to counteract SI: physical and/or
mental exercise, external noise, bright light. As regards noise, although in at least one
study pink noise has been administered for one hour after awakening with non-
univocal results (53), the effectiveness of different types of noise with different
intensities and durations should be assessed. Bright light might also be effective
against SI, since its alerting effects are well established (e.g. 9).
Several observations on the physiological correlates of the sleep-wake transition (8,
24, 31, 37, 42) are in line with evidence coming from human studies on cognitive (e.g.
51) and behavioral (e.g. 54) features of awakening from sleep, pointing out the need
to re-define the sleep-to-wake transition period as a neurophysiologically distinct
state. In other words, emerging from sleep can not be identified with an exact shifting
point from one state of consciousness (sleep) to another (wakefulness), but is better
described as a complex and slow process that takes some time to be completed.
During this transition period, that shares some features with both the wake and sleep
states, a clear dissociation between different parameters (physiological, cognitive and
behavioral) is evident, since they show different rates of change from the sleep
pattern to the wake pattern.
Consequently, in such a situation the subject may still be able to conduct some
simple social interaction (e.g. 11) but the "functional deafferentation", proposed by
Broughton (8) to explain the low levels of brain reactivity upon awakening, will make
it difficult to obtain more demanding and complex performance. For these reasons, in
all these situations requiring highly skilled performance immediatly after an abrupt
awakening (e.g., sustained military operations, medical emergency management), the
unavoidable adverse effects of SI have to be considered in advance, providing
personnel with simple tools to wash out these effects. At the present, the use of any
feasible alerting factor (physical exercise, external noise, bright light, cold water) can
only be suggested. Further research is needed to experimentally clarify which are the
most effective tools to be applied in operational settings.
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... When the end of a specific "operational design domain" (SAE, 2018) is reached, for example at a motorway exit, the automated driving system issues a request to intervene and the driver needs to take back vehicle control. When drivers are asleep during the automated drive and awakened by the system's request to intervene, they might face difficulties in taking back vehicle control: after waking up, humans experience a period of sensory-motor and cognitive impairment, typically referred to as "sleep inertia" (Ferrara & De Gennaro, 2000). Drivers' reactions are commonly delayed after sleep (Wörle, Metz, Othersen, & Baumann, 2020) and their lane-keeping and speed-keeping behavior is impaired . ...
... They reported that after awakening from a nap they felt disoriented and not fit for duty (Fallis, McMillan, & Edwards, 2011;Gregory, Winn, Johnson, & Rosekind, 2010). This observation is called sleep inertia, defined as a "period of transitory hypovigilance, confusion, disorientation of behavior and impaired cognitive and sensory-motor performance that immediately follows awakening" (Ferrara & De Gennaro, 2000). Various operator guidelines in aviation (CASA, 2013; EASA, 2019; IATA, 2015) recommend a procedure called the 'NASA nap' (Rosekind et al., 1994) to balance the benefits of napping with the risks associated with sleep inertia: According to this routine, the duration of a rest period is restricted and after the rest period a transitional phase should be allowed to let sleep inertia dissipate before returning to duty. ...
... One study found no effect of sleep inertia after a 10 min nap on steering and speed behavior compared to a heavily sleep-deprived control group (Hilditch, Dorrian, Centofanti, Van Dongen, & Banks, 2017) while a study on drivers awakening after EEG-confirmed stable sleep found lane-and speed-keeping behavior to be deteriorated . A nap of only 10 min cannot be expected to produce substantial sleep inertia (Ferrara & De Gennaro, 2000;Tassi & Muzet, 2000). Other studies found no sleep inertia impairments after a 10-min nap, but impairments after a 30-min nap were evident for 35 min after awakening (Brooks and Lack, 2006). ...
Objectives Driver sleepiness is one of the major safety issues in conventional driving and sleep inertia emerges as a driver state in automated driving. The aim of the present study was to assess the differential impacts of sleepiness and sleep inertia on driving behavior. Method 61 participants completed a 10-min manual driving task during an otherwise automated drive. They completed the task (a) under an alert state, (b) under a sleepy state, and (c) after EEG-confirmed sleep. Driving performance was assessed with the parameters lane-keeping, speed choice, and speed-keeping. The eye-blink-based sleepiness measure PERCLOS (the proportion of time with eyes closed) was compared for the three driver states. Results Lane- and speed-keeping performance were impaired under the sleepy state and after sleep, relative to the alert state. After sleep, lane-keeping behavior recovered rapidly and speed-keeping recovered by trend. Under the sleepy state, performance deteriorated. After sleep, the mean speed was lower than in the sleepy state and in the alert state. PERCLOS was increased after sleep and under the sleepy state, relative to the alert state. Conclusions Although sleep inertia had detrimental effects on driving parameters similar to sleepiness, this effect rapidly vanished. Hence, while brief naps might be suitable to restore alertness in general, the minimal time needed to regain full capacity after napping should be a focus of future research.
... Sleep inertia is a well-documented period of impaired cognitive and sensory motor performance and disorientation after waking from sleep, especially daytime naps. 16,17 There is some evidence to indicate that athletic performance is less susceptible to the effects of sleep inertia, 18 but there are a number of factors to consider when assessing this evidence. In particular, sleep inertia tends to be more severe following longer naps compared with shorter naps, 19 but the nap duration provided in most experimental studies examining the impact of daytime naps on athletic performance is short (approximately 20-30 min). ...
... Sleep inertia is a well-documented period of impaired cognitive and sensory motor performance and disorientation after waking from sleep, especially daytime naps. 16,17 In the present study, there was no effect of sleep inertia on sprint ability, but agility was slower across the test batteries in the 2 napping conditions compared with the control condition. Although agility was not statistically significant between conditions, medium to large effect sizes were observed. ...
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Purpose: This study examined the impact of sleep inertia on physical, cognitive, and subjective performance immediately after a 1- or 2-hour afternoon nap opportunity. Methods: Twelve well-trained male athletes completed 3 conditions in a randomized, counterbalanced order-9 hours in bed overnight without a nap opportunity the next day (9 + 0), 8 hours in bed overnight with a 1-hour nap opportunity the next day (8 + 1), and 7 hours in bed overnight with a 2-hour nap opportunity the next day (7 + 2). Nap opportunities ended at 4:00 PM. Sleep was assessed using polysomnography. Following each condition, participants completed four 30-minute test batteries beginning at 4:15, 4:45, 5:15, and 5:45 PM. Test batteries included a warm-up, self-ratings of readiness to perform, motivation to perform and expected performance, two 10-m sprints, 2 agility tests, a 90-second response-time task, and 5 minutes of seated rest. Results: Total sleep time was not different between conditions (P = .920). There was an effect of condition on readiness (P < .001), motivation (P = .001), and expected performance (P = .004)-all 3 were lower in the 8 + 1 and 7 + 2 conditions compared with the 9 + 0 condition. There was no effect of condition on response time (P = .958), sprint time (P = .204), or agility (P = .240), but a large effect size was observed for agility. Conclusions: After waking from a nap opportunity, agility may be reduced, and athletes may feel sleepy and not ready or motivated to perform. Athletes should schedule sufficient time (∼1 h) after waking from a nap opportunity to avoid the effects of sleep inertia on performance.
... The difference among the studies concerning the time course of SI can derive from methodological standpoints. First, only a few studies have investigated the time course of SI dissipation by measuring performances at regular time intervals and for a long time [22]. Indeed, most authors have typically made only one performance assessment after awakening (e.g., [23]). ...
... With regard to accuracy, we did not find any effects. Our results agreed with those of Balkin and Badia [57], suggesting that performance speed and accuracy are differentially affected by SI during the sleep-wake transition [4,22,55]. This finding could indicate that RT is an index that is more sensitive to the SI effect. ...
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Sleep inertia (SI) refers to a complex psychophysiological phenomenon, observed after awakening, that can be described as the gradual recovery of waking-like status. The time course of cognitive performance dissipation in an everyday life condition is still unclear, especially in terms of the sleep stage at awakening (REM or NREM-stage 2) and the relative effects on performance. The present study aimed to investigate the SI dissipation in different memory performances upon spontaneous morning awakening after uninterrupted nighttime sleep. Eighteen young adults (7 females; mean age 24.9 ± 3.14 years) spent seven non-consecutive nights (one baseline, three REM awakenings and three St2 awakenings) in the laboratory under standard polysomnographic (PSG) control. Participants were tested after three REM awakenings and three St2 awakenings, and three times at 11:00 a.m. as a control condition. In each testing session, participants filled in the Global Vigor and Affect Scale and carried out one memory task (episodic, semantic, or procedural task). For each condition, participants were tested every 10 min within a time window of 80 min. In accordance with previous studies, SI affected subjective alertness throughout the entire time window assessed. Moreover, SI significantly affected performance speed but not accuracy in the semantic task. With reference to this task, the SI effect dissipated within 30 min of awakening from REM, and within 20 min of awakening from St2. No significant SI effect was observed on episodic or procedural memory tasks.
... Sleep inertia dissipates with time awake, with estimates of its typical duration ranging from 20 to 30 min (Dinges et al., 1987;Tassi et al., 1992) to 1-2 h post-awakening (Jewett et al., 1999). Although sleep inertia occurs even in the absence of sleep debt (Akerstedt and Folkard, 1997), its effects are more profound and long-lasting after a period of sleep deprivation (Ferrara and De Gennaro, 2000). Finally, waking up from slow-wave sleep appears to have the most profound negative impact on subsequent vigilance and performance (Dinges, 1990;Bonnet, 1993;Matchock and Mordkoff, 2014). ...
... If this hypothesis is correct, then we predict that neural inertia should be larger when awakening from "recovery sleep" after sleep deprivation, since sleep deprivation increases the sleep inertia that is observed after awakening (Ferrara and De Gennaro, 2000). This is precisely what is observed empirically, with higher neural inertia in previously sleep-deprived animals (Joiner et al., 2013). ...
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“Neural inertia” is the brain’s tendency to resist changes in its arousal state: it is manifested as emergence from anaesthesia occurring at lower drug doses than those required for anaesthetic induction, a phenomenon observed across very different species, from invertebrates to mammals. However, the brain is also subject to another form of inertia, familiar to most people: sleep inertia, the feeling of grogginess, confusion and impaired performance that typically follows awakening. Here, we propose a novel account of neural inertia, as the result of sleep inertia taking place after the artificial sleep induced by anaesthetics. We argue that the orexinergic and noradrenergic systems may be key mechanisms for the control of these transition states, with the orexinergic system exerting a stabilising effect through the noradrenergic system. This effect may be reflected at the macroscale in terms of altered functional anticorrelations between default mode and executive control networks of the human brain. The hypothesised link between neural inertia and sleep inertia could explain why different anaesthetic drugs induce different levels of neural inertia, and why elderly individuals and narcoleptic patients are more susceptible to neural inertia. This novel hypothesis also enables us to generate several empirically testable predictions at both the behavioural and neural levels, with potential implications for clinical practice.
... Sleep inertia refers to the drowsy feeling and the transient impaired cognitive performance immediately at the awakening [15][16][17]. Surprisingly, Wertz et al. [18] showed that the effect of sleep inertia could be more severe than 26 h of sleep deprivation on a short-term memory task. The intensity and the duration of sleep inertia depend on the time of the day, the awakening duration before the nap, and also the duration of SWS during the nap [15][16][17]. ...
... Surprisingly, Wertz et al. [18] showed that the effect of sleep inertia could be more severe than 26 h of sleep deprivation on a short-term memory task. The intensity and the duration of sleep inertia depend on the time of the day, the awakening duration before the nap, and also the duration of SWS during the nap [15][16][17]. It has been shown that sleep inertia lasts between 10-15 min after a 50 min nap [19] and no more than 15 min after napping for 60 min or less [20]. ...
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To compare the effects of two nap opportunities (20 and 90 min) to countermeasure the transient naturally occurring increased sleepiness and decreased performances during the post-lunch dip (PLD). Fourteen highly trained judokas completed in a counterbalanced and randomized order three test sessions (control (Nonap), 20- (N20) and 90-min (N90) nap opportunities). Test sessions consisted of the running-based anaerobic sprint test (RAST), simple and multiple-choice reaction times (MCRT) and the Epworth sleepiness scale (ESS). From the RAST, the maximum (Pmax), mean (Pmean) and minimum (Pmin) powers were calculated. Blood samples were taken before and after the RAST to measure the effect of pre-exercise napping on energetic and muscle damage biomarkers and antioxidant defense. N20 increased Pmax and Pmean compared to No-nap (p < 0.001, d = 0.59; d = 0.66) and N90 (p < 0.001, d = 0.98; d = 0.72), respectively. Besides, plasma lactate and creatinine increased only when the exercise was performed after N20. Both N20 (p < 0.001, d = 1.18) and N90 (p < 0.01, d = 0.78) enhanced post-exercise superoxide dismutase activity compared to No-nap. However, only N20 enhanced post-exercise glutathione peroxidase activity (p < 0.001, d = 1.01) compared to pre-nap. Further, MCRT performance was higher after N20 compared to No-nap and N90 (p < 0.001, d = 1.15; d = 0.81, respectively). Subjective sleepiness was lower after N20 compared to No-nap (p < 0.05, d = 0.92) and N90 (p < 0.01, d = 0.89). The opportunity to nap for 20 min in the PLD enhanced RAST, MCRT performances, and antioxidant defense, and decreased sleepiness. However, the opportunity of 90 min nap was associated with decreased repeated sprint performances and increased sleepiness, probably because of the sleep inertia.
... Following the same example above, for drivers waking from a nap, the transition from sleep to wakefulness is characterised by "hypovigilance, confusion, disorientation of behaviour, and impaired cognitive and sensory-motor performance" (Ferrara & De Gennaro, 2000). ...
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Real-time monitoring of drivers’ functional states will soon become a required safety feature for commercially available vehicles with automated driving capability. Automated driving technology aims to mitigate human error from road transport with the progressive automatisation of specific driving tasks. However, while control of the driving task remains shared between humans and automated systems, the inclusion of this new technology is not exempt from other human factors-related challenges. Drivers’ functional states are essentially a combination of psychological, emotional, and cognitive states, and they generate a constant activity footprint available for measurement through neural and peripheral physiology, among other measures. These factors can determine drivers’ functional states and, thus, drivers’ availability to safely perform control transitions between human and vehicle. This doctoral project aims at investigating the potential of electrocardiogram (ECG), electrodermal activity (EDA) and functional near-infrared spectroscopy (fNIRS) as measures for a multimodal driver state monitoring (DSM) system for highly automated driving (i.e., SAE levels 3 and 4). While current DSM systems relying on gaze behaviour measures have proven valid and effective, several limitations and challenges could only be overcome using eye-tracking in tandem with physiological parameters. This thesis investigates whether ECG, EDA and fNIRS would be good candidates for such a purpose. Two driving simulator studies were performed to measure mental workload, trust in automation, stress and perceived risk, all identified as modulators of drivers’ functional states and that could eventually determine drivers’ availability to take-over manual control. The main findings demonstrate that DSM systems should adopt multiple physiological measures to capture changes in functional states relevant for driver readiness. Future DSM systems will benefit from the knowledge generated by this research by applying machine learning methods to these measures for determining drivers’ availability for optimal take-over performance.
... Especially after a long engagement in alternative activities, it can be challenging to take over manual control. For example, for drivers waking from a nap, the transition from sleep to wakefulness is characterised by "hypovigilance, confusion, disorientation of behaviour, and impaired cognitive and sensory-motor performance" [25], and drivers in such a state would likely be impaired for taking over manual control. Another case could be those drivers that have been engaged in a mentally demanding task (e.g. ...
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Highly automated driving will likely result in drivers being out-of-the-loop during specific scenarios and engaging in a wide range of non-driving related tasks. Manifesting in lower levels of risk perception to emerging events, and thus affect drivers' availability to take-over manual control in safety-critical scenarios. In this empirical research, we measured drivers' (N = 20) risk perception with cardiac and skin conductance indicators through a series of high-fidelity, simulated highly automated driving scenarios. By manipulating the presence of surrounding traffic and changing driving conditions as long-term risk modulators, and including a driving hazard event as a short-term risk modulator, we hypothesised that an increase in risk perception would induce greater physiological arousal. Our results demonstrate that heart rate variability features are superior at capturing arousal variations from these long-term, low to moderate risk scenarios. In contrast, skin conductance responses are more sensitive to rapidly evolving situations associated with moderate to high risk. Based on this research, future driver state monitoring systems should adopt multiple physiological measures to capture changes in the long and short term, modulation of risk perception. This will enable enhanced perception of driver readiness and improved availability to safely deal with take-over events when requested by an automated vehicle.
... Similarly, it has been shown that 60-min naps induce severe sleep inertia [69]. Importantly, Davies et al. [67] considered that a 90-min nap duration is optimal as it allows a complete sleep cycle (NREM + REM) to occur and thereby could reduce the severity of sleep inertia, since REM sleep is a lighter sleep state and waking up from this sleep stage is easier [70]. These findings provide supplementary evidence for the hypothesis that the optimal diurnal nap duration for athletes might be 90 min to avoid the impairment of performance due to sleep inertia [71]. ...
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Objective: (i) To evaluate the effectiveness of diurnal napping opportunities on athletes’ physical and cognitive performance and (ii) to outline how aspects of the study design (i.e., nap duration, exercise protocol, participants’ fitness level and previous sleep quantity) can influence the potential effects of napping through a systematic appraisal of the literature. Methods: This systematic review was conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. PubMed, Web of Science and SCOPUS databases were searched up to June 2020 for relevant studies investigating the effect of napping on physical and cognitive performances in physically active participants. Fourteen strong-quality and four moderate-quality (mean QualSyst score = 75.75 ± 5.7 %) studies met our inclusion criteria and were included in the final sample (total participants: 158 physically active and 168 athletes). Results: Most studies (n = 15) confirmed the beneficial effects of napping and showed that diurnal napping improved short term physical performance (n = 10), endurance performance (n = 3) and specific skill performance (n = 2). Two studies showed no significant napping effect and only one study showed reduced sprint performance following diurnal napping. Moreover, napping improved reaction time (n = 3), attention (n = 2) and short-term memory (n = 1) performances. Importantly, “replacement naps” showed to improve both physical and cognitive performances regardless of the type of exercise. However, “prophylactic naps” showed to only improve jump, strength, running repeated-sprint, attention and reaction time performances. Additionally, this systematic review revealed that longer nap opportunities (i.e., 90 min) resulted in better improvement of physical and cognitive performance and lower induced fatigue. Conclusions: A diurnal nap seems to be an advantageous intervention to enhance recovery process and counteract the negative effect of partial sleep deprivation on physical and cognitive performance. Particularly, in order to optimise physical performances of athletes experiencing chronic lack of sleep, findings from the included individual studies suggest 90 min. as the optimal nap duration. Diurnal napping may be beneficial for athletes but this benefit should be viewed with caution due to the quality of the evidence, risk of bias and the limited evidence about napping interventions.
... In fact, REM sleep was previously shown to enhance muscular efficiency[26], which represents a key factor in both UST and LST tests. Additionally, a complete sleep cycle (NREM + REM) has been suggested to reduce the severity of sleep inertia, since REM sleep is a lighter sleep state and waking up from this sleep stage is easier[48]. Concordantly, recent studies have reported that longer naps elicited a stronger effect on enhancing physical performance[9,26,49]. Thus, longer nap durations may be more suitable to generate significant improvements in postural balance during complex motor activities recurring high muscular efficiency. ...
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Although napping is commonly used as a strategy to improve numerous physical and cognitive performances, the efficacy of this strategy for improving postural balance has not yet been elucidated. Thus, the aim of this study was to conduct a comprehensive examination of the effect of a 60min nap opportunity (N60) on different components of postural control. Ten highly active individuals (age= 27±3.5 y, height= 1.75±0.52 m, weight= 66.02 ± 8.63kg) performed, in a randomized order, two afternoon test sessions following no nap (NN) and N60. Postural balance was assessed using the sensory organisation test (SOT), the unilateral stance test (UST), and the limits of Stability Test performed on NeuroCom® Smart Balance Master. The subjective rating of sleepiness before and after the nap conditions was also assessed. Compared to NN, N60 improved the composite balance score (p<0.05, ES = 0.75, Δ=5.3%) and the average and maximum percentage balance in the most challenging postural conditions of the SOT (p<0.05 for SOT-4 and 5 and p<0.0005 for SOT-6; ES range between 0.58 and 1.1). This enhanced postural balance in N60 was accompanied with improved visual (p<0.05; ES=0.93; Δ=8.9%) and vestibular (p<0.05; ES=0.81; Δ = 10.5%) ratios and a reduced level of sleepiness perception (p < 0.001, ES=0.87). However, no significant differences were found in any of the UST and LOS components’ scores (p>0.05). Overall, a 60 min post lunch nap opportunity may be viable for improving static balance, although further work, involving larger samples and more complex motor activities, is warranted.
Women who wake from sleep during sexual assault commonly report confusion and disorientation. Confusion and disorientation, with impaired decision making after waking, are symptoms of ‘sleep inertia’, and part of the normal transition from sleep to full wakefulness which is maximal in the minutes after wakening and can be prolonged. In this study of 305 adult females (median age 26, range 18–68), who presented for a sexual assault forensic medical examination, 38 (12%) (median age 27, range 18–51) woke to find sexual acts already in progress. For 25 of these women (25/38 for 66%), an act of penile-vaginal penetration was already occurring when the woman woke. Of the 38 women (12%) who woke during the sexual assault, several had factors known to enhance the impairment of sleep inertia including forced arousal (38/38, 100%) and age under 25 (15/38, 39%). 17 (17/38 for 45%) of these women who woke had consumed varying amounts of alcohol prior to sleep and these 17 woke fully during the assault and then stayed awake. A further 16 women, (16/38 for 42%) woke during the sexual assault but returned to sleep during or after the assault, and all these 16 gave a history of intoxication by drugs or alcohol prior to sleep. Importantly 5, (5/38 for 13%) of the women who woke during the assault had consumed no intoxicating substances. A further 68 (23%) of the 305 women, (median age 26, range 18–58) had no memory on waking of the alleged sexual assault despite having other reasons to believe that a sexual assault had occurred. Forensic medical examiners can assist both the justice process, and patient care, by considering the possibility of sleep inertia among victims who report disorientation and slow or confused decision making on waking during a sexual assault.
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The dynamics of cerebral blood flow velocity during sleep were measured in the right and left middle cerebral artery of 12 and 10 healthy male volunteers, respectively. A computer-assisted pulsed (2-MHz) Doppler ultrasonography system was modified for continuous long-term and on-line recording of cerebral hemodynamics in combination with polysomnography. Mean flow velocity (MFV) decreased steadily during deepening nonrapid eye movement (NREM) sleep and increased suddenly during rapid eye movement sleep, corresponding to changes in brain function. However, spontaneous or provoked changes in sleep stage patterns as well as awakenings from NREM sleep were not regularly accompanied by corresponding changes in MFV. Differing values for MFV in subsequent sleep cycles could be shown for several sleep stages. Furthermore, MFV values in sleep stage II at the end of an NREM-sleep period were lower than in preceding slow-wave sleep. After application of short acoustic signals the electroencephalogram frequency rose, indicating an arousal, whereas MFV rapidly decreased for several seconds and then gradually returned to the prior level. These results imply an uncoupling between cerebral electrical activity and cerebral perfusion during sleep and support a dissociation in the activity of central regulatory mechanisms. In light of the proposal that cortical energy consumption can be accounted for by cerebral electrical activity, the concept that cerebral perfusion during sleep is regulated solely by the metabolic rate must be reconsidered.
The two-process model of sleep regulation postulates that a homeostatic and a circadian process underlie sleep regulation. The timing of sleep and waking is accounted for by the interaction of these two processes. The assumptions of two separate processes or of a single process resulting from their additive interaction are mathematically equivalent but conceptually different. Based on an additive interaction, subjective alertness ratings in a forced desynchrony protocol and subjective sleepiness ratings in a photoperiod experiment were simulated. The correspondence between empirical and simulated data supports the basic assumption of the model.
This study was aimed at evaluating the roost important relations between individual characteristics of shiftworkers and their subjective health complaints, obtained by cross-sectional and longitudinal procedures. A total of 604 shiftworkers and 185 young subjects who were going to enter shiftwork were examined by means of individual difference and subjective health questionnaires. The questionnaires were administered concurrently to the group of workers already involved in shiftwork. In the other group studied, the questionnaires were administered before they entered shiftwork, and subjective health was re-examined after the first and third year of work on shifts. More health complaints were reported by the group of older workers and those with longer shiftwork experience, with higher scores of neuroticism, hard-driving and competitiveness, speed and impatience, and rigidity of sleeping habits, and lower scores on relaxedness, efficiency and vigorousness. However, the correlations between these dimensions, when taken before entering shiftwork, and subjective health complaints obtained after a few years working on shifts were small or absent, indicating low validity of the individual difference measures for predicting subsequent health problems in shiftworkers.
Naval ratings were roused during the night and presented themselves, dressed, for testing in a nearby room with 4 minutes. During the next 11 minutes they were given tests of reaction time, calculation and muscular co- ordination and steadiness. In all three tests performance was well below the normal level achieved during the day. On different occasions the men were aroused at different times of night and this factor influenced which task was affected most. Reaction time, with its intermittent call for rapid response, was impaired most in the early part of the night; the adding and co-ordination, which demanded more continuous performance, were more affected later in the night.
Prolonged work scenarios with demands for sustained performance are increasingly common. Because sleep loss inevitably compromises functioning in such situations, napping has been proposed as a countermeasure. The optimal timing of the nap relative to its benefits for performance and mood is not known, however. To address this issue, 41 healthy adults were permitted a two-hour nap at one of five times during a 56-hour period of intermittent work, with no other sleep. Naps were placed 12 hours apart, near the circadian peak (P) or trough (T), and were preceded by 6(P), 18(T), 30(P), 42(T), or 54(P) hours of wakefulness. Work test bouts occurred every few hours and consisted of a variety of psychomotor and cognitive tasks as well as mood scales completed at the beginning, middle and end of each bout. A total of eight performance and 24 mood parameters were derived from the bouts and compared between groups at all test points prior to and following the naps. An estimate of the extent to which each nap condition differed from the control (P54) condition was derived by totalling the proportion of test points that yielded statistically significant results relative to the total number of tests conducted both before and after naps.Although all performance and most mood parameters displayed a circadian-modulated deterioration as the protocol progressed, a nap appeared to attentuate the extent of this change in all performance parameters but not in mood parameters. Overall, the timing of the nap across days and within the circadian cycle was irrelevant to its effect on performance, suggesting that it diminished the intrusion of sleepiness into behavioural functioning, even though subjects were phenomenally unaware of this benefit.