The effects of unintentional drowsiness on the velocity of eyelid movements during spontaneous blinks
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Physiological Measurement
PAPER • OPEN ACCESS
The effects of unintentional drowsiness on the velocity of eyelid
movements during spontaneous blinks
To cite this article: Murray Johns and Christopher Hocking 2021 Physiol. Meas. 42 014003
View the article online for updates and enhancements.
This content was downloaded from IP address 46.4.80.155 on 13/09/2021 at 17:00Physiol. Meas. 42 (2021) 014003 https://doi.org/10.1088/1361-6579/abd5c3
PAPER
The effects of unintentional drowsiness on the velocity of eyelid
OPEN ACCESS
movements during spontaneous blinks
RECEIVED
24 August 2020
Murray Johns1,2 and Christopher Hocking1
REVISED 1
16 December 2020
Optalert Australia Pty Ltd, 112 Balmain Street, Richmond, Melbourne, Victoria, 3121, Australia
2
School of Health Sciences, Swinburne University of Technology, Hawthorn, Melbourne, Victoria, 3122, Australia
ACCEPTED FOR PUBLICATION
22 December 2020 E-mail: mjohns@optalert.com
PUBLISHED
Keywords: blinks, unintentional drowsiness, blepharometry, amplitude–velocity ratios
4 February 2021
Original content from this
work may be used under Abstract
the terms of the Creative
Commons Attribution 4.0 Objective. Unintentional drowsiness, when we should be alert, as for example when driving a vehicle,
licence. can be very dangerous. In this investigation we examined the effects of unintentional drowsiness on
Any further distribution of
this work must maintain
the relative velocities of eyelid closing and reopening movements during spontaneous blinks.
attribution to the Approach. Twenty-four young adults volunteered to take part in this experiment, and 18 were finally
author(s) and the title of
the work, journal citation accepted. They performed a 15 min visual reaction-time test at the same time of day and under the
and DOI.
same environmental conditions with and without overnight sleep deprivation, one week apart. Their
eyelid movements during blinks were monitored by a system of infrared reflectance blepharometry
during each test. Main results. Very close relationships between the amplitude and maximum velocity
of eyelid closing and reopening movements were confirmed. Frequency histograms of amplitude–
velocity ratios (AVRs) for eyelid closing and reopening movements showed significant differences
between alert and drowsy conditions. With drowsiness, eyelid movements became slower and AVRs
increased for many but not all blinks. We also described a time-on-task effect on the relative velocities
of eyelid movements which was more apparent in the drowsy condition. Eyelid movements became
progressively slower during the first half of the test. This was presumably due to a short-lived alerting
effect of starting the test. Significance. The relative velocity of eyelid closing and reopening movements
during spontaneous blinks decreases with unintentional drowsiness but is sensitive to the brief alerting
stimulus of starting a reaction-time test.
Introduction
When we choose to fall asleep intentionally it is usually after we have selected a warm, quiet, and comfortable
place in which to lie down—a bed in a bedroom. When we are ready, we switch the lights off and settle down in
our preferred sleeping position. We close our eyelids voluntarily and consequently stop blinking. We usually
enter the state of drowsiness, the transitional state between wakefulness and sleep, within a few minutes. This is
not a dangerous state to be in under those circumstances. However, under other circumstances, drowsiness can
arise unintentionally at times when we should remain awake, as for example when driving a vehicle, a task that
requires almost continuous visual attention. Unintentional drowsiness under those circumstances is dangerous
and is a major cause of road crashes (Sagaspe et al 2010, Ftouni et al 2013). Thus, the difference between
intentional and unintentional drowsiness mainly relates to voluntary eyelid closure and the intention of falling
asleep in the former instance, while in the latter instance, the intention is to remain awake, typically to perform
some task. Blinks continue to occur during unintentional drowsiness although many of them change their
characteristics, especially the velocity of their eyelid closing and reopening movements, the subject of this
investigation.
Drowsiness is known to fluctuate and to show what has been called ‘state instability’, with variations over
periods of seconds as demonstrated by analysis of the EEG (Doran et al 2001). There are periods when the EEG
shows characteristics that are typical of wakefulness alternating with brief periods that are typical of the
© 2021 Institute of Physics and Engineering in MedicinePhysiol. Meas. 42 (2021) 014003 M Johns and C Hocking
Figure 1. Deep (left) and superficial (right) layers of eyelid muscles in the right eye.
beginning of sleep, or microsleeps, during which there is loss of awareness of the here-and-now. That loss
becomes continuous during sleep. The fluctuating nature of unintentional drowsiness can also be demonstrated
by pupillometry (Yoss et al 1970), or by monitoring psychomotor performance, either intermittently during a
reaction-time test such as the psychomotor vigilance test (PVT) (Dinges and Powell 1985, Dorrian et al 2005), or
during a continuous tracking task, with lapses in performance associated with ‘behavioural microsleeps’ (Peiris
et al 2006).
In recent years, considerable emphasis has been placed on the investigation of unintentional drowsiness by
measuring the characteristics of blinks (Cori et al 2019). Johns has coined the term blepharometry, which refers
specifically to study of the eyelids, their various functions, and their movements. The terms oculography and
oculometrics are less specific and refer mainly to the study of eye movements. For example, electrooculography
has long been used to monitor eye movements as part of polysomnography in sleep laboratories
(Chaudhary 2007). However, during investigations of unintentional drowsiness, it is more common for blinks to
be monitored by other methods, particularly by infrared reflectance blepharometry (Caffier et al 2003, Johns et al
2007). This has been used to monitor blinks for prolonged periods during laboratory experiments (Anderson
et al 2013, Wilkinson et al 2013) and while driving (Ftouni et al 2013, Soleimanloo et al 2019). Blinks can also be
monitored by video camera images of the eyes and eyelids (Espinosa et al 2018). Another method, using a
magnetic induction search coil attached to an upper eyelid while the head is fixed within a magnetic field, is very
accurate but is suitable only for brief recordings in laboratory experiments (Evinger et al 1991).
Blinks involve a coordinated sequence of eyelid closing and reopening movements, mainly due to the actions
of two muscles in each eye, levator palpebrae superioris (LPS) and orbiculoris occuli (OO) (Evinger 1995, Bour
et al 2000) (figure 1).
The nerve supply to OO is via a branch of the facial nerve, whereas a branch of the oculomotor nerve supplies
LPS. The ligaments which attach each end of LPS to the boney orbit are positioned such that, when LPS and OO
muscles are relaxed, the eyelids remain closed, as happens during sleep. During wakefulness, the eyelids are open
most of the time because of the tonic activation of LPS. Each blink begins with the phasic inhibition of the LPS
(Aramideh et al 1994, Evinger 1995). A few milliseconds later there is phasic activation of OO to close the eyelids.
This mainly involves activation of the ‘fast-twitch’ palpebral fibres of OO rather than its orbital fibres (Bour et al
2000). Each OO muscle acts in conjunction with forces due to the elastic properties of the ligamentous
attachments of LPS which assist in closing the eyelids. Thus, there are two forces acting together to close the
eyelids—the contraction of OO and the pull of elastic ligaments on LPS. In alert wakefulness the upper and
lower eyelids are in contact for only a few milliseconds before OO relaxes and LPS contracts phasically to reopen
the eyelids. Sometimes the reopening movement begins before the upper eyelid has made contact with the lower
lid. These partial blinks sometimes make up a considerable proportion of all blinks (Ousler et al 2014). The
contractile force of LPS in reopening the eyelids is partially counteracted by the downward pull on that muscle
due its ligamentous attachments (Evinger 1995). At the end of each blink, the upper tarsal muscle (Müller’s
muscle) helps LPS, in its tonic activation mode, to maintain the elevated position of the upper eyelid. Sensory
2Physiol. Meas. 42 (2021) 014003 M Johns and C Hocking
feedback about the position and velocity of each upper eyelid is derived from mechanoreceptors in LPS, and
especially in Müller’s muscle, which is embedded underneath LPS (Yuzuriha et al 2005). There is no such
sensory feedback from OO muscles.
The maximum velocity of each eyelid closing or reopening movement during a blink is controlled in relation
to the amplitude of that movement (Evinger et al 1991, Evinger 1995, Cruz et al 2011). The further the eyelids
move during a blink the higher their velocity, a relationship known as the ‘main sequence’. However, it is
difficult to measure the maximum velocity of eyelid movements calibrated in absolute terms of degrees or
millimeters per second, especially when repeated measurements are required over long periods. A system of
infrared reflectance blepharometry, and the amplitude/velocity ratios (AVRs) that it measures, were introduced
in 2003 (Johns 2003). The AVR for each eyelid movement was calculated as follows:
(amplitude of eyelid movement in mv) ´ (conversion factor)
A/ V = .
(maximum change in eyelid position in mv per unit time) ´ (conversion factor)
A conversion factor is necessary to convert each measurement from mv to mm or degrees per unit time.
Because the conversion factor is measured at the same time and under the same circumstances for the ordinate
and the abscissa, it cancels itself out of the ratio. The AVR for each eyelid movement can then be measured
without the need for calibration in absolute terms (Johns et al 2007). These AVRs have the dimension of time,
not of distance or velocity, so they measure the relative velocity of eyelid movements in relation to their
amplitude, not their absolute velocity (Johns and Tucker 2005, Johns et al 2007). In 2003 the velocity of eyelid
movements was calculated as the change in position in mv per 10 ms. That proved to be too sensitive to noise,
and in 2005 it was changed to mv per 50 ms (Johns and Tucker 2005). Such AVRs have been measured frequently
under different circumstances since then (Anderson et al 2013, Ftouni et al 2013, Wilkinson et al 2013,
Soleimanloo et al 2019).
The current investigation was part of ongoing studies to investigate the nature of unintentional drowsiness.
Our focus was on the relationship between the amplitude and maximum velocity of eyelid closing and reopening
movements during blinks, and the frequency distribution of AVRs, measured by infrared reflectance
blepharometry in healthy young adults when they were alert after a ‘normal’ night’s sleep, and when drowsy
because of overnight sleep deprivation. Each subject’s eyelid movements were monitored while they performed
a 15 min visual reaction-time test under alert and drowsy conditions.
Our particular objectives were as follows:
1. To confirm the relationships between the amplitude and maximum velocity (the ‘main sequence’) for eyelid
closing and reopening movements during blinks as measured by infrared reflectance blepharometry in a
large series of blinks.
2. To describe the frequency distributions of AVRs for eyelid closing and reopening movements, and how
each is affected by unintentional drowsiness.
3. To investigate short-term changes in AVRs across five consecutive 3 min segments of recordings.
Methods
The system of infrared reflectance blepharometry used to measure the characteristics of blinks (manufactured by
Optalert Australia Pty Ltd, Melbourne) and the visual reaction-time test have been described elsewhere (Johns
et al 2007). Twenty-four people volunteered to take part in this investigation. They came from among the
undergraduate and post-graduate students of Swinburne University of Technology, Melbourne. Initial
inclusion criteria were that they were not being treated for any physical or mental disorder at the time and were
ostensibly healthy, and had normal visual acuity without correction. They gave their informed written consent
to the protocol which was approved by an ethics committee of Swinburne University.
During the reaction-time test about 85 brief visual stimuli, each involving a change of shapes for 400
milliseconds on a computer screen, were presented at random intervals between 5 and 15 s. Subjects were asked
to respond to each stimulus as soon as possible by pushing a button held in their dominant hand. They were
familiarized with the protocol for several minutes during a ‘trial run’ before the recordings were made. Subjects
answered the Karolinska Sleepiness Scale (KSS) about their state of alertness/drowsiness just before each
recording session (Åkerstedt and Gillberg 1990). During recording sessions each subject sat alone at a desk in
front of a computer screen, without interruption, in an office with ceiling lights. One recording session for each
subject was during the morning after their usual night’s sleep, described in a sleep questionnaire. The other
3Physiol. Meas. 42 (2021) 014003 M Johns and C Hocking
session was during the morning after they stayed awake and missed that night’s sleep. The order of those sessions
was randomized. Subjectively, this was quite a boring task, especially after the first few minutes.
After the recordings were analyzed, only those subjects who fulfilled additional criteria were subsequently
included in the investigation. In the alert condition, they had to have responded to every stimulus in the
reaction-time test within two seconds, and to have scored less than six on the KSS just before the test. In the
drowsy condition, they had to have made several errors of omission in the reaction-time test (with no response
to the visual stimulus within two seconds) and to have scored at least six on the KSS. On that basis, six of the 24
subjects were excluded from further investigation. The remaining 18 participants (12 men) had a mean age of
21.9 years (range 19–30). All their blinks during 270 min of recording in each condition, and the results of the
reaction-time tests, were analyzed using proprietary software. The resolution of those measurements was two
milliseconds. The relationships between particular blinks and performance of the reaction-time test are not
reported here.
Statistical analysis
The ‘main sequence’ relationships between the amplitude and maximum velocity of eyelid closing and
reopening movements in alert and drowsy conditions were assessed by linear regression and Spearman’s R. The
frequency distributions of AVRs were tested for normality by chi2 tests, in which the degrees of freedom were
adjusted when cells with few data points were collapsed together. Differences between the AVRs in five
consecutive 3 min segments of the recordings were analyzed by Kruskal–Wallis ANOVA and Mann–Whitney
U-tests. Statistical significance was accepted at pPhysiol. Meas. 42 (2021) 014003 M Johns and C Hocking
Figure 2. Relationships between the amplitude (A) and maximum velocity of eyelid movements during blinks (V ): (a) eyelid closing
movements when alert, (b) eyelid closing movements when drowsy, (c) eyelid reopening movements when alert, (d) eyelid reopening
movements when drowsy. (A=amplitude in mv; V=max change in eyelid position (mv) per 50 ms.)
drowsiness in 15 of the 18 participants. The other three subjects already had a high blink rate (>25 blinks per
minute) in the alert condition.
So far, we have been comparing the AVRs of eyelid closing and reopening movements during spontaneous
blinks recorded during 15 min test sessions in alert and drowsy conditions, separated by several days. Because
drowsiness is known to be a rapidly fluctuating state, we also wanted to know if there were changes in AVRs
between consecutive 3 min segments of the recordings. Figure 4(a) shows the mean of AVRs (with 95 per cent
confidence intervals) for eyelid closing movements during each segment, plotted separately for alert and drowsy
conditions. There was a statistically significant difference between segments for eyelid closing AVRs which was
more obvious in the drowsy condition (Kruskal–Wallis H=63.7 (4, n=7380), PPhysiol. Meas. 42 (2021) 014003 M Johns and C Hocking
Figure 3. The frequency histograms for AVRs during blinks: (a) AVRs for eyelid closing movements when alert and drowsy, (b) AVRs
for eyelid reopening movements when alert and drowsy.
those from an earlier study with far fewer blinks, using the same methods (Johns and Tucker 2005). They are also
consistent with the results of investigations using a magnetic induction search coil (Evinger et al 1991, Aramideh
et al 1994) or a video camera (Cruz et al 2011, Espinosa et al 2018). Since the correlation coefficients we have
reported involved thousands of blinks, they indicate an extraordinary degree of control over eyelid movements
during blinks, especially during eyelid closing movements. That is possible because each neuromuscular unit of
OO comprises one motor neuron with axonal branches to about 10 muscle fibres. This provides greater control
of OO than is possible for most skeletal muscles, which have up to 100 muscle fibres per motor neuron (Bour
et al 2000).
Each AVR represents the slope of the relevant relationship between the amplitude and maximum velocity of
eyelid movements during blinks. We found that the frequency distributions of AVRs were significantly different
from normal, regardless of how we transformed them. This requires further investigation. We used
nonparametric methods to show that the distribution of closing AVRs was different from that of reopening
AVRs, and that both were increased by unintentional drowsiness. That is, relative velocities of eyelid movements
during blinks were reduced by drowsiness. We speculate that this was because fewer neuromuscular units of OO
and LPS muscles were recruited at the time. However, drowsiness increased the AVRs of some blinks but not
6Physiol. Meas. 42 (2021) 014003 M Johns and C Hocking
Figure 4. The mean and 95% confidence intervals of AVRs during each 3 min segment of the 15 min recordings: (a) eyelid closing
movements when alert and drowsy, (b) eyelid reopening movements when alert and drowsy.
others. As a result, drowsiness involved some AVRs that were typical of alert wakefulness. This is consistent with
drowsiness being a fluctuating state, showing ‘state instability’.
We have described a time-on-task effect on AVRs, which increased progressively during the first half of the
recordings and then remained relatively constant. This was especially so in the drowsy condition. We postulate
that this was caused by starting the test in anticipation of a challenge which acted as an alerting stimulus, a
stimulus that was dissipated over several minutes. This presumably had more effect in the drowsy state because
general levels of alertness were lower then, after sleep deprivation, when the ability to maintain alertness was
impaired. This effect may not have been present if starting the test did not act as an alerting stimulus. As a
practical example of the relevance of this finding, we suggest that it poses a potential problem for attempts to
determine who is (or was) too drowsy to drive a vehicle after having been stopped by road traffic authorities. The
possibility of facing legal consequences would presumably provide an alerting stimulus for most drivers,
especially when confronted with a testing procedure. A test of their alertness-drowsiness after the event may
need to last several minutes to allow sufficient time for the alerting effect of starting the test to decline, and for
drowsiness to become manifest. That makes the measurement of alertness-drowsiness at a particular time
different from the measurement of blood alcohol. Alertness-drowsiness can be influenced by the very fact of
being measured, whereas the blood alcohol concentration is not.
7Physiol. Meas. 42 (2021) 014003 M Johns and C Hocking
A limitation of this investigation was that it involved only healthy young adults. The effect of age on AVRs
remains to be investigated. We did not investigate the differences in AVRs between subjects which could be
expected because there was no requirement that they should all be equally drowsy after missing a night’s sleep.
We have incidentally confirmed that the blink rate increases after sleep deprivation (Caffier et al 2003), an
observation that is currently unexplained, and which requires further investigation.
Conclusions
On the basis of this investigation we conclude the following:
• The ‘main sequence’ relationships between the amplitude and maximum velocity of eyelid closing and
reopening movements during blinks, measured by infrared reflectance blepharometry, are consistent with
those measured by other methods.
• The distribution of AVRs for eyelid closing movements during blinks is different from that of eyelid reopening
movements. Both are affected by unintentional drowsiness.
• Unintentional drowsiness increases the AVRs for some, but not all blinks. This is consistent with the concept
of ‘state instability’.
• There are changes in AVRs during a 15 min psychomotor performance task that reflect a short-term time-on-
task effect, especially in the drowsy condition. This may have implications for the assessment of drowsiness in
drivers.
Acknowledgments
We acknowledge the assistance of Dr Andrew Tucker, Prof John Patterson, Dr Kate Crowley, Dr Natalie Michael
and Robert Chapman with collection of the data that formed the basis of this investigation.
Author contributions
MJ designed this experiment, analyzed the data, and was the main author of this manuscript. CH helped collect
the data, prepared the figures, and helped write the manuscript.
Conflict of interest
Dr Johns is a member of the Board of Directors and a shareholder of Optalert Australia Pty Ltd, the maker of
Optalert technology which was used here to monitor and analyze blinks. That technology is the subject of
various patents. Mr Hocking is an employee of the same company.
Funding of this research
No funds were received for this research or the preparation of this report.
ORCID iDs
Murray Johns https://orcid.org/0000-0001-7195-3173
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