Optometry & Vision Science:
Eye-Related Pain Induced by Visually Demanding Computer Work
Thorud, Hanne-Mari Schiøtz*; Helland, Magne†; Aarås, Arne‡; Kvikstad, Tor Martin†; Lindberg, Lars Göran*; Horgen, Gunnar*
Department of Optometry and Visual Science, Buskerud University College, Kongsberg, Norway (H-MST, MH, AA, TMK, GH), and Department of Biomedical Engineering, Linköping University, Linköping, Sweden (LGL).
Received November 1, 2011; accepted December 23, 2011.
Hanne-Mari Schiøtz Thorud Department of Optometry and Visual Science Buskerud University College Frogs vei 41 3611 Kongsberg, Norway e-mail: firstname.lastname@example.org
Purpose. Eye strain during visually demanding computer work may include glare and increased squinting. The latter may be related to elevated tension in the orbicularis oculi muscle and development of muscle pain. The aim of the study was to investigate the development of discomfort symptoms in relation to muscle activity and muscle blood flow in the orbicularis oculi muscle during computer work with visual strain.
Methods. A group of healthy young adults with normal vision was randomly selected. Eye-related symptoms were recorded during a 2-h working session on a laptop. The participants were exposed to visual stressors such as glare and small font. Muscle load and blood flow were measured by electromyography and photoplethysmography, respectively.
Results. During 2 h of visually demanding computer work, there was a significant increase in the following symptoms: eye-related pain and tiredness, blurred vision, itchiness, gritty eyes, photophobia, dry eyes, and tearing eyes. Muscle load in orbicularis oculi was significantly increased above baseline and stable at 1 to 1.5% maximal voluntary contraction during the working sessions. Orbicularis oculi muscle blood flow increased significantly during the first part of the working sessions before returning to baseline. There were significant positive correlations between eye-related tiredness and orbicularis oculi muscle load and eye-related pain and muscle blood flow. Subjects who developed eye-related pain showed elevated orbicularis oculi muscle blood flow during computer work, but no differences in muscle load, compared with subjects with minimal pain symptoms.
Conclusions. Eyestrain during visually demanding computer work is related to the orbicularis oculi muscle. Muscle pain development during demanding, low-force exercise is associated with increased muscle blood flow, possible secondary to different muscle activity pattern, and/or increased mental stress level in subjects experiencing pain compared with subjects with minimal pain.
Computer vision syndrome is a frequently occurring health problem among visual display unit users.1,2 The term “computer vision syndrome” was defined about 20 years ago3 due to the extensive increase in use of personal computers in private homes and offices and denotes eye-related problems associated with computer use. Computer work is demanding for the eyes in respect to both accommodation and convergence,4–7 and the visual stress increases with factors such as refractive disorders, convergence insufficiency, and screen and surface glare.8–10 Computer vision syndrome includes ocular symptoms such as dry eyes, tired eyes, and blurred vision and extraocular symptoms such as pain around the eyes and in the neck and shoulders.1,2,11 The causes of the ocular symptoms include attention-reduced blinking rate, uncorrected refractive error, and fatigue in the ocular system, like in the ciliary body which controls accommodation.2 Furthermore, sustained accommodation triggers trapezius muscle activity and possible development of myalgia.8,12 Extraocular symptoms such as pain around the eyes may originate from the orbicularis oculi muscles. The orbicularis oculi muscle is an elliptical sheet that surrounds the eye and extends from the lids to the brow, temple, and cheek. Orbicularis oculi consists of two main parts, the palpebral part which is confined to the lids and an outer orbital part. The palpebral part provides involuntary and voluntary blinking whereas the orbital part closes the lids firmly. During squinting, the orbital part contracts while the palpebral part of orbicularis oculi relaxes.13 Eyelid squinting is potentially benefiting by improving visual acuity in the presence of refractive error and by decreasing retinal illumination under glare conditions.14 The muscle fibers of orbicularis oculi muscle are among the smallest in diameter of all mammalian muscles, and a large majority of the fibers do not extend the full length of the muscle.15–18 The human orbicularis oculi constitutes of about 15% fatigue-resistant, slow-twitch, oxidative type 1 fibers, and the rest of the muscle consists of fatiguable, fast-twitch, glycolytic type 2 fibers.15,17,19 Earlier studies have shown increased discomfort and muscle activity in the orbital part of orbicularis oculi during near-work situations where the eyes were stressed by factors such as excessive lighting (glare) and use of small font.20–22 Peripheral mechanisms for development of muscle pain have been linked to tissue damage, ischemia, and inflammation.23 However, during low-force work, the mechanisms seem to be somewhat different, and previous studies have showed maintained or increased muscle blood flow in workers with chronic shoulder and neck pain compared with healthy controls.24–26 Furthermore, a significant association between muscle blood flow and pain development has been observed.26 A hypothesis regarding work situations with cognitive tasks and low-level muscle activity proposes that muscle pain originates from the blood vessel-nociceptor interactions of the connective tissue of the muscle.27 The aims of this study were to record eye-related symptoms during visually demanding computer work and correlate these symptoms to muscle load and muscle blood flow in orbicularis oculi. The following hypothesis was tested: Pain arising from the orbicularis oculi muscle during visually demanding computer work is correlated to changes in muscle blood flow. It is of importance to investigate the origin of eye-related pain during visually demanding computer work to increase the knowledge on how to optimize computer work conditions.
Subjects and Design
A group of healthy young students [14 females and 6 males, age 22 ± 4 years (mean ± SD), range 19–35 years] was randomly selected at the Department of Optometry and Visual Science at Buskerud University College, Norway. All subjects had visual acuity ≤20/20 in each eye and accommodation normal for the age. Nineteen subjects had full binocular vision with only small heterophorias. One subject had an alternating esotropia but with visual acuity of 20/20 in each eye. Informed consent was obtained according to protocol approved by the Regional Committees for Medical Research Ethics, Norway (ID 95199). The study followed the tenets of the Declaration of Helsinki. All subjects were experienced computer users. The testing was carried out at an optimized computer workplace. The laptop had a 15 in LCD screen, with 1024 × 768 pixels resolution and a refresh rate of 75 Hz (Hewlett-Packard Compaq EVO N1020v). Test subjects were placed in a stable office chair with forearms resting on the desktop. Sightline to the center of the screen was 30 to 40° below the horizontal line of the eyes and the screen was angled perpendicular to the line of sight. Viewing distance from the test subject to the computer screen was 40 to 60 cm. The work task consisted of a data dialogue situation.28,29 The work task was to find and “bold” as many e's as possible in an unknown English scientific text shown on the screen.30 The subjects were looking directly on the screen at all times and were only allowed to perform the marking and bolding task by using an ordinary mouse connected to the laptop. Productivity was calculated as the number of bold e's, and accuracy was given as the number of bold e's/number of e's in the text read. Times New Roman letters (8 points) were used, and a glare source was introduced. The glare source consisted of two large surface luminaries situated about 30° to the right of the fixation line. This was to simulate a visual display unit screen placement in an office with a window next to the screen. The two luminaries were made up of translucent acrylic diffusing fronts (1.25 m × 0.57 m) equipped each with six 60 W fluorescent tubes. The intensity of the luminance from the luminaries was 5500 to 6000 cd/m2 (measured across the screen). Such values are close to luminance levels from a window on a sunny day. The illumination level was approximately 300 lx on the work table. The light measurements were done with a Hagner Universal Photometer (Model S3, Sweden).
The testing included a 1 min rest, 60 min computer work, a 7.5 ± 1.5 min break (mean ± SD, n = 20), 1 min rest, 60 min computer work, a 1.4 ± 0.6 min break (mean ± SD, n = 20), and finally 1 min rest (Fig. 1). During all the rest recordings, the subjects were looking straight forward while relaxing in the office chair and the glare source was turned off. The break between the 2 h of computer work was introduced to make the testing resembling a standard computer work situation and also because 2 h of continuous work was exhausting for the subjects. In this break, to motivate the subjects to maximal performance in the second hour of work, they were allowed to move and were offered one cup of water, tea, or coffee and a small chocolate snack. In the short break before the last rest session, the subjects were only resting in the office chair.
Symptoms were recorded approximately 5 min before start of the first rest session and immediately after each 60 min work period (Fig. 1). The symptoms were recorded by using a questionnaire with nine questions with 100 mm Visual Analog Scales (VAS),31,32 and the subjects used about 1 min to complete the questionnaire. The questions were related to (1) tiredness in and around the eyes, (2) pain in and around the eyes, (3) itchiness in and around the eyes, (4) gritty eyes, (5) blurred vision, (6) degree of photophobia, (7) dry eyes, (8) tearing eyes, and (9) headache. The end points for the questions were as follows: left end point; “none” (0 mm) and right end point; “very much/intense” (100 mm). The subjects were told to localize the pain and tiredness symptoms to the forehead, around the eyes, and/or in the eyes.
Air temperature and humidity at the start of test procedures were 21 ± 1°C and 38 ± 8% (mean ± SD, n = 20) and 22 ± 1°C and 38 ± 7% (mean ± SD, n = 12) at the end of test procedures. Air temperature, but not humidity, increased significantly during testing. The tests were performed from September to December at Department of Optometry and Visual Science, Buskerud University College, Kongsberg, Norway.
The skin was cleaned with alcohol and lightly abraded before two electromyography (EMG) electrodes (Ambu, Denmark) were placed on the orbital part of orbicularis oculi muscle 15 mm beneath the lower lid on a vertical line intersecting the pupil when looking straight ahead (Fig. 2), and the distance between the two electrodes was about 5 mm. The reference electrode was placed on the temporal process of the zygomatic bone (Fig. 3). The diameter of the electrodes was 15 mm and interelectrode resistance was <5 kΩ. The EMG procedure was carried out by using a physiometer (Premed A/S, Oslo, Norway) connected to a computer.
The EMG signal was normalized by performing a calibration of the EMG response to force using a calibration platform with a force transducer (AMTI, Model number FD1-0500, Watertown, MA). A soft rubber end rested firmly on the skin located directly superficial to the orbicularis oculi (15 mm below the lower lid margin), and the lever arm was connected to the force transducer (Fig. 4). Isometric contraction of orbicularis oculi was performed by supporting the head with a forehead rest and chin rest and having the subject squint their eyes while keeping the mouth closed. The force of the contraction was measured on the contralateral side of the electrodes, assuming a simultaneous contraction of both sides. The subjects were informed of the importance of the use of equal force on both sides, and a training session was executed if necessary.
First, a measurement of maximal voluntary contraction (MVC) was carried out and the contraction was held for no longer than 2 s to avoid fatigue. MVC was assessed from the displayed maximum EMG root mean square (rms) (μV) and force (N) on a computer. An EMGrms/force relationship for the actual range of the work load below 30% MVC was established and calculated by linear regression. The results were considered satisfactory when the EMGrms showed a continuous increase. The EMGrms/force relationship obtained during the calibration procedure was used to convert the EMGrms recorded to % MVC. % MVC = [(EMGrms − m) * 100%/(a * Fmax)]. Fmax was the maximum force in N during MVC, a the slope of the linear regression line in μV/N, and m the minimum value of the EMGrms signal in μV. The physiometer used a preamplifier at electrode level with a gain of 216, input impedance >5 GΩ, and a common mode rejection ratio >100 dB. The signal was filtered by a band-pass filter from 20 to 800 Hz, amplified by a two-step variable gain amplifier (VGA), sampled at 1600 Hz, and digitized by a 12 bit analog to digital converter. The rms value of the signal was calculated in real time by a microcontroller over 0.1 s intervals taking into account the gain of the VGA. The VGA had a gain of 1 or 10, and the microcontroller selected the highest gain during low levels of the EMG signal and lowest gain during high levels. The results of the rms calculations were transmitted on an optically isolated serial port to a computer. The computer presented the signals graphically in real time and stored the signal for later analysis. During both calibration and recordings, the EMG signals were visually checked to ensure no excessive noise.33–35 The testing of each subject was performed >15 min after the last performed MVC to avoid influence of calibration on testing.
Photoplethysmography (PPG) is originally a non-invasive optical technique for measuring peripheral blood circulation like skin perfusion.36 The PPG technique for non-invasive monitoring from deeper vascular compartments has been further developed by using an appropriate combination of optical wavelengths and distance between the light source and photodetector.37–39 In this study, a special custom-designed optical probe (Department of Biomedical Engineering, Linköping University, Sweden) was developed and optimized for measurement of blood flow in the orbital part of the orbicularis oculi muscle (Figs. 2 and 5). Similar applications of PPG have been used to measure blood flow in muscles such as biceps brachii, tibialis anterior, trapezius, and supraspinatus.37,38,40–42 Near-infrared light (810 nm) from a light-emitting diode (LED) was directed toward the skin, absorbed, and scattered in the underlying tissue. Reflected light from the tissue was received by a photodetector placed adjacent to the LED. The LED at 810 nm was to ensure that the blood flow signal would be insensitive to variations in oxygen saturation. The probe was a prototype and the components were integrated into a black-colored silicone plate. The center-to-center distance between the LED and the photodetector was 11 mm (Fig. 5). With this combination of wavelength and distance, the depth of the measurements was 8 to 10 mm.37,38 The distance from the skin to the fascia of the orbital part of orbicularis oculi muscle is about 5 mm, based on studies of the anatomy of the orbicularis muscle and surrounding tissue in two human cadavers at the Institute of Basic Medical Sciences, Department of Anatomy, University of Oslo, Norway (Fig. 2), and literature research.43–45 Location of the PPG probe on the orbital part of orbicularis oculi muscle in the test subjects was 15 mm beneath the lower lid on a vertical line intersecting the pupil when looking straight ahead. The probe was attached to the skin with medical adhesive tape and covered with black-colored adhesive tape to avoid stray light from the glare source. There was about 10 min from attachment of the PPG probe to start of testing in each subject. The signals from the photodetector were processed in an amplifier and sent by Bluetooth to a PC (Fig. 3). We recently did a study with the same setup as in this study except that the subjects (n = 9) worked for 10 min with a computer work task (rewriting a text from one window on the screen to a second window on the same screen) that was less demanding for the orbicularis oculi compared with the work task in this study. There was no change in muscle blood flow during the 10 min computer work, indicating no effect on blood flow due to heating generated by the near-infrared LED38 and inhibited convection under the probe (unpublished results).
The levator labii superioris muscle originates posterior to the orbicularis oculi muscle and may contribute to the EMG and PPG signal from the orbicularis oculi muscle (Fig. 2). The test subjects were told to not talk or move unnecessarily during the test sessions to minimize both contribution from levator labii superioris and noise in the PPG signal which was sensitive to movement.37 Due to a possible contribution of the levator labii superioris muscle during EMG calibration, % MVC recorded during testing may be too low.
The 0.1 s intervals of sampled EMG were ranked to produce an amplitude distribution function.33 Static and median load were defined as amplitude distribution function levels 0.1 and 0.5, respectively, and were computed during the 1 min rest sessions and the first minute of every 10 min during the 60 min work sessions.33 A validity test was carried out before the study started, and it indicated reproducible results based on the mean values but with at relative large dispersion indicating the need for very accurate calibration (unpublished results). In the analysis, three subjects were excluded due to problems with calibration of the EMG signal, and one subject was excluded because the raw data were deleted by mistake.
The PPG signal can be divided into two separate parts: an AC and a DC signal. The AC signal correlates directly to blood flow and is synchronous with the heart rate. It reflects the arterial blood flow in the vascular bed39 in terms of both the pulsatile blood volume variations and the orientation of red blood cells.46,47 The DC signal is a baseline reflecting the total blood volume39 and varies slowly based on vasomotor activity, respiration, and thermoregulation.36 Other factors that may affect the amount of light received by the detector include movement of the vessel wall.46,47 Blood flow was recorded at a sampling frequency of 100 Hz using software developed at Department of Biomedical Engineering, Linköping University, Sweden. Blood flow was then analyzed in MatLab R2009b (The MathWorks, Inc., Natick, MA) by software developed at Department of Biomedical Engineering, Linköping University, Sweden, as the pulse-by-pulse amplitude of the AC component of the PPG signal. Mean amplitudes were computed during the 1 min rest sessions and the first minute of every 10 min during the 60 min work sessions. Muscle blood flow during the work sessions was related to mean muscle blood flow during the first 1 min rest recording. Two subjects were excluded from analysis due to excessive noise in the PPG signal.
Overall changes over time were tested with Friedman test. Wilcoxon signed rank test was used for comparing related variables. Spearman's rank correlation coefficient was used to examine correlations. Differences in EMG and blood flow between groups were tested by comparing means of area under curve with Mann-Whitney U test.48 If significance was indicated, differences at each time point were tested by Mann-Whitney U test. A statistical difference was accepted at p < 0.05 (two-tailed). Statistical analyses were performed in PASW Statistics 17.0 (SPSS Inc., Chicago, IL).
Eye-related symptoms were recorded before the start of the test session and immediately after each hour of computer work. After 1 h, there was a significant increase in tiredness and pain in and around the eyes, itchiness, gritty eyes, blurred vision, photophobia, dry eyes, and tearing eyes (Table 1). Except for tiredness and blurred vision, there was no further significant increase in symptoms in the second hour of work. Headache symptoms did not increase significantly during the 2 h of computer work (Table 1). A total of 78% of the subjects localized their tiredness symptoms and 68% of the subjects localized their pain symptoms. Regarding tiredness, 14% of the symptoms was localized to the forehead, 31% to “around the eyes,” and 55% to “in the eyes.” Regarding pain, 5% of the symptoms was localized to the forehead, 30% to “around the eyes,” and 65% to “in the eyes.”
Computer Work Performance
Productivity was calculated as the raw number of bolded e's, and productivity in the first and second hour was 748 ± 27 and 857 ± 34 (mean ± SEM, n = 20), respectively. Accuracy during the two 60 min computer work sessions was calculated as the number of bold e's/number of e's read. In the first hour, accuracy was 0.90 ± 0.02 compared with 0.92 ± 0.02 in the last hour (mean ± SEM, n = 20). There was a significant increase in both productivity and accuracy from the first to the second hour of computer work. However, there were no significant correlations between computer work performance and tiredness and pain symptoms.
Muscle activity was recorded during the 2 h of computer work, and there was significantly higher muscle activity during the computer work sessions compared with rest. Static load was stable at 1.1% MVC during computer work and about 40% elevated during work compared to rest. Median load increased by 60% in the first minute after start of computer work, before EMG measurements stabilized at 1.5% MVC and was about 30% elevated during work compared with rest (Fig. 6). When comparing muscle activity in the first and second hour of computer work, there was significantly lower muscle activity at start of the second hour compared with at start of the first hour (static load, p = 0.041; median load, p = 0.049), probably due to adaptation to the work task.49,50
In the first 40 min after the start of computer work, blood flow significantly increased 20% above baseline level, before returning to baseline in the last 20 min of the first hour. In the second hour of computer work, blood flow significantly increased to 18% above baseline level only in the first minute of work. There was a significant overall higher blood flow in the first hour compared with the second hour of computer work (Fig. 7).
Tiredness in Relation to Muscle Activity and Muscle Blood Flow
There were significant, positive correlations between tiredness and muscle activity in orbicularis oculi (Tables 2 and 3), but no significant correlations were observed between tiredness and muscle blood flow (not shown in table).
Pain in Relation to Muscle Blood Flow and Muscle Activity
There were significant, positive correlations between pain and blood flow in orbicularis oculi (Table 4), but no significant correlations were observed between pain and muscle activity (not shown in table).
The subject population was divided into a Pain group and a Minimal pain group based on the subjects' score on the VAS. The Pain group was defined as having an increase in the VAS score of >10 mm from baseline to after 1 h. The Minimal pain group was defined as having an increase in the VAS score ≤10 mm from baseline to after 1 h. In the literature, an increase from baseline in scores of around 10 mm VAS is regarded clinical important.51,52 In both the Minimal pain group and the Pain group, all the subjects had baseline symptoms <10 mm VAS.
Blood flow was overall significantly higher in the Pain group during the first hour of computer work compared with the Minimal pain group. There were no overall significant differences in muscle activity between the Pain and Minimal pain group. Muscle activity and blood flow showed significant overall time effects in both symptoms groups, except for blood flow in the Minimal pain group (Fig. 8).
Major significant findings are as follows: (1) Visually demanding computer work for 2 h induced several eye-related symptoms such as pain, tiredness, and blurred vision. (2) Orbicularis oculi muscle load was increased and stable during the 2 hours of computer work, whereas muscle blood flow was increased during the first 40 min of the first hour of computer work and the first minute of the second hour of work before returning to baseline. (3) There were positive correlations between tiredness symptoms and muscle load and pain symptoms and muscle blood flow in orbicularis oculi. (4) Subjects who developed eye-related pain showed increased orbicularis oculi blood flow during the first hour of computer work compared with subjects with minimal pain symptoms.
The visually demanding computer work lasted for 2 h and induced several symptoms associated with computer vision syndrome.1,2 Tiredness, pain, and blurred vision symptoms may have increased because glare and small font in addition to performing a high-precision task over time is demanding for convergence and accommodation.2,4,6,9,10 During the computer task, attention-reduced blinking led to increased ocular surface exposure which may have disrupted the precorneal tear film and ultimately resulted in dry and sore eyes.53–55 The origin of the pain symptoms “in the eye” may therefore be the cornea, the ciliary body, and extraocular muscles.2 Because of increased squinting to avoid the glare during the 2 h of computer work, the orbital part of the orbicularis oculi muscle contracted, and pain and tiredness symptoms “around the eyes” may therefore have its origin in the orbicularis oculi muscle.21 Tiredness and muscle load were positively correlated in the present study, in accordance with earlier studies.20–22
Only tiredness and blurred vision symptoms showed a further increase in intensity after 2 h compared with after 1 h of computer work. In line with this, in a recent study using a similar computer-based office work task [90 min continuous work, stationary computer with a slightly bigger screen (2 in), Arial font 11, no glare], eye strain symptoms increased steeply the first 30 min of computer work followed by a slow increase in the last 60 min.30 However, symptoms in the last hour could also be influenced by ingested caffeine and sugar in the break between the 2 h of computer work.56
Muscle activity in orbicularis oculi was low during computer work (mean values <2% MVC). Musculoskeletal disorders have been related to static muscle loads as low as 0.5 to 1% MVC and to sustained muscle load in general. Hence, focus in occupational ergonomics has been changed from maximum acceptable % MVC limits to time limits for prolonged sustained or repeated muscle contractions.57–61 The work performed by the orbital part of orbicularis oculi during the visually demanding computer work task may be characterized as sustained/repetitive low-force contractions as the test subjects more or less continuously squint to improve the visual acuity because of small font on the computer screen and to avoid excessive light from the glare source from entering the eye.20 Several studies have shown that repetitive low-force contractions induce metabolic changes in skeletal muscle linked to pain perception.25,62–64 In the trapezius (pars descendens), increased levels of interstitial muscle lactate, potassium, and glutamate were detected during a 20 min repetitive low-force arm exercise.25,62,63 Glutamate stimulates nociceptors by the NMDA receptor, and lactate lowers pH and increased H+ may stimulate several proton-sensitive receptors on the nociceptive nerve ending.23,65,66 Increased interstitial potassium may increase muscle pain sensation by depolarizing nerve endings and afferent fibers.23 It is possible that similar interstitial changes occurred in the orbicularis oculi muscle during the visually demanding work task. This could contribute to the increase in pain and tiredness symptoms during the 2 h of computer work.
Blood flow in orbicularis oculi was significantly increased during the first 40 min of the first hour of computer work and the first minute of the second hour of work before returning to baseline (Fig. 7). The return of blood flow to baseline before the end of computer work could not be explained by corresponding changes in muscle activity, which was significantly increased and stable during both hours of work (Fig. 6). In accordance, a study using a similar computer-based office work task also showed a significant fall in trapezius blood flux after 30 min of computer work without similar changes in muscle load.30 Increased microcirculation in relation to increase in muscle activity is well documented in the literature.25,64 The following reduced blood flow response in this study could be due to time-dependent changes in interstitial vasoactive metabolites in the muscle, such as potassium. Potassium induces vasodilation by hyperpolarization of smooth muscle cells involving activation of inward rectifier potassium channels and the Na+/K+ ATPase.67–69 Depolarization with KCl and blockade of Ca2+-activated K+ channels inhibit initial vasodilation in soleus muscle and gastrocnemius muscle in rats.70 This indicates that potassium is involved in the early phase of reactive hyperaemia in skeletal muscle.71,72 During a 60 min period of exercise (4 twitches/sec) in dog anterior calf muscles with blood flow held constant, venous potassium first increased before a decreasing trend after about 20 to 30 min of exercise.71 The same decreasing trend in venous potassium level after 30 min of exercise has been shown during low-intensity isometric knee extension (5% MVC) lasting for 60 min.73 Blood flow in the second hour of work in this study was lower compared with the first hour, despite sustained muscle activity. In the 5% MVC isometric knee extension study, subjects rested for 10 min after the 60 min exercise before another 10 min exercise at same intensity level. During the 10 min break, venous potassium levels fell below rest values before start of the first 60 min exercise session. In the following 10 min exercise, potassium concentration increased but did not reach the levels in the first exercise session.73 Consequently, changes in skeletal muscle blood flow during prolonged low-force exercise could be influenced by changes in interstitial metabolites, such as potassium. In future experiments, muscle oxygenation should be measured along with blood flow to further investigate how the changes in blood flow affects muscle metabolism.74
Heart rate and mean arterial pressure were not recorded in this study. Earlier studies using mental stress tasks, including demanding computer work, have reported significant increases in heart rate, mean arterial pressure, and muscle blood flow, probably due to an active coping response/central command.30,75–77 The changes in blood flow seen in this study may therefore be partly caused by a central neural response and not solely linked to changes in muscle activity.77 In addition, the observed changes in blood flow could be influenced by local heating.78 Increased heart rate due to mental stress may shunt blood to the skin to dissipate heat79 and consequently muscle blood flow could have been affected because of inhibited convection and increased temperature under the PPG probe.38 Temperature in the test room in this study only increased by 1°C during testing, and this would probably not influence muscle blood flow significantly.80
Orbicularis oculi muscle blood flow in the second hour of computer work could also be affected by drinks/snacks ingested during the break between the 2 h. Some of the subjects drank one cup of coffee/tea in the break. Caffeine influences the vasodilator effect of adenosine.72,81–83 However, previous human studies showing vasoconstrictor effects of caffeine on blood flow during exercise have used doses ≥6 mg/kg.82,84 A single cup of coffee provides a caffeine dose of <3 mg/kg.85
In this study, we showed a positive correlation between eye-related pain and blood flow in orbicularis oculi, together with no significant association between pain and muscle activity. In the first hour of computer work, subjects who developed pain symptoms had significantly higher muscle blood flow compared with subjects with minimal pain symptoms. A recent study on trapezius showed a significant association between development of pain over time and blood flow and no significant interactions between pain ratings and muscle load during a 90 min computer task.30 In a follow-up study, this reference group was compared to subjects with chronic shoulder and neck pain doing the same 90 min computer exercise, and during the task, trapezius blood flow increased to the same extent in both pain-afflicted subjects and controls despite higher pain sensitivity during exercise in the subjects with chronic shoulder and neck pain. The study showed significant positive correlations between pain ratings and trapezius blood flux and no significant associations between pain and EMG recordings in the active trapezius of subjects with chronic shoulder and neck pain.26 In patients with myalgia, there have been done a number of studies on muscle activity and metabolism related to development of pain. Recordings in trapezius during 8 h of repetitive manual work in women with chronic shoulder and neck pain showed higher pain intensity and consistently elevated blood flow compared with pain-free female colleagues but no differences in muscle load between the groups.24 In accordance, women with chronic work-related myalgia (MYA) doing 20 min of repetitive low-force exercise (moving short wooden sticks back and forth on a pegboard) exhibited significantly increased pain intensity compared with female controls (CON), but trapezius muscle blood flow during exercise increased to the same extent in both groups. However, the MYA group showed higher levels of interstitial potassium during exercise.25,63 In a similar study using the same protocol but with a heavier load (100 g sticks compared with 23 g sticks), pain ratings and relative muscle load was higher in the MYA group together with reduced blood flow during exercise compared with CON. Potassium levels did not differ between the groups.74 When comparing the “light” (23 g sticks) and “heavy” version (100 g sticks) of the repetitive exercise, the relative increase during exercise in potassium and blood flow was higher in the “light” compared with the “heavy” version in the MYA group.25,63,74 This may indicate differences in potassium levels depending on muscle activity pattern which could affect blood flow.25,63,74 Interestingly, in the present study at the time points during computer work were the association between pain and blood flow were strongest (Table 4), potassium levels have also been shown to be at the highest during low-force exercise.73
An additional or alternative explanation for the positive correlation between pain and blood flow may be that subjects experiencing pain have an increased mental stress level compared with subjects with minimal pain, inducing a greater sympathoinhibitory effect in the muscle and muscle vasodilation.77 Vasodilation has previously been directly linked to pain sensation in the blood vessel-nociceptor interaction hypothesis.27
In conclusion, eyestrain during visually demanding computer work is related to the orbicularis oculi muscle. Muscle pain development during demanding, low-force exercise may be related to increased muscle blood flow. Subjects who develop pain may have a different muscle activity pattern, producing metabolites linked to both increased pain sensation and vasodilation, and/or increased mental stress level producing vasodilation and pain compared with subjects with minimal pain development.23,72,73,77 The mechanisms behind this pain development may be different compared to during contractions at higher muscle loads where microcirculation is attenuated.86,87
Hanne-Mari Schiøtz Thorud
Department of Optometry and Visual Science
Buskerud University College
Frogs vei 41
3611 Kongsberg, Norway
We thank the students at Department of Optometry and Visual Science, Buskerud University College, for participating as test subjects in the study. We also thank the students Sina Delavari, Steffen Amlie Hole, Nina Haarslev Johannessen, Anders Olsrud, Anne Therese Putkowski, and Joakim Sand for contributing with Figure 5. A special thanks to Professor Eric Rinvik at Institute of Basic Medical Sciences, Department of Anatomy, University of Oslo, for organizing anatomical studies of the orbicularis oculi muscle.
This work was supported by grant number 176541/V10 from The Norwegian Research Council.
This paper was presented as a poster at the 40th European Muscle Conference in Berlin, Germany, in September 2011.
1. Hayes JR, Sheedy JE, Stelmack JA, Heaney CA. Computer use, symptoms, and quality of life. Optom Vis Sci 2007;84:738–44.
2. Blehm C, Vishnu S, Khattak A, Mitra S, Yee RW. Computer vision syndrome: a review. Surv Ophthalmol 2005;50:253–62.
3. Von Stroh R. Computer vision syndrome. Occup Health Saf 1993;62:62–6.
4. Best PS, Littleton MH, Gramopadhye AK, Tyrrell RA. Relations between individual differences in oculomotor resting states and visual inspection performance. Ergonomics 1996;39:35–40.
5. Culhane HM, Winn B. Dynamic accommodation and myopia. Invest Ophthalmol Vis Sci 1999;40:1968–74.
6. Gratton I, Piccoli B, Zaniboni A, Meroni M, Grieco A. Change in visual function and viewing distance during work with VDTs. Ergonomics 1990;33:1433–41.
7. Gur S, Ron S, Heicklen-Klein A. Objective evaluation of visual fatigue in VDU workers. Occup Med (Lond) 1994;44:201–4.
8. Aaras A, Horgen G, Bjorset HH, Ro O, Walsoe H. Musculoskeletal, visual and psychosocial stress in VDU operators before and after multidisciplinary ergonomic interventions. A 6 years prospective study—part II. Appl Ergon 2001;32:559–71.
9. Hedge A, Sims WR Jr., Becker FD. Effects of lensed-indirect and parabolic lighting on the satisfaction, visual health, and productivity of office workers. Ergonomics 1995;38:260–80.
10. Piccoli B, Braga M, Zambelli PL, Bergamaschi A. Viewing distance variation and related ophthalmological changes in office activities with and without VDUs. Ergonomics 1996;39:719–28.
11. Anshel JR. Visual ergonomics in the workplace. AAOHN J 2007;55:414–20; quiz 421–2.
12. Richter HO, Banziger T, Forsman M. Eye-lens accommodation load and static trapezius muscle activity. Eur J Appl Physiol 2010;111:29–36.
13. Bron AJ, Tripathi RC, Tripathi BJ. Wolff's Anatomy of the Eye and Orbit, 8th ed. London: Chapman & Hall Medical; 1997.
14. Sheedy JE, Truong SD, Hayes JR. What are the visual benefits of eyelid squinting? Optom Vis Sci 2003;80:740–4.
15. Happak W, Burggasser G, Gruber H. Histochemical characteristics of human mimic muscles. J Neurol Sci 1988;83:25–35.
16. Polgar J, Johnson MA, Weightman D, Appleton D. Data on fibre size in thirty-six human muscles. An autopsy study. J Neurol Sci 1973;19:307–18.
17. Goodmurphy CW, Ovalle WK. Morphological study of two human facial muscles: orbicularis oculi and corrugator supercilii. Clin Anat 1999;12:1–11.
18. Wirtschafter JD, Lander T, Baker RH, Stevanovic M, Kirsch J, McLoon LK. Heterogeneous length and in-series arrangement of orbicularis oculi muscle: individual myofibers do not extend the length of the eyelid. Trans Am Ophthalmol Soc 1994;92:71–88; discussion 88–90.
19. Cheng NC, Liao SL, Wang IJ, Lin IC, Tang YB. Fiber type and myosin heavy chain compositions of adult pretarsal orbicularis oculi muscle. J Mol Histol 2007;38:177–82.
20. Gowrisankaran S, Sheedy JE, Hayes JR. Eyelid squint response to asthenopia-inducing conditions. Optom Vis Sci 2007;84:611–9.
21. Berman SM, Bullimore MA, Jacobs RJ, Bailey IL, Gandhi N. An objective measure of discomfort glare. J Illum Eng Soc 1994;23:40–8.
22. Nahar NK, Sheedy JE, Hayes J, Tai YC. Objective measurements of lower-level visual stress. Optom Vis Sci 2007;84:620–9.
23. Mense S. Algesic agents exciting muscle nociceptors. Exp Brain Res 2009;196:89–100.
24. Larsson B, Rosendal L, Kristiansen J, Sjogaard G, Sogaard K, Ghafouri B, Abdiu A, Kjaer M, Gerdle B. Responses of algesic and metabolic substances to 8 h of repetitive manual work in myalgic human trapezius muscle. Pain 2008;140:479–90.
25. Rosendal L, Larsson B, Kristiansen J, Peolsson M, Sogaard K, Kjaer M, Sorensen J, Gerdle B. Increase in muscle nociceptive substances and anaerobic metabolism in patients with trapezius myalgia: microdialysis in rest and during exercise. Pain 2004;112:324–34.
26. Strom V, Roe C, Knardahl S. Work-induced pain, trapezius blood flux, and muscle activity in workers with chronic shoulder and neck pain. Pain 2009;144:147–55.
27. Knardahl S. Psychophysiological mechanisms of pain in computer work: the blood vessel-nociceptor interaction hypothesis. Work Stress 2002;16:179–89.
28. Westlander G, Magnusson B. Swedish women and new technology. Women Health 1988;13:95–116.
29. Westlander G. Use and non use of VDTs—organization of terminal work: research findings from Swedish cross-site studies in the field of automation. Int J Human Comp Interaction 1990;2:137–51.
30. Strom V, Knardahl S, Stanghelle JK, Roe C. Pain induced by a single simulated office-work session: time course and association with muscle blood flux and muscle activity. Eur J Pain 2009;13:843–52.
31. du Toit R, Pritchard N, Heffernan S, Simpson T, Fonn D. A comparison of three different scales for rating contact lens handling. Optom Vis Sci 2002;79:313–20.
32. Kildeso J, Wyon D, Skov T, Schneider T. Visual analogue scales for detecting changes in symptoms of the sick building syndrome in an intervention study. Scand J Work Environ Health 1999;25:361–7.
33. Jonsson B. Measurement and evaluation of local muscular strain in the shoulder during constrained work. J Hum Ergol (Tokyo) 1982;11:73–88.
34. Veiersted KB. The reproducibility of test contractions for calibration of electromyographic measurements. Eur J Appl Physiol Occup Physiol 1991;62:91–8.
35. Aaras A, Veierod MB, Larsen S, Ortengren R, Ro O. Reproducibility and stability of normalized EMG measurements on musculus trapezius. Ergonomics 1996;39:171–85.
36. Allen J. Photoplethysmography and its application in clinical physiological measurement. Physiol Meas 2007;28:R1–39.
37. Hagblad J, Lindberg LG, Kaisdotter Andersson A, Bergstrand S, Lindgren M, Ek AC, Folke M, Linden M. A technique based on laser Doppler flowmetry and photoplethysmography for simultaneously monitoring blood flow at different tissue depths. Med Biol Eng Comput 2010;48:415–22.
38. Sandberg M, Zhang Q, Styf J, Gerdle B, Lindberg LG. Non-invasive monitoring of muscle blood perfusion by photoplethysmography: evaluation of a new application. Acta Physiol Scand 2005;183:335–43.
39. Lindberg LG, Oberg PA. Photoplethysmography. Part 2. Influence of light source wavelength. Med Biol Eng Comput 1991;29:48–54.
40. Sandberg M, Larsson B, Lindberg LG, Gerdle B. Different patterns of blood flow response in the trapezius muscle following needle stimulation (acupuncture) between healthy subjects and patients with fibromyalgia and work-related trapezius myalgia. Eur J Pain 2005;9:497–510.
41. Sandberg ML, Sandberg MK, Dahl J. Blood flow changes in the trapezius muscle and overlying skin following transcutaneous electrical nerve stimulation. Phys Ther 2007;87:1047–55.
42. Zhang Q, Lindberg LG, Kadefors R, Styf J. A non-invasive measure of changes in blood flow in the human anterior tibial muscle. Eur J Appl Physiol 2001;84:448–52.
43. Demirci H, Nelson CC. Ultrasound biomicroscopy of the upper eyelid structures in normal eyelids. Ophthal Plast Reconstr Surg 2007;23:122–5.
44. Hwang SH, Hwang K, Jin S, Kim DJ. Location and nature of retro-orbicularis oculus fat and suborbicularis oculi fat. J Craniofac Surg 2007;18:387–90.
45. Iwanami M, Tsurukiri K. Histological comparison between young and aged specimens of the Oriental lower eyelid using sagittal serial sections. Plast Reconstr Surg 2007;119:2061–71.
46. Lindberg LG, Oberg PA. Optical properties of blood in motion. Opt Eng 1993;32:253–7.
47. Naslund J, Pettersson J, Lundeberg T, Linnarsson D, Lindberg LG. Non-invasive continuous estimation of blood flow changes in human patellar bone. Med Biol Eng Comput 2006;44:501–9.
48. Matthews JN, Altman DG, Campbell MJ, Royston P. Analysis of serial measurements in medical research. BMJ 1990;300:230–5.
49. LaStayo P, Pifer J, Pierotti D, Lindstedt S. Electromyographic adaptations elicited by submaximal exercise in those naive to and in those adapted to eccentric exercise: a descriptive report. J Strength Cond Res 2008;22:833–8.
50. Finsen L, Sogaard K, Jensen C, Borg V, Christensen H. Muscle activity and cardiovascular response during computer-mouse work with and without memory demands. Ergonomics 2001;44:1312–29.
51. Ostelo RW, Deyo RA, Stratford P, Waddell G, Croft P, Von Korff M, Bouter LM, de Vet HC. Interpreting change scores for pain and functional status in low back pain: towards international consensus regarding minimal important change. Spine (Phila Pa 1976) 2008;33:90–4.
52. Zisapel N, Nir T. Determination of the minimal clinically significant difference on a patient visual analog sleep quality scale. J Sleep Res 2003;12:291–8.
53. Wolkoff P, Nojgaard JK, Troiano P, Piccoli B. Eye complaints in the office environment: precorneal tear film integrity influenced by eye blinking efficiency. Occup Environ Med 2005;62:4–12.
54. Patel S, Henderson R, Bradley L, Galloway B, Hunter L. Effect of visual display unit use on blink rate and tear stability. Optom Vis Sci 1991;68:888–92.
55. Tsubota K, Nakamori K. Dry eyes and video display terminals. N Engl J Med 1993;328:584.
56. Conger SA, Warren GL, Hardy MA, Millard-Stafford ML. Does caffeine added to carbohydrate provide additional ergogenic benefit for endurance? Int J Sport Nutr Exerc Metab 2011;21:71–84.
57. de Looze M, Bosch T, van Dieen J. Manifestations of shoulder fatigue in prolonged activities involving low-force contractions. Ergonomics 2009;52:428–37.
58. Veiersted KB, Westgaard RH, Andersen P. Pattern of muscle activity during stereotyped work and its relation to muscle pain. Int Arch Occup Environ Health 1990;62:31–41.
59. Sjogaard G, Kiens B, Jorgensen K, Saltin B. Intramuscular pressure, EMG and blood flow during low-level prolonged static contraction in man. Acta Physiol Scand 1986;128:475–84.
60. Sjøgaard G, Jensen BR. Low-level static exertions. In: Karwowski W, Marras WS, eds. The Occupational Ergonomics Handbook, Fundamentals and Assessment Tools for Occupational Ergonomics, 2nd ed. Boca Raton, FL: CRC/Taylor & Francis; 2006:1–13.
61. Jensen C, Nilsen K, Hansen K, Westgaard RH. Trapezius muscle load as a risk indicator for occupational shoulder-neck complaints. Int Arch Occup Environ Health 1993;64:415–23.
62. Rosendal L, Blangsted AK, Kristiansen J, Sogaard K, Langberg H, Sjogaard G, Kjaer M. Interstitial muscle lactate, pyruvate and potassium dynamics in the trapezius muscle during repetitive low-force arm movements, measured with microdialysis. Acta Physiol Scand 2004;182:379–88.
63. Rosendal L, Kristiansen J, Gerdle B, Sogaard K, Peolsson M, Kjaer M, Sorensen J, Larsson B. Increased levels of interstitial potassium but normal levels of muscle IL-6 and LDH in patients with trapezius myalgia. Pain 2005;119:201–9.
64. Sjogaard G, Savard G, Juel C. Muscle blood flow during isometric activity and its relation to muscle fatigue. Eur J Appl Physiol Occup Physiol 1988;57:327–35.
65. Mense S. The pathogenesis of muscle pain. Curr Pain Headache Rep 2003;7:419–25.
66. Mense S. Peripheral mechanisms of muscle pain: reponse behavior of muscle nociceptors and factors eliciting local muscle pain. In: Mense S, Gerwin RD, eds. Muscle Pain Understanding the Mechanisms. Berlin: Springer-Verlag; 2010:49–103.
67. Knot HJ, Zimmermann PA, Nelson MT. Extracellular K(+)-induced hyperpolarizations and dilatations of rat coronary and cerebral arteries involve inward rectifier K(+) channels. J Physiol 1996;492(Pt 2):419–30.
68. Zaritsky JJ, Eckman DM, Wellman GC, Nelson MT, Schwarz TL. Targeted disruption of Kir2.1 and Kir2.2 genes reveals the essential role of the inwardly rectifying K(+) current in K(+)-mediated vasodilation. Circ Res 2000;87:160–6.
69. Burns WR, Cohen KD, Jackson WF. K+-induced dilation of hamster cremasteric arterioles involves both the Na+/K+-ATPase and inward-rectifier K+ channels. Microcirculation 2004;11:279–93.
70. Shipley RD, Kim SJ, Muller-Delp JM. Time course of flow-induced vasodilation in skeletal muscle: contributions of dilator and constrictor mechanisms. Am J Physiol Heart Circ Physiol 2005;288:H1499–507.
71. Sparks HV. Mechanism of vasodilation during and after ischemic exercise. Fed Proc 1980;39:1487–90.
72. Sarelius I, Pohl U. Control of muscle blood flow during exercise: local factors and integrative mechanisms. Acta Physiol (Oxf) 2010;199:349–65.
73. Sjogaard G. Muscle energy metabolism and electrolyte shifts during low-level prolonged static contraction in man. Acta Physiol Scand 1988;134:181–7.
74. Sjogaard G, Rosendal L, Kristiansen J, Blangsted AK, Skotte J, Larsson B, Gerdle B, Saltin B, Sogaard K. Muscle oxygenation and glycolysis in females with trapezius myalgia during stress and repetitive work using microdialysis and NIRS. Eur J Appl Physiol 2010;108:657–69.
75. Halliwill JR, Lawler LA, Eickhoff TJ, Dietz NM, Nauss LA, Joyner MJ. Forearm sympathetic withdrawal and vasodilatation during mental stress in humans. J Physiol 1997;504(Pt 1):211–20.
76. Larsson SE, Larsson R, Zhang Q, Cai H, Oberg PA. Effects of psychophysiological stress on trapezius muscles blood flow and electromyography during static load. Eur J Appl Physiol Occup Physiol 1995;71:493–8.
77. Wallin BG, Charkoudian N. Sympathetic neural control of integrated cardiovascular function: insights from measurement of human sympathetic nerve activity. Muscle Nerve 2007;36:595–614.
78. Pearson J, Low DA, Stohr E, Kalsi K, Ali L, Barker H, Gonzalez-Alonso J. Hemodynamic responses to heat stress in the resting and exercising human leg: insight into the effect of temperature on skeletal muscle blood flow. Am J Physiol Regul Integr Comp Physiol 2011;300:R663–73.
79. Fechir M, Schlereth T, Kritzmann S, Balon S, Pfeifer N, Geber C, Breimhorst M, Eberle T, Gamer M, Birklein F. Stress and thermoregulation: different sympathetic responses and different effects on experimental pain. Eur J Pain 2009;13:935–41.
80. Heinonen I, Brothers RM, Kemppainen J, Knuuti J, Kalliokoski KK, Crandall CG. Local heating, but not indirect whole body heating, increases human skeletal muscle blood flow. J Appl Physiol 2011;111:818–24.
81. Hellsten Y, Maclean D, Radegran G, Saltin B, Bangsbo J. Adenosine concentrations in the interstitium of resting and contracting human skeletal muscle. Circulation 1998;98:6–8.
82. Radegran G, Calbet JA. Role of adenosine in exercise-induced human skeletal muscle vasodilatation. Acta Physiol Scand 2001;171:177–85.
83. Riksen NP, Smits P, Rongen GA. The cardiovascular effects of methylxanthines. Handb Exp Pharmacol 2011:413–37.
84. Daniels JW, Mole PA, Shaffrath JD, Stebbins CL. Effects of caffeine on blood pressure, heart rate, and forearm blood flow during dynamic leg exercise. J Appl Physiol 1998;85:154–9.
85. Fredholm BB, Battig K, Holmen J, Nehlig A, Zvartau EE. Actions of caffeine in the brain with special reference to factors that contribute to its widespread use. Pharmacol Rev 1999;51:83–133.
86. Larsson R, Oberg PA, Larsson SE. Changes of trapezius muscle blood flow and electromyography in chronic neck pain due to trapezius myalgia. Pain 1999;79:45–50.
87. Ashina M, Stallknecht B, Bendtsen L, Pedersen JF, Galbo H, Dalgaard P, Olesen J. In vivo evidence of altered skeletal muscle blood flow in chronic tension-type headache. Brain 2002;125:320–6.
computer vision syndrome; eyestrain; orbicularis oculi muscle; electromyography; photoplethysmography; muscle blood flow; muscle activity; muscle pain; mental stress
This article has been cited 1 time(s).
Journal of Physical Therapy Science
Risk Factors Affecting Subjective Symptoms of Fatigue Due to the Environment of High School Students' Computer Workstation in the Republic of Korea
Journal of Physical Therapy Science, 25(4):
© 2012 American Academy of Optometry
Highlight selected keywords in the article text.