1. 1
Point & Click (by Dwelling and Blinking) Performance with
Eye Tracking
Matthew Conte
York University
Toronto, Ontario, Canada M3J 1P3
mattconte@rogers.com
I. Scott Mackenzie
York University
Toronto, Ontario, Canada M3J 1P3
mack@cse.yorku.ca
ABSTRACT
An eye tracker can be used to point and click with a
cursor like a mouse. The ISO 9241-9 standard is used to
evaluate performance of non keyboard input devices such
as a mouse. This paper evaluates two clicking techniques
for a portable, ubiquitous eye tracker and compares them
with a mouse. The evaluation used throughput (bits/s),
error rate (%) and mean time per trial (ms) as
measurements of performance in a two-dimensional
point-select task. The “click by dwelling” technique
required participants to look at an on-screen target and
dwell on it for 500ms to select it. The “click by blinking”
technique required participants to look at an on-screen
target and select it by holding a blink for 500ms to select
it. The mouse had a throughput of 4.79 bits/s. Click by
dwelling performed better overall with a throughput of
1.79 bits/s. Click by blinking had a throughput of 1.16
bits/s and a lower error rate with more time taken to
complete a task than click by dwelling. Participants
preferred to click by blinking because it doesn’t produce
involuntary clicks.
Keywords
Eye tracking, pointing devices, ISO 9241, Fitts’ law,
performance evaluation
INTRODUCTION
The most popularized pointing device today is the mouse.
The user selects an object by moving the mouse on a
surface which moves the on-screen cursor and then selects
target by pressing a button. When using eye tracking for
pointing and clicking, the user locates the target by
looking at it: selection can be done with no button
pressing [1]. This solution is more straightforward than
using a mouse, more suitable for handicapped users who
are incapable of using a mouse and doesn't succumb to
cursor clutching like a mouse does where the user has to
lift up the mouse to disable tracking and repositioning it
to a more convenient, “movable” location. Damaging
health effects of using a mouse also don't apply when
using an eye tracker such as carpal tunnel syndrome.
Clicking without button pressing with an eye tracker can
be done by looking/dwelling at the selected target or by
blinking while looking at the target.
Evaluating Point & Click Performance
The ISO standard for measuring performance for non-
keyboard devices (mouse, trackball, touchpad, etc.) is ISO
9241 Ergonomic requirements for office work with visual
display terminals - Part 9: Requirements for non-
keyboard input devices [2]. This standard provides
guidelines and testing procedures for evaluating non-
keyboard pointing devices. This experiment uses task # 2
from this standard which evaluates computer pointing
devices with two dimensional target selections.
Performance is measured by throughput. Calculating
throughput in bits per second (bits/s) is based on Fitts’
law [3], and requires an Index of Difficulty (ID) and
Movement Time (MT). Movement Time is the mean time
taken to complete a series of target point and select tasks.
Index of Difficulty is calculated with the Shannon
formulation as follows:
ID = log2(D / W + 1)
Where D is the distance between two consecutive targets
and W is the width of each target. However, the standard
suggests using an Effective Target Width (We) and
Effective target distance (De) instead, because it captures
spatial variability over a series of trails, so it better
reflects how users performed, instead of what was shown
to them [4].
We is calculated by projecting selection points on the task
axis (straight line from the source to destination target),
then computing the distance along the projected x-axis,
Delta x, is calculated from the actual point selected to the
center of the destination target. A positive delta x is
considered over-shooting, a negative delta x is considered
under-shooting. We for a series of trials is 4.133 times the
Standard Deviation of x (SD):
We = 4.133 × SD
De is the distance of the actual path traversed along the
task axis with the cursor. The new Index of Difficulty
(IDe) is now expressed as:
IDe = log2(De / We + 1).
Giving the throughput (TP) calculation as follows:
TP = IDe / MT
Prior Evaluations
There is only one other experiment that has evaluated
point and select performance using an eye tracker with

2. ISO 9241 Task #2 [5]. This experiment had the user use
eye tracking for pointing and clicking by looking at the
target and clicking by dwelling at it for a fixed period of
time (500 ms and 750 ms). The experiment also included
clicking with a spacebar while using an eye tracker and a
mouse as a baseline condition. The cursor was hidden to
reduce visual distractions for the eye tracker evaluation.
This experiment concluded that overall performance for
eye tracking was optimal and most preferred using the
spacebar to click with a throughput of 3.78 bits/s, just
under that of a mouse with 4.68 bits/sec throughput [5].
The performance of 500ms dwell time was also better
than the longer dwell time of 750ms at 3.06 bits/s and
2.30 bits/s respectively.
Click by Blinking
One of the most common slips that occurs with clicking
by dwelling as evident in this prior experiment is the
effect of jittering away from the target when attempting to
gaze at it resulting in either a time-out error where
selecting a target takes too long or a selection error where
the user fails to click the target.
One possible way this slip can be resolved is to blink
when the user gets the cursor on the target to prevent the
cursor from jittering away from the target. Click by
blinking is similar to clicking with a separate key which
had greater performance in the first experiment but
without actually using a separate key as people with
physical disabilities may not be able to do. After a series
of practice trials, 500 ms is found to be long enough for
not producing involuntary click events from casual
blinking and is ideal for comparing since 500ms is the
optimal click by dwelling time in the first experiment.
By using ISO 9241 Task # 2 for evaluating non keyboard
input devices, this paper will evaluate performance of eye
tracking for point and select tasks by using click by
dwelling and blinking.
METHOD
Participants
Twelve volunteer participants (9 male, 3 female) were
recruited from a local university campus. All participants
had no experience in using an eye tracker but have
experience in using a mouse. All participants had normal
vision except for one who wore glasses and another who
wore contact lenses during the experiment.
Apparatus
The eye tracker used is the Eyetech Digital Systems TM3
eye tracker (Figure 1a) that used Quick Glance version
5.0.1 software. Unlike the device used in the first ISO-
conforming eye tracker experiment, this device is more
portable, ubiquitous and less cumbersome to setup. The
device uses infrared emitters on its sides to illuminate the
eyes and its infrared camera to provide reference points
for the tracker. The eye tracker is initially setup by asking
for the lens size and working distance, which has a default
setting of 16mm and 50-60cm respectively. The manual
indicates that it works for users with glasses or contact
lenses. The tracker confirms that it can detect your eyes
through cross hairs displayed on the user’s eyes (Figure
1b).
Calibration is done using 16 circles on the screen where
the user uses his/her eyes to look at the center of each
target that appears on screen for 1.5 seconds until the next
target appears. The targets appear from left to right, top to
bottom.
The calibration returns a numerical score for each eye
where a lower score means less estimated deviation from
where each eye is looking at and where the cursor is
located. The software insists that an optimal score is from
1 to 10.
Through a large number of practice trials, the most
feasibly attainable score averaged at 4.0 per eye. This
score on average took approximately 6 minutes after 10
extra attempts that never improved the score any further.
Figure 1a: Eyetech DS TM3 Eye Tracker
Figure 1b: Quick Glance software displaying cross
hairs on user’s eyes for reference points

3. Click by dwelling has a default dwelling area of 20mm
where the user had to dwell within that area size for a
specified amount of time before a click event occurs. The
dwell area used in this experiment is the smallest settable
area of 5mm which is close to the smallest target
participants had to select. This area was found to produce
less errors and greater throughput than larger dwelling
areas as a result of many practice trials.
An audible click feedback is heard at the same time of a
dwell or blink click event with a click delay of 0.2
seconds where the click event occurs 0.2 seconds after the
sound is played.
Cursor movement is set to a smoothing factor of 10 as set
in the software.
The camera has a frame rate of 30 frames per second, a
16cm by 12cm field of view, and a pixel density of 64.6
pixels/cm.
The computer used with the eye tracker is a Lenovo 3000
N100 laptop with a 15.4 inch screen running on Windows
XP.
Performance Evaluation Software
Performance data was collected using a Java GUI/Swing
program that simulates ISO 9241 – Part 9 task #2 and a
Java based Anova program was used to test for significant
results.
Procedure
Each participant was warned about prolonged viewing of
a computer screen and infrared light and asked if they had
any medical conditions regarding their eyes that could be
affected. Those who had no medical conditions and chose
to continue filled in a questionnaire asking their age,
gender, any experience with eye trackers and computer
mice and if they wore contact lenses or glasses.
Participants were informed that they could wear contact
lenses or glasses if they wore them.
Each participant was then asked to place themselves in
front of the laptop while being within 50-60cm in front of
the eye tracker and able to see the entire screen (Figure 2).
Participants were asked to sit comfortably to try to not
move their head during the experiment as they were
warned of prolonged staring at the screen and that the
tracker must see their eyes at the center of the screen as
displayed by the running software which isn't shown
during the experiment to reduce visual distractions.
The eye tracker is placed in front of the screen and
adjusted to an angle such that the participants’ eyes are
approximately at the center of the screen after they found
a comfortable position.
Before the start of the experiment, participants would
calibrate until they achieved a score of at least 4.0 for
each eye with no more than a 0.4 deviation between each
eye. This is only done once before the experiment for
click by dwelling and blinking.
After successful calibration, participants were informed of
how to click with the eye tracker and they would hear a
click noise if they clicked correctly. Participants were
allowed to practice as much as they want before
beginning the experiment.
When they were ready to start the experiment,
participants were asked to select the center of the red
target “as quickly and accurately as possible” and that
their completion time and target misses would be
recorded, but their completion time doesn't begin until the
first target is selected. The experiment didn't begin until
they clicked the quick launch icon at the task bar.
After the experiment is finished, each participant filled in
a questionnaire to rate their preferences and performance
of the eye tracker and how much fatigue they had.
Design
The main independent variable (factor) for this
experiment is the point-select technique with three levels:
 Blink: eye tracking + blink at target for 500ms
 Dwell: eye tracking + dwell at target for 500ms
 Mouse: mouse with up click (baseline
condition)
The ISO 9241 Java program runs 4 blocks of 17 targets,
each block having different target widths and distances
between each target:
 Target Widths: 16, 32 pixels (6, 12 mm),
 Target Distances: 254, 509 pixels ( 82.5,165
mm)
The 4 blocks of trials and 4 target width and distance
combinations were two other independent variables.
Figure 2: A participant during the experiment

4. Figure 3 displays a sample block with the order of target
selection.
The dependent variables were throughput (bits/s), error
rate (% of misses), and mean time per trial (target in ms).
This experiment has 1 between-subjects factor of two
levels; a group who did click by blinking before dwelling
and vice-versa. The groups are shown below:
 Blink, Dwell, Mouse
 Dwell, Blink, Mouse
 Mouse, Blink, Dwell
 Mouse, Dwell, Blink
having 3 participants each.
Each subsequent target appears on the opposite side of the
target circle in a clockwise fashion so that the distance
between each subsequent target is approximately the same
as required by ISO 9241.
After each block was completed, a dialog box would
display the participants’ results for the block and the
participant was encouraged to rest before continuing to
the next block. After all 4 blocks were completed; a final
dialog box displaying their overall results is shown.
RESULTS AND DISCUSSION
As Figure 4 depicts, the mouse has significantly better
throughput (F2,11 = 159.357, p < .0001) of 4.79 bits/s,
error rate of 6.4 % and mean time per trial of 951.7 ms
than click by dwelling and blinking as expected of users
with ample experience with a mouse and very little with
an eye tracker.
Click by dwelling was significantly higher in throughput
with 1.79 bits/s, error rate and significantly lower in mean
time per trial than click by blinking with a throughput of
1.16 bits/s. The significance was greatest with mean time
taken per trial (F1,11 = 91.494, p < .0001). Click by
blinking took about 60% longer to point and select a
target than click by dwelling.
Figure 3: Sample block with order of target selection
0
1
2
3
4
5
6
7
Dwell Blink Mouse
Throughput(bits/s)
0
10
20
30
40
50
60
70
80
90
Dwell Blink Mouse
ErrorRate(%)
0
500
1000
1500
2000
2500
3000
3500
4000
4500
Dwell Blink Mouse
CompletionsTimeperTrial(ms)
Figure 4: Overall results of Throughput, Error
Rate and Mean Time per Trial

5. Prolonged Use
One result to be considered is the affects on performance
by prolonged use of the eye tracker. This result can be
seen amongst the 4 blocks of trials since blocks done later
may have better or worse results than the blocks done
first. Since optimal use of the eye tracker requires users to
not move their head after they calibrate, it might be
difficult for a user to do so without feeling uncomfortable,
affecting performance.
As seen in Figure 5a, error rate has actually improved
through prolonged use of an eye tracker, as opposed to
worsening as expected, where each block took under one
minute to complete. Improvement of error rate was found
to be most significant with click by dwelling (F3,10 =
3.247, p < .05).
Throughout the experiment, most participants hadn’t
appeared to be moving very much and remained fairly
still as instructed. Results of improvement could have
been a result of practicing.
Target Size and Distance
Another interesting result observed is the participants’
error rate with blocks of varying target sizes and distances
between them.
As seen in Figure 5b, participants had a far lower error
rate when the target size (width) is larger and the distance
between each target is smaller when using the eye tracker.
Error rates were reduced by about 50% when target
widths were larger (doubled).
Results of throughput were similar but not as significant,
and there was no significance in mean time per trial.
-50 0 50 100
Block 1
Block 2
Block 3
Block 4
Error Rate (%)
Mouse
Blink
Dwell
Figure 5a: Error Rate results for each Block of Trials
-50 0 50 100 150
Dwell
Blink
Mouse
Error Rate (%)
Large Width + Large Distance
Large Width + Small Distance
Small Width + Large Distance
Small Width + Small Distance
Figure 5b: Error rate results for Different Target
Widths and Distances
Questionnaire
The eye tracker assessment questionnaire (Figure 6)
given at the end of the experiment consisted of 11
questions asking the participants to rate their overall
experience, preferences, eye tracking performance and
their fatigue (higher rating being higher fatigue). The
rating was done on a 5 point scale with 1 being the least
favorable and 5 being most favorable.
Participants were impressed with the performance of the
eye tracker, in particular with its smoothness and
operation speed. Eye fatigue was the biggest concern of
all participants. Participants complained that their eyes
became very dry and uncomfortable and that their necks
were a little stiff from not moving them. Eye fatigue
scored worst amongst all questions.
Discussions after the experiment revealed that participants
enjoyed using the eye tracker but still prefer to use a
standard mouse. Their concern was that they didn’t like
having to go through such a long calibration process, to
keep their head still for so long, to be a certain distance
away from the eye tracker. Participants generally
preferred to click by blinking than by dwelling because
they preferred to choose when to click and click by
dwelling produced involuntary clicks.

6. 0 1 2 3 4 5 6
Like Using Eye Tracker?
Overall Preference
(Compared to Mouse)
Click by Dwell Preference
Click by Blink Preference
Overall Comfort
Speed Performance
Selection Performance
Physical Effort
Smoothness Performance
Neck Fatigue
Shoulder Fatigue
Eye Fatigue
Figure 6: Eye Tracker Questionnaire Results
First Eye Tracker Evaluation Comparison
These results aren’t as good as the first eye tracker
evaluation experiment [5]. In the first experiment, results
had no select errors for click by dwelling, only timeout
errors where if no selection occurred in 2.5 s, it’s a
timeout error and each participant had fewer than 30% of
these errors. Click by pressing the space bar produced
selection errors but participants produced less than 30%
of these errors and very few timeout errors. Point-select
times were also much smaller.
This may be due the fact that participants were in a head-
fixed eye tracking system where the participant had their
heads strapped down so they couldn’t move, making it
less likely to reduce accuracy in prolonged use and
wasting less time needing to adjust and center their head
like with a head-free eye tracker.
Participants were much more concerned with fatigue of
the neck and shoulders from using the head-fixed eye
tracker whereas the head-free tracker participants had
little or no concern with fatigue except for the eyes. Eye
fatigue was badly rated for both experiments, but this is
expected of an eye tracker used for prolonged periods of
time.
A head-fixed eye tracker seems to be a more intrusive and
less versatile implementation of a mouse; it’s more prone
to fatigue of the neck and shoulders. A head free eye
tracker can be a more comfortable, portable and less
fatiguing solution and is capable of improving in
performance with practice.
CONCLUSION
This paper evaluates a portable, ubiquitous solution of an
eye tracker conforming to ISO 9241-9. Three point-select
techniques were evaluated, two involving the eye tracker
(click by dwelling and click by blinking) and one using a
mouse. Click by dwelling yielded better overall
performance than click by blinking with throughputs of
1.76 bits/s and 1.16 bits/s respectively which are far less
than the mouse’s throughput of 4.79 bits/s. Click by
blinking produced less errors but took more time to
complete the same task.
Participants preferred to click by blinking even though it
took longer to select but didn’t like using the eye tracker
overall primarily due to the fatigue they get, especially in
their eyes. Since all participants were young, fatigue may
not happen to them as much as older people, making it
easier for them to remain still longer and complete a task
that takes little time to complete. Performance of an eye
tracker may get worse if participants were older or doing
much longer tasks.
Ideas to consider in future experiments in evaluating an
eye tracker for point-select tasks would be to have
participants take part in longer experiments to discover
any loss of performance through prolonged use and to
determine better settings for eye tracking performance
such as target size, target distances and different clicking
techniques.
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