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Metrics
to 1.5 seconds after the previous selection. This
was to prevent rhythm effects affecting the tap-
ping phase information in the mobile condition.
There were no restrictions on the accuracy that
was required by the user. A tap anywhere on the
screen regardless of the position of the target
counted as a selection.
There were two experimental conditions: tap-
ping while sitting and tapping while walking and
20 users performed both conditions in a counter-
balanced order, with 18 participants being right
handed and 2 participants being left handed. All
participants tapped with their dominant hand while
holding the device in their non-dominant hand. For
the walking condition, the participants navigated
a quiet triangle of paths on the university campus
(of total length approximately 200 metres).
Calibration of the screen becomes an issue
when looking at accuracy of tapping in a pen
based interface, as an error in the calibration can
lead to a consistent and unwanted bias in the re-
sults. The screen was calibrated once at the start
of the experiment, and the same device was used
throughout the experiment. Three participants
tested the screen calibration. The device was
placed on the desk and users performed a similar
task to the tapping study for four separate sessions.
In this case accuracy was heavily emphasised as
the most important aspect of the study. This was
borne out by the much closer concentration of
points than in the final results, with mean standard
deviation of the error for each participant for all
targets being less than a pixel. After each session,
the device was rotated by 90 degrees (additive for
each section) to negate any systematic tapping
bias. Mean values were recorded for each screen
target position and were subtracted from the fi-
nal results. This method provides a closer match
between the position the user actually tapped in
and the recorded tap position.
Standard usability metrics were used for assess-
ing user performance in the task. Comparisons
were made between time to tap and accuracy of
tap for each of the groups. Time to tap was taken
from the time that the target was displayed on
the screen to the time of the stylus down event.
The hypotheses were that users would be more
accurate and faster in the seated condition. The
effect of screen position of the target on accuracy
of the tap was also examined.
The instrumented usability approach also
allows us to gain further insights into the users
actions during the study. The interactions of par-
ticipants' tapping and step patterns were examined.
Gait Detection
As a mobile user walks while holding a mobile
device, his or her arm will oscillate as a result of
the user's gait. If we examine only the vertical axis
of this oscillation, there will be one oscillation per
step. Figure 5 shows a time series for the verti-
cal acceleration axis. A Fast Fourier Transform
is used to determine the frequency at which the
peak amplitude occurs, between 1 and 3Hz in the
spectrum. For the controlled conditions in this
study, this corresponds to the walking step rate.
In practice, this is the frequency of maximum
power in the spectrum as the users are looking at
the screen and therefore trying to hold the device
relatively still with respect to their body as they
walk. The vertical axis acceleration signal is then
zero phase shift filtered using a narrow bandpass
Butterworth filter centred around this frequency.
Figure 5 demonstrates the filtered signal. As the
user walks with the device held steady in one hand,
an approximately regular oscillation is formed in
the vertical axis. One oscillation corresponds to
one step.
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