  One of the main challenges of gaze-based interactions is the ability to
distinguish normal eye function from a deliberate interaction with the computer
system, commonly referred to as 'Midas touch'. In this paper we propose, EyeTAP
(Eye tracking point-and-select by Targeted Acoustic Pulse) a hands-free
interaction method for point-and-select tasks. We evaluated the prototype in
two separate user studies, each containing two experiments with 33 participants
and found that EyeTAP is robust even in presence of ambient noise in the audio
input signal with tolerance of up to 70 dB, results in a faster movement time,
and faster task completion time, and has a lower cognitive workload than voice
recognition. In addition, EyeTAP has a lower error rate than the dwell-time
method in a ribbon-shaped experiment. These characteristics make it applicable
for users for whom physical movements are restricted or not possible due to a
disability. Furthermore, EyeTAP has no specific requirements in terms of user
interface design and therefore it can be easily integrated into existing
systems with minimal modifications. EyeTAP can be regarded as an acceptable
alternative to address the Midas touch.
