AN ALGORITHM FOR AUTOMATICALLY DETECTING DYSLEXIA ON THE FLY
Journal article, Peer reviewed
Published version
Permanent lenke
https://hdl.handle.net/10642/6795Utgivelsesdato
2018-06Metadata
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Originalversjon
Shrestha S, Murano P. AN ALGORITHM FOR AUTOMATICALLY DETECTING DYSLEXIA ON THE FLY. International Journal of Computer Science & Information Technology (IJCSIT). 2018;10(3) http://dx.doi.org/10.5121/ijcsit.2018.10301Sammendrag
There are different types of algorithms used in eye tracking technologies. These algorithms are divided into
two main categories: feature-based and model-based. Feature-based technologies consist of threshold
values, which are used to decide the presence or absence of features or determinant factors. While the
model-based approach is an iterative search of a model parameter, which is the best fitting model that is a
closest match to the image. However, these approaches have significant problems regarding computational
speed and accuracy.
Similarly, there are different types of eye – tracking technologies, which depend on different types of
technologies such as infrared video cameras and other technologies, which require specific calibration and
setup and are quite expensive. Therefore, in this paper, we propose an alternative eye–tracking technology
using a new eye-tracking algorithm, which is highly portable and independent of any hardware or software
systems. In an evaluation the algorithm worked accurately for users with strong dyslexia. Participants had
various positive and negative opinions regarding such an auto-detection system. Furthermore, we propose
that such technology could be used to automatically modify the content of online material to better suit
dyslexic users.