Citation: Fassetti, F.; Fassetti, I.
Discriminating Pattern Mining for
Diagnosing Reading Disorders. Appl.
Sci. 2022, 12, 7540. https://doi.org/
10.3390/app12157540
Academic Editors: Sławomir
Nowaczyk, Rita P. Ribeiro and
Grzegorz Nalepa
Received: 11 June 2022
Accepted: 19 July 2022
Published: 27 July 2022
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Article
Discriminating Pattern Mining for Diagnosing
Reading Disorders
†
Fabio Fassetti
1,
*
,‡
and Ilaria Fassetti
1,2,‡
1
DIMES, University of Calabria, 87036 Rende, Italy; ilaria.fassetti@gmail.com
2
LogopediaTherapeia Rehabilitation Center, 00162 Rome, Italy
* Correspondence: f.fassetti@dimes.unical.it
† This paper is an extended version of paper published in the 33rd Annual ACM Symposium on Applied
Computing, held in Pau, France, 9–13 April 2018.
‡ These authors contributed equally to this work.
Abstract:
Tachistoscopes are devices that display a word for several seconds and ask the user to write
down the word. They have been widely employed to increase recognition speed, to increase reading
comprehension and, especially, to individuate reading difficulties and disabilities. Once the therapist
is provided with the answers of the patients, a challenging problem is the analysis of the strings to
individuate common patterns in the erroneous strings that could raise suspicion of related disabilities.
In this direction, this work presents a machine learning technique aimed at mining exceptional string
patterns and is precisely designed to tackle the above-mentioned problem. The technique is based
on non-negative matrix factorization, nnmf, and exploits as features the structure of the words in
terms of the letters composing them. To the best of our knowledge, this is the first attempt of mining
tachistoscope answers to discover intrinsic peculiarities of the words possibly involved in reading
disabilities. From the technical point of view, we present a novel variant of nnmf methods with the
adjunctive goal of discriminating between sets. The technique has been experimented in a real case
study with the help of an Italian speech therapist center that collaborate with this work.
Keywords: reading disorders; matrix factorization; pattern extraction
1. Introduction
Tachistoscopes are widely employed devices useful in many scenarios [
1
–
3
]. Roughly
speaking, these instruments display a word for some milliseconds (on the basis of the
wanted difficulty for the exercise) and next the patient is asked for writing down the word.
The results shed lights on reading speed, reading comprehension, and are generally helpful
to highlight many kinds of reading disorders. Such devices provide the therapist with a set
of correctly written words and a set of erroneously written words. Tachistoscopic training,
also known as Flash Recognition Training (FRT), in some environments requires that an
individual be able to acquire visual information and remember them later on in an optimal
way. A second phase requires that the individual express the derived information through
verbal, written, or keyboard means. The tachistoscope is therefore used by the speech
therapist to evaluate the visual reaction time, speed and recognition interval, automation
and visual sequencing. We know that, when a subject with good reading skills is faced with
a text, his eyes scan it horizontally line by line and from left to right, in a path defined as
“saccades and fixations”. The process, completely automatic, has been known for some time:
our eyes proceed “in jumps” of about seven-nine characters, pausing for a few fractions
of a second more on some key points generally corresponding to the most important
and most significant words. The mechanisms underlying the reading are manifold and
integrate with each other. These rapid movements serve to obtain the visual information
essential for decoding the text. Among the parameters of the text that influence saccades we
include length, lexical frequency, the predictability of words in the text. Proper functioning
Appl. Sci. 2022, 12, 7540. https://doi.org/10.3390/app12157540 https://www.mdpi.com/journal/applsci
