A pilot study of the use of emerging computer technologies to improve the effectiveness of reading and writing therapies in children with Down syndrome

Felix, Vanessa G.; Mena, Luis J.; Ostos, Rodolfo; Maestre, Gladys E.

doi:10.1111/bjet.12426

Cited by 55 publications

(50 citation statements)

References 58 publications

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“…e benefits of mobile technology can be found anywhere: communication, education, scientific research, healthcare, and entertainment, to name a few, but despite its multidisciplinary application, mobile technology and all its advantages are far away from being accessible to people with disabilities [1], people with Down syndrome among them [2]. Researchers in Human-Computer Interaction (HCI) have recognized and analyzed several barriers that people with Down syndrome face when interacting with mobile technology [3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Analyzing Typical Mobile Gestures in mHealth Applications for Users with Down Syndrome

Luna-García

Mendoza-González²,

Mendoza-González

et al. 2018

Mobile Information Systems

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Transportation, Health, and Entertainment are just a few areas of mobile technology application. Nevertheless, there are still some people who find difficulties using it. Although there are a lot of applications of mHealth available for almost any kind of mobile device, there is still a lack of understanding and attending users' needs, especially those of users with disabilities. People with Down syndrome have the potential to function as active members of our society, taking care of themselves and their own, having jobs, voting, and so on, but their physical limitations prevent them from handling correctly technological tools that could enhance their performance, including mobile technology. In this paper, we had analyzed how suitable the mHealth applications are for users with Down syndrome. We tested 24 users and analyzed their physical performance in fine-motor movements while developing a set of tasks over a mHealth application. Results showed that the design of a mHealth application for users with Down syndrome must center its interaction with simple gestures as tap and swipe avoiding more complex ones as spread and rotate. is research is a starting point to understand the fundamentals of people with Down syndrome interacting with mobile technology.

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Section: Introductionmentioning

confidence: 99%

Analyzing Typical Mobile Gestures in mHealth Applications for Users with Down Syndrome

Luna-García

Mendoza-González²,

Mendoza-González

et al. 2018

Mobile Information Systems

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“…Although some of these limitations of DS cannot be overcome, early speech training can improve the quality with which individuals with DS communicate. In this context, some studies have examined speech production by focusing on articulatory sounds made by children with DS [29][30][31].…”

Section: Related Workmentioning

confidence: 99%

An Analysis of Visual Speech Features for Recognition of Non-articulatory Sounds using Machine Learning

Carlos¹,

Alinne²,

Carolina³

et al. 2019

IJCA

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People with articulation and phonological disorders need exercise to execute sounds of speech. Essentially, exercise starts with production of non-articulatory sounds in clinics or homes where a huge variety of the environment sounds exist; i.e., in noisy locations. Speech recognition systems considers environment sounds as background noises, which can lead to unsatisfactory speech recognition. This study aims to assess a system that supports aggregation of visual features to audio features during recognition of non-articulatory sounds in noisy environments. Thehe methods Mel-Frequency Cepstrum Coefficients and Laplace transform were used to extract audio features, Convolutional Neural Network to extract video features, and Support Vector Machine to recognize audio and Long Short-Term Memory networks for video recognition. Report experimental results regarding the accuracy, recall and precision of the system on a set of 585 sounds was achieved. Overall, the results indicate that video information can complement audio recognition and assist non-articulatory sound recognition.

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“…The vocabulary and its continuous stimulation is a good predictor of reading skills [33,34], allowing to reach a degree of reading of secondary discrimination. A related study indicate that technologies improved reading therapies [35]. Taking into account the previous work, we designed didactic strategies with gestural resources to stimulate visual-motor memory in the DS population and studied the stimulation of reading abilities using gestural interaction.…”

Section: Reading Skills Of Down Syndrome Students and Gestural Interfmentioning

confidence: 99%

Gestural Interaction and Reading Skills: A Case of Study with People with Down Syndrome

Torres-Carrión¹,

González-González²,

Bravo³

et al. 2019

Preprint

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People with Down syndrome present cognitive difficulties that affect their reading skills. In this study we present results about the use of gestural interaction with Kinect sensor to improve the reading skills of students with Down syndrome. Following a case of study method for small samples with disabilities, measuring different variables related to reading skills in an experimental group and in a control group. We found improvements in the visual association, visual comprehension, sequential memory, and visual integration after this stimulation in the experimental group compared to the control group. Also, we found that the number of error and delay time of interaction decrease between sessions in the experimental group. learning (typical pre-school and school age) can be used with students with DS too (i.e. PBSkids 1 reading) or to working memory training (i.e. Cogmed 2 ).There are several specialties related with the reading teaching, such as the speech therapy, with continuous contributions of psycholinguistics [9]. Following Zubiría's theory [10], there are six levels of readings: phonetics, primary, secondary and tertiary decoding, categorical and "metatextual", leaving the first four levels as elementary and the last two as higher level. In our case, based on this theory, we have focus on secondary decoding, because it is the common level of reading in the DS population.Reading comprehension as a cognitive process gives meaning to the relevant ideas of a text and its relation to prior knowledge, in which working memory's executive processes play a crucial role. The process of memory assessment is given through brief stimuli called 'memory reconsolidation'. Relationship between response time (velocity) and a number of identified items aiming to expose how information is maintained in short term memory and why this memory has limited capacity [11]. The memory reconsolidation allows the reactivation and modification of memories by stimuli [12]. Its strength being inversely proportional to the age of memory [13]. Taking into account this context, in this study the variables time and cognitive errors were selected as a methodological basis to measure the variation of learning between periodic lessons.About the assessment, it allows teachers and educational system to undertake the best methodological and didactic strategies [14,15,16]. In students with DS, the assessment does not vary from the rest of the students in terms of measuring their achievement, measuring variables such as response time, successes and errors. However, it is important to consider the student's degree of error [17,18], or the continuous feedback to the process, motivating the effort of the student, not only the achievement [15]. In this work, the assessment process has been designed and supported by technical designers and teachers taking special characteristics of DS students. One of the most important dimensions in the assessment of teaching-learning process is probably the academic performance [19]. Academic performance can be assess...

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A pilot study of the use of emerging computer technologies to improve the effectiveness of reading and writing therapies in children with Down syndrome

Cited by 55 publications

References 58 publications

Analyzing Typical Mobile Gestures in mHealth Applications for Users with Down Syndrome

Analyzing Typical Mobile Gestures in mHealth Applications for Users with Down Syndrome

An Analysis of Visual Speech Features for Recognition of Non-articulatory Sounds using Machine Learning

Gestural Interaction and Reading Skills: A Case of Study with People with Down Syndrome

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