The Experts below are selected from a list of 2136 Experts worldwide ranked by ideXlab platform
M. Vanderlinden - One of the best experts on this subject based on the ideXlab platform.
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Re-education of a surface Dysgraphia with a visual imagery strategy
Cognitive Neuropsychology, 1992Co-Authors: Mp. Departz, Xavier Seron, M. VanderlindenAbstract:We report the re-education of a brain-damaged patient, LP, who presented a surface Dysgraphia. This Dysgraphia resulted from impairments of the lexical procedure of writing arising from a deficit located in the orthographic output lexicon. Our hypothesis was that LP had lost the relevant orthographic representations of some words. A two-stage therapeutic programme was carried out. In the first stage, we tried to optimise the relatively spared phonological procedure in writing by re-teaching some graphemic contextual rules. Because of residual surface dyslexia and verbal memory deficits associated with this surface Dysgraphia, and because of the structure of the French language, we retaught, in the second stage, the spelling of some irregular and ambiguous words by means of a visual imagery technique. In post-therapy, we observed a selective effect of this imagery strategy by comparison with a classic methodology of repetitive presentation of ambiguous and irregular spellings. The results of our therapy support cognitive-oriented therapeutic approaches and are discussed with regard to recent debates on the subject in neuropsychology.
Sara Rosenblum - One of the best experts on this subject based on the ideXlab platform.
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identifying developmental Dysgraphia characteristics utilizing handwriting classification methods
IEEE Transactions on Human-Machine Systems, 2017Co-Authors: Sara Rosenblum, Gideon DrorAbstract:Diagnosis of a specific learning disability such as Dysgraphia impacts children's academic progress and well-being. Dysgraphia is diagnosed by clinicians based on children's written product and educational staff's impressions. This process is time consuming and subjective. Consequently, many children with mild Dysgraphia remain undiagnosed, especially those from lower socioeconomic backgrounds. In this work, a method for automatic identification and characterization of Dysgraphia in third-grade children is described. The method is based on analyzing the child's writing dynamics by sampling the pressure the pen exerts on the paper as well as the pen's position and orientation by using a standard digital writing pad. Ninety-nine samples were collected from writers with Dysgraphia and proficient writers. A wide range of features covering dynamic properties of the writing and typographic (i.e., visual) properties were extracted for each participant. Machine learning methodologies were used to infer a statistical model, which is capable of discriminating dysgraphic products from proficient products with approximately 90% accuracy. The model was analyzed to conclude which handwriting features are most discriminative. Since the model provides 90% sensitivity for a specificity of 90%, it is the first step toward future use as an effective standard indicator for Dysgraphia detection.
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Identification and Rating of Developmental Dysgraphia by Handwriting Analysis
IEEE Transactions on Human-Machine Systems, 2017Co-Authors: Jiri Mekyska, Marcos Faundez-zanuy, Zdenek Mzourek, Zoltan Galaz, Zdenek Smekal, Sara RosenblumAbstract:Developmental Dysgraphia, being observed among 10–30% of school-aged children, is a disturbance or difficulty in the production of written language that has to do with the mechanics of writing. The objective of this study is to propose a method that can be used for automated diagnosis of this disorder, as well as for estimation of difficulty level as determined by the handwriting proficiency screening questionnaire. We used a digitizing tablet to acquire handwriting and consequently employed a complex parameterization in order to quantify its kinematic aspects and hidden complexities. We also introduced a simple intrawriter normalization that increased Dysgraphia discrimination and HPSQ estimation accuracies. Using a random forest classifier, we reached 96% sensitivity and specificity, while in the case of automated rating by the HPSQ total score, we reached 10% estimation error. This study proves that digital parameterization of pressure and altitude/tilt patterns in children with Dysgraphia can be used for preliminary diagnosis of this writing disorder.
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the effects of protracted graphomotor tasks on tripod pinch strength and handwriting performance in children with Dysgraphia
Disability and Rehabilitation, 2010Co-Authors: Batya Engelyeger, Sara RosenblumAbstract:Purpose. To examine the impact of prolonged graphomotor tasks on tripod-pinch strength and on handwriting process and product measures of children with Dysgraphia and typical peers.Method. Participants were 51 children in third to fifth grades, divided into two groups: 23 children with Dysgraphia and 28 typical peers, as determined by the Handwriting Proficiency Screening Questionnaire. The procedure included two sessions, with a 15-min break between sessions. In each session, the participants performed two tasks: the visual-motor control subtest of Bruininks-Oseretsky and a handwriting copying task, both performed on an electronic tablet as part of the Computerised Penmanship Evaluation Tool. Tripod pinch strength was evaluated before and after each session.Results. Significantly lower tripod-pinch strength was found among children with dysgrphia in comparison to typically developed peers. This deterioration in tripod-pinch strength was associated with a significant deterioration in handwriting process a...
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relationships between handwriting performance and organizational abilities among children with and without Dysgraphia a preliminary study
Research in Developmental Disabilities, 2010Co-Authors: Sara Rosenblum, Tsipi Aloni, Naomi JosmanAbstract:Organizational ability constitutes one executive function (EF) component essential for common everyday performance. The study aim was to explore the relationship between handwriting performance and organizational ability in school-aged children. Participants were 58 males, aged 7-8 years, 30 with Dysgraphia and 28 with proficient handwriting. Group allocation was based on children's scores in the Handwriting Proficiency Screening Questionnaire (HPSQ). They performed the Hebrew Handwriting Evaluation (HHE), and their parents completed the Questionnaire for Assessing Students' Organizational Abilities-for Parents (QASOA-P). Significant differences were found between the groups for handwriting performance (HHE) and organizational abilities (QASOA-P). Significant correlations were found in the dysgraphic group between handwriting spatial arrangement and the QASOA-P mean score. Linear regression indicated that the QASOA-P mean score explained 42% of variance of handwriting proficiency (HPSQ). Based on one discriminant function, 81% of all participants were correctly classified into groups. Study results strongly recommend assessing organizational difficulties in children referred for therapy due to handwriting deficiency.
Mp. Departz - One of the best experts on this subject based on the ideXlab platform.
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Re-education of a surface Dysgraphia with a visual imagery strategy
Cognitive Neuropsychology, 1992Co-Authors: Mp. Departz, Xavier Seron, M. VanderlindenAbstract:We report the re-education of a brain-damaged patient, LP, who presented a surface Dysgraphia. This Dysgraphia resulted from impairments of the lexical procedure of writing arising from a deficit located in the orthographic output lexicon. Our hypothesis was that LP had lost the relevant orthographic representations of some words. A two-stage therapeutic programme was carried out. In the first stage, we tried to optimise the relatively spared phonological procedure in writing by re-teaching some graphemic contextual rules. Because of residual surface dyslexia and verbal memory deficits associated with this surface Dysgraphia, and because of the structure of the French language, we retaught, in the second stage, the spelling of some irregular and ambiguous words by means of a visual imagery technique. In post-therapy, we observed a selective effect of this imagery strategy by comparison with a classic methodology of repetitive presentation of ambiguous and irregular spellings. The results of our therapy support cognitive-oriented therapeutic approaches and are discussed with regard to recent debates on the subject in neuropsychology.
Pierre Dillenbourg - One of the best experts on this subject based on the ideXlab platform.
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Acquisition of handwriting in children with and without Dysgraphia: A computational approach.
PloS one, 2020Co-Authors: Thomas Gargot, Thibault Asselborn, Laurence Casteran, Wafa Johal, Pierre Dillenbourg, Hugues Pellerin, Ingrid Zammouri, Salvatore Maria Anzalone, David Cohen, Caroline JollyAbstract:Handwriting is a complex skill to acquire and it requires years of training to be mastered. Children presenting Dysgraphia exhibit difficulties automatizing their handwriting. This can bring anxiety and can negatively impact education. 280 children were recruited in schools and specialized clinics to perform the Concise Evaluation Scale for Children's Handwriting (BHK) on digital tablets. Within this dataset, we identified children with Dysgraphia. Twelve digital features describing handwriting through different aspects (static, kinematic, pressure and tilt) were extracted and used to create linear models to investigate handwriting acquisition throughout education. K-means clustering was performed to define a new classification of Dysgraphia. Linear models show that three features only (two kinematic and one static) showed a significant association to predict change of handwriting quality in control children. Most kinematic and statics features interacted with age. Results suggest that children with Dysgraphia do not simply differ from ones without Dysgraphia by quantitative differences on the BHK scale but present a different development in terms of static, kinematic, pressure and tilt features. The K-means clustering yielded 3 clusters (Ci). Children in C1 presented mild Dysgraphia usually not detected in schools whereas children in C2 and C3 exhibited severe Dysgraphia. Notably, C2 contained individuals displaying abnormalities in term of kinematics and pressure whilst C3 regrouped children showing mainly tilt problems. The current results open new opportunities for automatic detection of children with Dysgraphia in classroom. We also believe that the training of pressure and tilt may open new therapeutic opportunities through serious games.
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extending the spectrum of Dysgraphia a data driven strategy to estimate handwriting quality
Scientific Reports, 2020Co-Authors: Thibault Asselborn, Mateo Chapatte, Pierre DillenbourgAbstract:This paper proposes new ways to assess handwriting, a critical skill in any child’s school journey. Traditionally, a pen and paper test called the BHK test (Concise Evaluation Scale for Children’s Handwriting) is used to assess children’s handwriting in French-speaking countries. Any child with a BHK score above a certain threshold is diagnosed as ‘dysgraphic’, meaning that they are then eligible for financial coverage for therapeutic support. We previously developed a version of the BHK for tablet computers which provides rich data on the dynamics of writing (acceleration, pressure, and so forth). The underlying model was trained on dysgraphic and non-dysgraphic children. In this contribution, we deviate from the original BHK for three reasons. First, in this instance, we are interested not in a binary output but rather a scale of handwriting difficulties, from the lightest cases to the most severe. Therefore, we wish to compute how far a child’s score is from the average score of children of the same age and gender. Second, our model analyses dynamic features that are not accessible on paper; hence, the BHK is useful in this instance. Using the PCA (Principal Component Analysis) reduced the set of 53 handwriting features to three dimensions that are independent of the BHK. Nonetheless, we double-checked that, when clustering our data set along any of these three axes, we accurately detected dysgraphic children. Third, Dysgraphia is an umbrella concept that embraces a broad variety of handwriting difficulties. Two children with the same global score can have totally different types of handwriting difficulties. For instance, one child could apply uneven pen pressure while another one could have trouble controlling their writing speed. Our new test not only provides a global score, but it also includes four specific score for kinematics, pressure, pen tilt and static features (letter shape). Replacing a global score with a more detailed profile enables the selection of remediation games that are very specific to each profile.
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The Dynamics of Handwriting Improves the Automated Diagnosis of Dysgraphia
2019Co-Authors: Konrad ̇zolna, Thibault Asselborn, Caroline Jolly, Laurence Casteran, Marie-ange Nguyen Morel, Wafa Johal, Pierre DillenbourgAbstract:Handwriting disorder (termed Dysgraphia) is a far from a singular problem as nearly 8.6% of the population in France is considered dysgraphic. Moreover, research highlights the fundamental importance to detect and remediate these handwriting difficulties as soon as possible as they may affect a child's entire life, undermining performance and self-confidence in a wide variety of school activities. At the moment, the detection of handwriting difficulties is performed through a standard test called BHK. This detection, performed by therapists, is laborious because of its high cost and subjectivity. We present a digital approach to identify and characterize handwriting difficulties via a Recurrent Neural Network model (RNN). The child under investigation is asked to write on a graphics tablet all the letters of the alphabet as well as the ten digits. Once complete, the RNN delivers a diagnosis in a few milliseconds and demonstrates remarkable efficiency as it correctly identifies more than 90% of children diagnosed as dysgraphic using the BHK test. The main advantage of our tablet-based system is that it captures the dynamic features of writingsomething a human expert, such as a teacher, is unable to do. We show that incorporating the dynamic
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Automated human-level diagnosis of Dysgraphia using a consumer tablet.
NPJ digital medicine, 2018Co-Authors: Thibault Asselborn, Caroline Jolly, Wafa Johal, Thomas Gargot, David Cohen, Łukasz Kidziński, Pierre DillenbourgAbstract:The academic and behavioral progress of children is associated with the timely development of reading and writing skills. Dysgraphia, characterized as a handwriting learning disability, is usually associated with dyslexia, developmental coordination disorder (dyspraxia), or attention deficit disorder, which are all neuro-developmental disorders. Dysgraphia can seriously impair children in their everyday life and require therapeutic care. Early detection of handwriting difficulties is, therefore, of great importance in pediatrics. Since the beginning of the 20th century, numerous handwriting scales have been developed to assess the quality of handwriting. However, these tests usually involve an expert investigating visually sentences written by a subject on paper, and, therefore, they are subjective, expensive, and scale poorly. Moreover, they ignore potentially important characteristics of motor control such as writing dynamics, pen pressure, or pen tilt. However, with the increasing availability of digital tablets, features to measure these ignored characteristics are now potentially available at scale and very low cost. In this work, we developed a diagnostic tool requiring only a commodity tablet. To this end, we modeled data of 298 children, including 56 with Dysgraphia. Children performed the BHK test on a digital tablet covered with a sheet of paper. We extracted 53 handwriting features describing various aspects of handwriting, and used the Random Forest classifier to diagnose Dysgraphia. Our method achieved 96.6% sensibility and 99.2% specificity. Given the intra-rater and inter-rater levels of agreement in the BHK test, our technique has comparable accuracy for experts and can be deployed directly as a diagnostics tool.
Lyndsey Nickels - One of the best experts on this subject based on the ideXlab platform.
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Treatment of irregular word spelling in developmental surface Dysgraphia
Cognitive neuropsychology, 2005Co-Authors: Ruth Brunsdon, Max Coltheart, Lyndsey NickelsAbstract:An increasing number of cognitive neuropsychological treatment studies of acquired Dysgraphia have been published in recent years, but to our knowledge there are no corresponding studies of developmental Dysgraphia. This paper reports a cognitive neuropsychological treatment programme designed for a child with developmental surface Dysgraphia. The treatment aim was to improve functioning of the orthographic output lexicon, and so treatment methods targeted irregular word spelling. Treatment methods were based on previous successful treatments employed in cases of adult acquired surface Dysgraphia (Behrmann, 1987; De Partz, Seron, & Van der Linden, 1992; Weekes & Coltheart, 1996). Results showed a significant treatment effect for both spelling and reading of irregular words that was largely stable over time and that generalised partially to spelling of untreated irregular words. Homophone words were not treated but some aspects of homophone reading and spelling also improved, though homophone confusion errors remained. Comparison of treatment effectiveness with and without mnemonics suggested that the mnemonic cue itself was not necessary to achieve treatment success for irregular word spelling. Analyses revealed that untreated irregular words whose spellings became correct as a result of treatment generalisation were those whose original misspellings were closest to being correct prior to treatment. Results also provided preliminary evidence that the mechanism underlying treatment generalisation involved improved access to orthographic representations, resulting in an increased tendency to employ orthography for spelling attempts and reduced reliance on phoneme to grapheme conversion.