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Journal of Psycholinguistic Research Dec 2023Research regarding dysgraphia, an impairment in writing, is attaining more attention in recent times. The existing studies on dysgraphia draw insights from cognitive,...
Research regarding dysgraphia, an impairment in writing, is attaining more attention in recent times. The existing studies on dysgraphia draw insights from cognitive, behavioural, neurological, and genetic fields of knowledge. However, these multiple studies on dysgraphia fail to illustrate how these cognitive, behavioural, neurological, and genetic systems interact and intersect in dysgraphia. Therefore, the studies could not offer a comprehensive understanding of dysgraphia. In order to fill this gap, the review attempts to study dysgraphia using the notion of modularity by accommodating insights from cognitive, behavioural, neurological, and genetic aspects of dysgraphia. Such a profound understanding could facilitate an early diagnosis and holistic intervention towards dysgraphia.
Topics: Humans; Agraphia; Writing
PubMed: 37930468
DOI: 10.1007/s10936-023-10029-6 -
Scientific Reports Dec 2020Dysgraphia, a disorder affecting the written expression of symbols and words, negatively impacts the academic results of pupils as well as their overall well-being. The...
Dysgraphia, a disorder affecting the written expression of symbols and words, negatively impacts the academic results of pupils as well as their overall well-being. The use of automated procedures can make dysgraphia testing available to larger populations, thereby facilitating early intervention for those who need it. In this paper, we employed a machine learning approach to identify handwriting deteriorated by dysgraphia. To achieve this goal, we collected a new handwriting dataset consisting of several handwriting tasks and extracted a broad range of features to capture different aspects of handwriting. These were fed to a machine learning algorithm to predict whether handwriting is affected by dysgraphia. We compared several machine learning algorithms and discovered that the best results were achieved by the adaptive boosting (AdaBoost) algorithm. The results show that machine learning can be used to detect dysgraphia with almost 80% accuracy, even when dealing with a heterogeneous set of subjects differing in age, sex and handedness.
Topics: Adolescent; Agraphia; Algorithms; Case-Control Studies; Child; Data Accuracy; Female; Handwriting; Humans; Machine Learning; Male
PubMed: 33299092
DOI: 10.1038/s41598-020-78611-9 -
Nursing May 2008
Topics: Agraphia; Humans
PubMed: 18431188
DOI: 10.1097/01.NURSE.0000317668.40925.d8 -
Canadian Journal of Psychiatry. Revue... Oct 1989
Topics: Agraphia; Delirium; Handwriting; Humans; Neurocognitive Disorders
PubMed: 2804886
DOI: 10.1177/070674378903400729 -
Cortex; a Journal Devoted To the Study... Jan 2011
Review
Topics: Adult; Agraphia; Brain; Cerebellum; Child; Cognition; Dyslexia; Humans; Learning Disabilities; Motor Skills; Neural Pathways
PubMed: 19818437
DOI: 10.1016/j.cortex.2009.08.016 -
Progress in Neuro-psychopharmacology &... Jan 2023Writing abilities are impacted by dysgraphia, a condition of learning disability. It might be challenging to diagnose dysgraphia at an initial point of a child's...
Writing abilities are impacted by dysgraphia, a condition of learning disability. It might be challenging to diagnose dysgraphia at an initial point of a child's upbringing. Problematic abilities linked to Dysgraphia difficulties that is utilized in detecting the learning disorder. The features used in this research to identify dysgraphia include handwriting and geometric features that is reclaimed using kekre-discrete cosine mathematical model. The feature learning step of deep transfer learning makes good use of the obtained features to identify dysgraphia. The results of the data collection indicate that this study can use handwritten images to detect children who have dysgraphia. Compared to past investigations, this experiment has shown a significant improvement in the capacity to identify dysgraphia using handwritten drawings. The proposed approach is compared with the machine learning and deep learning approaches where the Kekre-Discrete Cosine Transform with Deep Transfer Learning (K-DCT-DTL) outperforms the existing approaches. The proposed K-DCT-DTL approach attains 99.75% of highest accuracy that exhibits the efficiency of the proposed method.
Topics: Child; Humans; Agraphia; Deep Learning; Handwriting; Machine Learning; Learning Disabilities
PubMed: 36181958
DOI: 10.1016/j.pnpbp.2022.110647 -
Neurology May 2022Most primary progressive aphasia (PPA) literature is based on English language users. Linguistic features that vary from English, such as logographic writing systems,...
BACKGROUND AND OBJECTIVES
Most primary progressive aphasia (PPA) literature is based on English language users. Linguistic features that vary from English, such as logographic writing systems, are underinvestigated. The current study characterized the dysgraphia phenotypes of patients with PPA who write in Chinese and investigated their diagnostic utility in classifying PPA variants.
METHODS
This study recruited 40 participants with PPA and 20 cognitively normal participants from San Francisco, Hong Kong, and Taiwan. We measured dictation accuracy using the Chinese Language Assessment for PPA (CLAP) 60-character orthographic dictation test and examined the occurrence of various writing errors across the study groups. We also performed voxel-based morphometry analysis to identify the gray matter regions correlated with dictation accuracy and prevalence of writing errors.
RESULTS
All PPA groups produced significantly less accurate writing responses than the control group and no significant differences in dictation accuracy were noted among the PPA variants. With a cut score of 36 out of 60 in the CLAP orthographic dictation task, the test achieved sensitivity and specificity of 90% and 95% in identifying Chinese participants with PPA vs controls. In addition to a character frequency effect, dictation accuracy was affected by homophone density and the number of strokes in semantic variant PPA and logopenic variant PPA groups. Dictation accuracy was correlated with volumetric changes over left ventral temporal cortices, regions known to be critical for orthographic long-term memory. Individuals with semantic variant PPA frequently presented with phonologically plausible errors at lexical level, patients with logopenic variant PPA showed higher preponderance towards visual and stroke errors, and patients with nonfluent/agrammatic variant PPA commonly exhibited compound word and radical errors. The prevalence of phonologically plausible, visual, and compound word errors was negatively correlated with cortical volume over the bilateral temporal regions, left temporo-occipital area, and bilateral orbitofrontal gyri, respectively.
DISCUSSION
The findings demonstrate the potential role of the orthographic dictation task as a screening tool and PPA classification indicator in Chinese language users. Each PPA variant had specific Chinese dysgraphia phenotypes that vary from those previously reported in English-speaking patients with PPA, highlighting the importance of language diversity in PPA.
Topics: Agraphia; Aphasia, Primary Progressive; China; Humans; Language; Phenotype; Primary Progressive Nonfluent Aphasia
PubMed: 35410909
DOI: 10.1212/WNL.0000000000200350 -
Journal of Speech, Language, and... Dec 2006This article presents a critical review of literature on dysgraphia associated with Alzheimer's disease (AD). Research presented includes discussions of central and... (Review)
Review
PURPOSE
This article presents a critical review of literature on dysgraphia associated with Alzheimer's disease (AD). Research presented includes discussions of central and peripheral spelling impairments as well as the impact of general, nonlinguistic cognitive functions on dysgraphia associated with AD.
METHOD
The studies critically reviewed were from a variety of disciplines, with emphasis on seminal work, recent literature, and the first author's research.
CONCLUSIONS
Studies have shown that writing impairment is heterogeneous within the AD population; however, there are certain aspects of the writing process that are more vulnerable than others and may serve as diagnostic signs. Identifying patterns of writing impairment at different stages of AD may help to chart disease progression and assist in the development of appropriate interventions.
Topics: Aged; Agraphia; Alzheimer Disease; Cognition Disorders; Humans; Prevalence
PubMed: 17197498
DOI: 10.1044/1092-4388(2006/094) -
Journal of Child Neurology Jan 1995
Review
Topics: Agraphia; Child; Developmental Disabilities; Humans; Motor Skills; Writing
PubMed: 7538525
DOI: 10.1177/08830738950100S103 -
Developmental Medicine and Child... Apr 2007Failure to attain handwriting competency during the school-age years often has far-reaching negative effects on both academic success and self-esteem. This complex... (Review)
Review
Failure to attain handwriting competency during the school-age years often has far-reaching negative effects on both academic success and self-esteem. This complex occupational task has many underlying component skills that may interfere with handwriting performance. Fine motor control, bilateral and visual-motor integration, motor planning, in-hand manipulation, proprioception, visual perception, sustained attention, and sensory awareness of the fingers are some of the component skills identified. Poor handwriting may be related to intrinsic factors, which refer to the child's actual handwriting capabilities, or extrinsic factors which are related to environmental or biomechanical components, or both. It is important that handwriting performance be evaluated using a valid, reliable, standardized tool combined with informal classroom observation and teacher consultation. Studies of handwriting remediation suggest that intervention is effective. There is evidence to indicate that handwriting difficulties do not resolve without intervention and affect between 10 and 30% of school-aged children. Despite the widespread use of computers, legible handwriting remains an important life skill that deserves greater attention from educators and health practitioners.
Topics: Agraphia; Brain; Child; Child, Preschool; Handwriting; Humans; Kinesthesis; Occupational Therapy; Proprioception; Psychomotor Disorders; Remedial Teaching
PubMed: 17376144
DOI: 10.1111/j.1469-8749.2007.00312.x