Handwriting Changes in Alzheimer's Disease: A Systematic Review.

BACKGROUND: Handwriting is a complex process involving fine motor skills, kinesthetic components, and several cognitive domains, often impaired by Alzheimer's disease (AD). OBJECTIVE: Provide a systematic review of handwriting changes in AD, highlighting the effects on motor, visuospatial and linguistic features, and to identify new research topics. METHODS: A search was conducted on PubMed, Scopus, and Web of Science to identify studies on AD and handwriting. The review followed PRISMA norms and analyzed 91 articles after screening and final selection. RESULTS: Handwriting is impaired at all levels of the motor-cognitive hierarchy in AD, particularly in text, with higher preservation of signatures. Visuospatial and linguistic features were more affected. Established findings for motor features included higher variability in AD signatures, higher in-air/on-surface time ratio and longer duration in text, longer start time/reaction time, and lower fluency. There were conflicting findings for pressure and velocity in motor features, as well as size, legibility, and pen lifts in general features. For linguistic features, findings were contradictory for error patterns, as well as the association between agraphia and severity of cognitive deficits. CONCLUSIONS: Further re-evaluation studies are needed to clarify the divergent results on motor, general, and linguistic features. There is also a lack of research on the influence of AD on signatures and the effect of AD variants on handwriting. Such research would have an impact on clinical management (e.g., for early detection and patient follow-up using handwriting tasks), or forensic examination aimed at signatory identification.

Handwriting Evaluation Using Deep Learning with SensoGrip.

Handwriting learning disabilities, such as dysgraphia, have a serious negative impact on children's academic results, daily life and overall well-being. Early detection of dysgraphia facilitates an early start of targeted intervention. Several studies have investigated dysgraphia detection using machine learning algorithms with a digital tablet. However, these studies deployed classical machine learning algorithms with manual feature extraction and selection as well as binary classification: either dysgraphia or no dysgraphia. In this work, we investigated the fine grading of handwriting capabilities by predicting the SEMS score (between 0 and 12) with deep learning. Our approach provided a root-mean-square error of less than 1 with automatic instead of manual feature extraction and selection. Furthermore, the SensoGrip smart pen SensoGrip was used, i.e., a pen equipped with sensors to capture handwriting dynamics, instead of a tablet, enabling writing evaluation in more realistic scenarios.

Speech and Language Therapy for Acquired Central Dysgraphia in Neurological Patients: A Systematic Review to Describe and Identify Trainings for Clinical Practice.

PURPOSE: Acquired central dysgraphia is a heterogeneous neurological disorder that usually co-occurs with other language disorders. Written language training is relevant to improve everyday skills and as a compensatory strategy to support limited oral communication. A systematic evaluation of existing writing treatments is thus needed. METHOD: We performed a systematic review of speech and language therapies for acquired dysgraphia in studies of neurological diseases (PROSPERO: CRD42018084221), following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist with a search on several databases for articles written in English and published until August 31, 2021. Only methodological well-designed studies were included. Further assessment of methodological quality was conducted by means of a modified version of the Downs and Black checklist. RESULTS: Eleven studies of 43 patients in total were included. For each study, we collected data on type of population, type of impairment, experimental design, type of treatment, and measured outcomes. The studies had a medium level of assessed methodological quality. An informative description of treatments and linkages to deficits is reported. CONCLUSIONS: Although there is a need for further experimental evidence, most treatments showed good applicability and improvement of written skills in patients with dysgraphia. Lexical treatments appear to be more frequently adopted and more flexible in improving dysgraphia and communication, especially when a multimodal approach is used. Finally, the reported description of treatment modalities for dysgraphia in relation to patients' deficits may be important for providing tailored therapies in clinical management.

Early diagnosis of the learning disabilities in kids using a computer game-based solution.

PURPOSE: Learning disabilities or learning disorders are umbrella terms used for wide variety of learning problems like Dyslexia, Dyscalculia, Dysgraphia, and Dyspraxia. These disabilities are due to the neurological disorders which affects brain functions. Early diagnosis of these disabilities in kids from age 3 to 6 will help to start early medical treatments and get them back to the normal condition. MATERIAL AND METHOD: we developed a software-based Learning Disability Evaluation Kit called YALU with computer Game Modules for kids targeting their learning disabilities. These Computer game-based modules of the YALU consist of different tasks for the different age levels to identify the symptoms of the disabilities mentioned above. The children's interaction results to each task of the game modules with the answers of the questioner about the children given by the parents will be evaluated with the threshold values given by a panel of consultant psychologist and paediatrician of the normal kids to identify the learning disabilities in kids aged 3-6 years. The result will be given to the respective parties and uploaded to the Website under the child's name. RESULT: YALU has been tested using 50 students in age 3-5 in three preschools. The teachers have identified Fourteen students with some learning disability symptoms. Using YALU, twelve out of fourteen students had been clearly identified. Hence, the YALU Evaluation Kit to have an accuracy 85% in diagnosing the right disability. However, the accuracy could be increased with the accurate assessments of the parents about their kids.IMPLICATIONS FOR REHABILITATIONLearning disabilities are neurological disorders that affect the brain's ability to receive, process, store, respond to and communicate information; and there are four types (Dyslexia, Dyspraxia, Dysgraphia and Dyscalculia)In this paper, we present the extracted computational techniques targeting the Dyslexia, Dyspraxia, Dysgraphia and Dyscalculia and developed a software application (YALU Learning Disability Evaluation Kit) which consists of computer game modules for the kids for evaluation their learning disabilities.The developed game modules can screen the learning disabilities and these gamification modules (YALU) consists of tasks which are based on symptoms of the said disabilities. The outcomes of each module is evaluated these learning disabilities in kids age from 3 years to 6 years by analysing children's interactions to the each tasks, the child condition and then compare the result with the threshold values of the normal kids given by consultant psychologist and paediatrician.

Two adult patients with moyamoya disease presenting with alexia with agraphia limited to kanji: can revascularization improve characteristic symptoms?

Patients with moyamoya disease (MMD) may exhibit higher brain dysfunction due to hypoperfusion, which may be ameliorated by revascularization. However, few studies have examined the relationship between cerebral perfusion and language function or the ameliorating effect of revascularization on language dysfunction. We present two cases with MMD who presented with alexia with agraphia, specifically for Japanese kanji. The patients had impaired perfusion in the left inferior temporal and lateral occipital lobes. Following superficial temporal artery-middle cerebral artery bypass, the symptoms improved dramatically. Thus, correction of hypoperfusion may be effective even in adult patients with MMD presenting with language dysfunction.

Dysgraphia Phenotypes in Native Chinese Speakers With Primary Progressive Aphasia.

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.

Tonal and orthographic analysis in a Cantonese-speaking individual with nonfluent/agrammatic variant primary progressive aphasia.

Clinical understanding of primary progressive aphasia (PPA) has been established based on English-speaking population. The lack of linguistic diversity in research hinders the diagnosis of PPA in non-English speaking patients. This case report describes the tonal and orthographic deficits of a multilingual native Cantonese-speaking woman with nonfluent/agrammatic variant PPA (nfvPPA) and progressive supranuclear palsy. Our findings suggest that Cantonese-speaking nfvPPA patients exhibit tone production impairments, tone perception deficits at the lexical selection processing, and linguistic dysgraphia errors unique to logographic script writer. These findings suggest that linguistic tailored approaches offer novel and effective tools in identifying non-English speaking PPA individuals.

Analysis of Graphomotor Tests with Machine Learning Algorithms for an Early and Universal Pre-Diagnosis of Dysgraphia.

Five to ten percent of school-aged children display dysgraphia, a neuro-motor disorder that causes difficulties in handwriting, which becomes a handicap in the daily life of these children. Yet, the diagnosis of dysgraphia remains tedious, subjective and dependent to the language besides stepping in late in the schooling. We propose a pre-diagnosis tool for dysgraphia using drawings called graphomotor tests. These tests are recorded using graphical tablets. We evaluate several machine-learning models and compare them to build this tool. A database comprising 305 children from the region of Grenoble, including 43 children with dysgraphia, has been established and diagnosed by specialists using the BHK test, which is the gold standard for the diagnosis of dysgraphia in France. We performed tests of classification by extracting, correcting and selecting features from the raw data collected with the tablets and achieved a maximum accuracy of 73% with cross-validation for three models. These promising results highlight the relevance of graphomotor tests to diagnose dysgraphia earlier and more broadly.

Handwriting in Alzheimer's Disease.

BACKGROUND: Agraphia is a typical feature in the clinical course of Alzheimer's disease (AD). OBJECTIVE: Assess the differences between AD and normal aging as regards kinematographic features of handwriting and elucidate writing deficits in AD. METHODS: The study included 23 patients with AD (78.09 years/SD = 7.12; MMSE 21.39/SD = 3.61) and 34 healthy controls (75.56 years/SD = 5.85; MMSE 29.06/SD = 0.78). Both groups performed alphabetical and non-alphabetical writing tasks. The kinematographic assessment included the average number of inversions per stroke (NIV; number of peaks in the velocity profile in a single up or down stroke), percentage of automated segments, frequency (average number of strokes per second), writing pressure, and writing velocity on paper. RESULTS: A total of 14 patients showed overt writing difficulties reflected by omissions or substitutions of letters. AD patients showed less automated movements (as measured by NIV), lower writing velocity, and lower frequency of up-and-down strokes in non-alphabetical as well as in alphabetical writing. In the patient group, Spearman correlation analysis between overt writing performance and NIV was significant. That means patients who had less errors in writing a sentence showed a higher automaticity in handwriting. The correctness of alphabetical writing and some kinematographic measures in writing non-alphabetical material reached excellent diagnostic values in ROC analyses. There was no difference in the application of pressure on the pen between patients and controls. CONCLUSION: Writing disorders are multi-componential in AD and not strictly limited to one processing level. The slow and poorly automated execution of motor programs is not bound to alphabetical material.

Dystypia Associated with Diaschisis of the Middle Frontal Gyri after Left Angular Infarction.

Dystypia without aphasia, agraphia, or apraxia is a rare symptom and has been suggested to result from a lesion in the left middle frontal cortex. We herein describe a man with dystypia with agraphia due to infarction of the left angular gyrus. His dystypia seemed to result from the convergence failure of the kana into the alphabetical spellings. During dystypia, hypoperfusion of the bilateral middle frontal cortices was discovered. However, after his symptoms improved, blood flow in the middle frontal cortices returned to normal. This case suggests that the middle frontal cortex is downstream of the angular gyrus in the dictating pathway and a lesion in the left middle frontal cortex could cause pure dystypia.

Dysgraphia detection through machine learning.

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.

Evolution of Writing Impairment in Spanish Patients with Alzheimer's Disease.

BACKGROUND: Although some studies suggest that writing difficulties may be one of the early symptoms of Alzheimer's disease (AD), they have been scarcely studied compared to oral language. Particularly noteworthy is the paucity of longitudinal studies that enable the observation of writing impairment as cognitive decline progresses. OBJECTIVE: The aim of this study was to examine the characteristics of writing in patients with AD and to monitor the deterioration of their performance over a follow-up period. METHODS: Sixty-four participants (half with AD and half healthy elderly) were compared in a word and pseudo-word dictation task. Patients were evaluated every 6 months over a 2.5 year follow-up period. RESULTS: The evolution of patient performance and error profile shows a typical pattern of deterioration, with early damage to the lexical pathway, which later extends to the phonological pathway and eventually affects peripheral processes. CONCLUSION: These results confirm the presence of writing difficulties from the early stages of AD, supporting the value of this task for early diagnosis. Furthermore, it allows us to explain the contradictory data obtained in previous investigations.

Acquisition of handwriting in children with and without dysgraphia: A computational approach.

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.

A Rare Clinical Antity; Pure Gerstmann Syndrome.

Gerstmann syndrome is defined as a tetrad including agraphia, acalculia, finger agnosia, and right-left disorientation. In the case studies presented in the literature, it has been reported that Gerstmann syndrome usually appears as an incomplete tetrad of symptoms or accompanied by cognitive deficits including aphasia, alexia, apraxia and some perceptual disorders. Here, we present of the patient with left angular and supramarginal gyrus infarction affecting the parietal lobe. In addition to the symptoms mentioned above, the patient had alexia and anomic aphasia as well. We discussed the clinic appearance and reviewed the current literature.

Selective impairment of On-reading (Chinese-style pronunciation) in alexia with agraphia for kanji due to subcortical hemorrhage in the left posterior middle temporal gyrus.

We report a patient with alexia with agraphia for kanji after hemorrhage in the left posterior middle temporal gyrus. The results of single-character kanji reading and two-character on- (Chinese-style pronunciation), kun- (native Japanese pronunciation), and Jukujikun (irregular kun-) reading word tests revealed that the patient could not read kanji characters with on-reading but read the characters with kun-reading. We consider that this on-reading alexia was caused by disconnection between the posterior inferior temporal cortex (orthographic lexicon) and the posterior superior temporal gyrus (phonological lexicon), and preserved kun- and Jukujikun-reading was realized by bypassing the orthography-to-phonology route by the semantic route.

Proactive interference apraxic agraphia: a writing and drawing disorder associated with corticobasal syndrome.

Proactive interference is when a previously performed task impairs performance on a current task. It is often associated with memory tasks and has not been reported to interfere with writing or drawing. We evaluated a left-handed man diagnosed with corticobasal syndrome who had a two-year history of progressive agraphia. On the sentence writing and clock drawing tasks, he initially wrote letters and numbers correctly but revealed an increase of movement errors as the tasks progressed. We propose the term "proactive interference apraxic agraphia" for this novel disorder. Prefrontal dysfunction may cause an impairment in disengaging from previously activated motor programs.

Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality.

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.