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LSTM-Based Autoencoders in Online Handwriting Data Augmentation and Preprocessing
Gavenciak, Michal
On-line handwriting analysis is a research field that is among others used in assessment of handwriting difficulties (HD), which can be manifestations of degenerative brain diseases such as Parkinson’s disease in the elderly, or developmental dysgraphia in children. Using advanced modelling approaches or artificial intelligence is often difficult because of the limited data availability in both demographic cohorts. In this article, a data processing approach, using LSTM-based autoencoders, is described as a way of augmenting the database with semisynthetic data or preprocessing the data to improve the performance of feature-based classification. The proposed method has led to a 3 percentage point increase in classification accuracy when compared to baseline. While the improvement is marginal, it highlights another possible area of research to improve the efficacy of automated HD assessment.
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Semi-automatic computerized system for the segmentation of online handwriting
Gavenčiak, Michal ; Mekyska, Jiří (referee) ; Zvončák, Vojtěch (advisor)
The prevalence of developmental dysgraphia among school children is between 10-30%, yet in Czech Republic, there is no objective method to diagnose it or determine its severity. Past studies have shown the possibility of automatic diagnosis using digital data gathered using a digitizing tablet and a stylus. Data gathered within an ongoing study contain information on position, time stamp, tilt, pressure and azimuth of the stylus. These data are, however, unsuitable for further analysis due unspecified number of exercises contained in one SVC file. Within this thesis the data is analysed and a program, which is able to segment these data into units of exercises and display the processed data on the screen, is designed and implemented.
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Research of new online handwriting features in children with graphomotor difficulties
Gavenčiak, Michal ; Mekyska, Jiří (referee) ; Zvončák, Vojtěch (advisor)
In the Czech Republic, there is currently no objective method to diagnose graphomotor difficulties in children. Ongoing research uses modern digitizers to capture the hand-writing process and quantify its parameters. The first goal of this thesis is to develop software tools to faciliate work with the collected data, such as database validation and writing exercise rating, done by specialists. Another goal of this thesis is to design new on-line handwriting parameters which are then to be analysed on a cohort of school children from 2nd to 4th class of primary school (n=239). The implementation of two desktop programs on the .NET platform is described, among three new quantifying parameters based on the principles of isochrony, two-dimensional cross-correlation, and geometrical centroid. All three parameters show significant correlation (r = [0,2; 0,3])with the HPSQ-C rating in 2nd- and 4th-graders and correlation (𝜌= [0,2; 0,5]) with specialist’s subjective scores in all children from the cohort. The analysis suggests children with graphomotor difficulties struggle with regulating handwriting speed and working memory.
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Application for mastering of handwriting
Gradoš, Matej ; Gavenčiak, Michal (referee) ; Mekyska, Jiří (advisor)
Writing is an activity that accompanies us almost every day from a very young age. Children begin to familiarize themselves with the proper grip of a writing tool as early as preschool, primarily through activities related to drawing. Upon entering the early grades of elementary school, children start writing and practice it in special notebooks called „písanka“. Mastering this skill requires a strong connection between fine motor skills and perceptual abilities. The aim of this bachelor’s thesis is to transfer writing practice to an online environment and design an application for Apple iPad tablets with the Apple Pencil stylus, which enables children to engage in self-study through interactive means, ranging from tracing curves and basic letter elements to writing complete words. By creating a database of exercises, we can supplement traditional printed exercise book and thus monitor not only the result of handwriting but also its entire progression, capturing data on pen movement, tilt, and pressure The data obtained this way serves as an excellent tool for improvement and gaining confidence in writing.
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Research of new online handwriting features in children with graphomotor difficulties
Gavenčiak, Michal ; Mekyska, Jiří (referee) ; Zvončák, Vojtěch (advisor)
In the Czech Republic, there is currently no objective method to diagnose graphomotor difficulties in children. Ongoing research uses modern digitizers to capture the hand-writing process and quantify its parameters. The first goal of this thesis is to develop software tools to faciliate work with the collected data, such as database validation and writing exercise rating, done by specialists. Another goal of this thesis is to design new on-line handwriting parameters which are then to be analysed on a cohort of school children from 2nd to 4th class of primary school (n=239). The implementation of two desktop programs on the .NET platform is described, among three new quantifying parameters based on the principles of isochrony, two-dimensional cross-correlation, and geometrical centroid. All three parameters show significant correlation (r = [0,2; 0,3])with the HPSQ-C rating in 2nd- and 4th-graders and correlation (𝜌= [0,2; 0,5]) with specialist’s subjective scores in all children from the cohort. The analysis suggests children with graphomotor difficulties struggle with regulating handwriting speed and working memory.
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Semi-Automatic Segmentation Of On-Line Handwriting
Gavenčiak, Michal
This paper deals with the automation of digital trace data segmentation. The data are obtained from a digitizing tablet and are then subjected to handwriting analysis, providing quantified information about a person’s handwriting, which might help in the diagnosis of handwriting difficulties. In order to successfully analyze the data, they must be segmented by individual handwriting exercise. Implementation of a python-based program with a GUI is described along with its basic functionality.
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Semi-automatic computerized system for the segmentation of online handwriting
Gavenčiak, Michal ; Mekyska, Jiří (referee) ; Zvončák, Vojtěch (advisor)
The prevalence of developmental dysgraphia among school children is between 10-30%, yet in Czech Republic, there is no objective method to diagnose it or determine its severity. Past studies have shown the possibility of automatic diagnosis using digital data gathered using a digitizing tablet and a stylus. Data gathered within an ongoing study contain information on position, time stamp, tilt, pressure and azimuth of the stylus. These data are, however, unsuitable for further analysis due unspecified number of exercises contained in one SVC file. Within this thesis the data is analysed and a program, which is able to segment these data into units of exercises and display the processed data on the screen, is designed and implemented.
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