Advanced Parametrization of Graphomotor Difficulties in School-Aged Children

Abstract

School-aged children spend 31-60 % of their time at school performing handwriting, which is a complex perceptual-motor skill composed of a coordinated combination of fine graphomotor movements. As up to 30 % of them experience graphomotor difficulties (GD), timely diagnosis of these difficulties and therapeutic intervention are of great importance. At present, an objective, computerized decision support system for the identification and assessment of GD in school-aged children is still missing. In this study, we propose three novel advanced handwriting parametrization techniques based on modulation spectra, fractional order derivatives, and tunable Q-factor wavelet transform to improve the identification of GD using online handwriting. For this purpose, we analyzed signals acquired from 7 basic graphomotor tasks performed by 53 children attending 3rd and 4th grade at several primary schools around the Czech Republic. Combining the newly proposed features with the conventionally used ones, we were able to identify GD with 84 % accuracy. In this study, we showed that using advanced parametrization of basic graphomotor movements can be potentially used to improve our capabilities of quantifying problems with the development of legible, fast-paced handwriting, and help with the early diagnosis of handwriting difficulties frequently manifested in developmental dysgraphia.

Analysis of Various Fractional Order Derivatives Approaches in Assessment of Graphomotor Difficulties

“…Recently, the FC has been significantly examined in computer vision, particularly in image restoration, superresolution, image segmentation or motion estimation [8]. In line with this trend, in our recent research, we developed new parametrisation techniques of online handwriting (a handwritten signal with temporal information) based on the application of the fractional order derivatives (FD) [9]- [13].…”

“…Next, Mekyska et al [17] (2019) proposed a model (based on XGBoost, 76 children) and achieved 50 % sensitivity and 90 % specificity in identification of GD presence using 7 basic graphomotor elements quantified by conventional temporal, spatial, kinematic, and dynamic parameters. In 2020, Galaz et al [13] published a work dealing with advanced analysis (utilising modulation spectra, fractional order derivatives, and tunable-Q wavelet transform) of graphomotor elements in 53 children attending 3rd and 4th grade of elementary schools. Employing random forests they reached 83 % sensitivity and 81 % specificity.…”

“…Considering the success of utilizing the FD (Grünwald-Letnikov approach) in Parkinson's disease dysgraphia analysis in our previous works [9]- [12], and in the assessment of GD in school-aged children [13], [28], this study, as a next logical step, has the following aims:…”

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

“…More recently, a study used the same kind of approach, but applied it to drawings instead of writing, for the detection of graphomotor difficulties [21]. They recorded drawings of graphomotor tasks and used a machine-learning model to determine the classification.…”

On Systematic Design of Fractional-Order Element Series

“…In fractional calculus [ 1 , 2 , 3 , 4 , 5 ], generalizing derivatives with integer order to derivatives with non-integer or fractional order, has tremendously gained attention as it is applied in many and various engineering and research disciplines and areas, spanning biology [ 6 , 7 , 8 , 9 ], food [ 10 , 11 , 12 ], cybersecurity [ 13 , 14 ], modeling and control [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ], signal processing [ 22 , 23 , 24 ], electrical engineering [ 25 , 26 , 27 , 28 , 29 , 30 ], and other. The reason for the increased interest in fractional-order calculus and system design may be seen in the fact that the presence of fractional order represents another degree of freedom to mathematically describe the behavior of a function block.…”