Advanced Parameterisation of Online Handwriting in Writers with Graphomotor Disabilities

Grafomotorick© obt­e (GD) vraznÄ ovlivuj­ kvalitu ivota koln­m vÄkem poÄ­naj­c, kde se vyv­jej­ grafomotorick© schopnosti, a do dchodov©ho vÄku. VÄasn diagnza tÄchto obt­­ a terapeutick zsah maj­ velk vznam k jejich zlepen­. Vzhledem k tomu, e GD souvis­ z v­cermi symptomy v oblasti kinematiky, zkladn­ kinematick© parametry jako rychlost, zrychlen­ a vih prokzaly efektivn­ kvantizaci tÄchto symptom. Objektivn­ vpoÄetn­ syst©m podpory rozhodovn­ pro identifikaci a vyeten­ GD vak nen­ dostupn. A proto je hlavn­m c­lem m© disertaÄn­ prce vzkum pokroÄil© metody parametrizace online p­sma pro analzu GD se speciln­m zamÄen­m na vyuit­ metod zlomkov©ho kalkulu. Tato prce je prvn­, kter experimentuje s vyuit­m derivac­ neceloÄ­seln©ho du (FD) pro analzu GD pomoc­ online p­sma z­skan©ho od pacient s Parkinsonovou nemoc­ a u dÄt­ koln­ho vÄku. Byla navrena a evaluovna nov metoda parametrizace online p­sma zaloena na FD vyuit­m Grnwald-Letnikova p­stupu. Bylo dokzno, e navren metoda vznamnÄ zlepuje diskriminaÄn­ s­lu a deskriptivn­ schopnosti v oblasti Parkinsonick© dysgrafie. StejnÄ tak metoda pozitivnÄ ovlivnila i nejmodernÄj­ techniky v oblasti analzy GD u dÄt­ koln­ho vÄku. Vyvinut parametrizace byla optimalizovna s ohledem na vpoÄetn­ nroÄnost (a o 80 %) a tak© na vyladÄn­ du FD. Ke konci prce byly porovnny v­cer© p­stupy vpoÄtu FD, jmenovitÄ Riemann-Liouvillv, Caputv spoleÄnÄ z Grnwald-Letnikovm p­stupem za Äelem identifikace tÄch nejvhodnÄj­ch pro jednotliv© oblasti analzy GD.Graphomotor disabilities (GD) significantly affect the quality of life beginning from the school-age, when the graphomotor skills are developed, until the elderly age. The timely diagnosis of these difficulties and therapeutic interventions are of great importance. As GD are associated with several symptoms in the field of kinematics, the basic kinematic features such as velocity, acceleration, and jerk were proved to effectively quantify these symptoms. Nevertheless, an objective computerized decision support system for the identification and assessment of GD is still missing. Therefore, the main objective of my dissertation is the research of an advanced online handwriting parametrization utilized in the field of GD analysis, with a special focus on methods based on fractional calculus. This work is the first to experiment with fractional-order derivatives (FD) in the GD analysis by online handwriting of Parkinsonâs disease (PD) patients and school-age children. A new online handwriting parametrization technique based on the Grnwald-Letnikov approach of FD has been proposed and evaluated. In the field of PD dysgraphia, a significant improvement in the discrimination power and descriptive abilities was proven. Similarly, the proposed methodology improved current state-of-the-art techniques of GD analysis in school-aged children. The newly designed parametrization has been optimized in the scope of the computational performance (up to 80 %) as well as in FD order fine-tuning. Finally, various FD-approaches were compared, namely Riemann-Liouville, Caputoâs, together with Grnwald-Letnikov approximation to identify the most suitable approach for particular areas of GD analysis.

Recent Advances in Motion Analysis

The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application

Dordt College 2003-2004 Catalog

Academic Catalog for 2003-04https://digitalcollections.dordt.edu/academic_catalogs/1012/thumbnail.jp

Dordt College 2003-2004 Catalog

Academic Catalog for 2003-04https://digitalcollections.dordt.edu/academic_catalogs/1012/thumbnail.jp

Dordt College 2011-12 Catalog

Academic Catalog for 2011-12https://digitalcollections.dordt.edu/academic_catalogs/1004/thumbnail.jp

2006-2007 Undergraduate Catalog

2006-2007 undergraduate catalog for Morehead State University