REVIEW OF MATHEMATICAL MODELS OF ABNORMAL NEUROLOGICAL MOVEMENTS WITH TAKING INTO ACCOUNT THE COGNITIVE FEEDBACK-EFFECTS OF NEURONODES OF THE CEREBRAL CORTE
DOI:
https://doi.org/10.32782/KNTU2618-0340/2020.3.2-2.22Keywords:
tremor; cerebral cortex (CC); electroencefalogram (EEG); abnormal neurological movement (ANM); feedback-communication; feedback-model; feedbackinteraction; incoherent functionality; tremor-object (T-object); Archimedes spiral; electroencephalograph; 3D microaccelerometer; Fourier transformAbstract
With the use of modern computer technology, it is possible to provide a digital, systematic and automated approach to health monitoring. In particular, this article provides an example of the application of these technologies to the diagnosis of tremor. Any deviation from the norm indicates that a person may have fatigue, an overly excited emotional state, or pathology. The cause of pathology can be disorders in the cerebral cortex or directly on the periphery of the human body (limbs, eyes). The most advanced technologies today include recording human movements in space using high-sensitivity speed cameras and a method of identifying tremor on the plane by recognizing the Archimedes spiral pattern, which can be performed on a pen graphics tablet. The hardware solution is based on a tablet with an Archimedes spiral pattern, a graphic digital pen device with a built-in 3D microaccelerometer and an electroencephalograph. By using the built-in module of the 3D microaccelerometer in the digital pen of the graphics tablet, the condition of maintaining the existing satisfactory accuracy of measurements with the additional ability to control the separation of the pen from the surface is provided. Important elements of development are algorithms for obtaining the values of the simulated system parameters, the possibility of visual representation of the obtained results, the need for dynamic setting of system parameters. All this allows you to more clearly present the results and promotes the targeted use of technology. A good solution and a positive element of this development is the implementation in the form of a separate module, with the ability to constantly update methods and maintain the relevance of research. The implementation of software in this way helps to increase the adaptability, ease of use in various systems in the course of research. Mathematical methods, namely computational algorithms, are implemented as a set of classes with methods that model behavior. Software modules, classes, and their interaction are implemented in the form of a single module-library, which will allow flexible use of the method of analysis of input data in various applications and programs.
References
Rajaraman V., Jack D., Adamovich S. V., Hening W., Sage J., Poizner H. A Novel Quantitative Method for 3D Measurement of Parkinsonian Tremor. Clinical Neurophysiology. 2000. Vol. 11. Issue 2. P. 187−369.
Haubenberger D., Kalowitz D., Nahab F. B, Toro C., Ippolito D., Luckenbaugh D. A., Wittevrongel L., Hallett M. Validation of Digital Spiral Analysis as Outcome Parameter for Clinical Trials in Essential Tremor. Movement Disorders. 2011. Vol. 26. Issue 11. P. 2073−2080.
Legrand A. P., Rivals I., Richard A., Apartis E., Roze E., Vidailhet M., Meunier S., Hainque E. New Insight in Spiral Drawing Analysis Methods – Application to Action Tremor Quantification. Clinical Neurophysiology. 2017. Vol. 128. Issue 10. P. 1823–1834.
Wang J.-S., Chuang F.-C. An Accelerometer-Based Digital Pen with a Trajectory Recognition Algorithm for Handwritten Digit and Gesture Recognition. IEEE Transactions on Industrial Electronics. 2012. Vol. 59. Issue 7. P. 2998−3007.DOI: 10.1109/TIE.2011.2167895.
Louis E. D., Gillman A., Böschung S., Hess C. W., Yu Q., Pullman S. L. High width Variability during Spiral Drawing: Further Evidence of Cerebellar Dysfunction in Essential Tremor. Cerebellum. 2012. Vol. 11. Issue 4. P. 872−879. DOI: 10.1007/s12311-011-0352-4.
Sergienko I. V., Deineka V. S. Optimal Control of Distributed Systems withConjugation Conditions. New York: Kluwer Aсademic Publishers, 2005. 383 p.
Lions J.-L. Perturbations Singulières dans les Problèmes aux Limites et en Contrôle Optimal. New York: Springer, 2008. 645 p.
Sergienko. I. V., Petryk M. R, Leclerc S., Fraissard J. Highly Efficient Methods of the Identification of Competitive Diffusion Parameters in Inhomogeneous Media of Nanoporous Particles. Cybernetics and Systems Analysis. 2015. Vol. 51. Issue 4. P. 529−546. DOI: 10.1007/s10559-015-9744-7.
Ленюк М. П., Петрик М. Р. Методи інтегральних перетворень Фур’є-Бесселя в задачах математичного моделювання масопереносу в неоднорідних середовищах. Київ: Наукова думка, 2000. 372 c.
Xіміч О. М., Петрик М. Р., Михалик Д. М., Бойко І. В., Попов О. В., Сидорук В. А. Методи математичного моделювання та ідентифікації складних процесів і систем на основі висопродуктивних обчислень (нейро- та нанопористі кібер-фізичні системи із зворотніми зв’язками, моделі з даними розрідженої структури, паралельні обчислення). Київ: Національна Академія наук України, Інститут кібернетики імені В. В. Глушкова, 2019. 180 c.
Mykhalyk D., Mudryk I., Hoi A., Petryk M. Modern Hardware and Software Solution for Identification of Abnormal Neurological Movements of Patients with Essential Tremor. Proceeding of the 9th International Conference on Advanced Computer Information Technologies (Czech Republic, Budejovice, June 5-7, 2019). 2019. P. 183−186.
