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1

Rola metali w rozwoju choroby Alzheimera i Parkinsona

Żygowska Justyna, Szymańska Aneta

Wiadomości Chemiczne

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2022

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[Z] 76, 1-2

1--25

EN

Neurodegenerative diseases are the consequence of progressive brain degeneration caused by the death of nerve cells. Many factors that influence the neurodegeneration development are still not fully known. A lot of studies indicate the contribution of metal ions in this process. Copper, zinc, and iron are trace elements essential for proper functioning of the body. They are part of many enzymes participating in the transmission of the nerve signals, electrons transport, neurotransmitters and nucleic acids synthesis, and oxygen storage. Disorder of metals homeostasis leads to the development of severe diseases and nervous system degenerations. An excess of copper and iron ions causes a significant increase in cellular oxidative stress. Metals catalyze the reactions of free radicals formation that destroy proteins, lipids, and nucleic acids. High concentration of copper and iron ions were found in the deposits of amyloidogenic proteins. Amyloid β (Alzheimer disease) and α synuclein (Parkinson disease) have ions binding chain structures. The metal-protein interaction increases oligomerization speed in vitro. A lot of evidence suggests that the disorder of Cu, Zn and Fe homeostasis accelerates the progress of brain neurodegeneration. Human organism contains many metals, which are not needed for the proper functioning of the body, e.g. aluminum. Al binds to nucleic acids causing an increase in cellular oxidative stress and initiating proteins oligomerization. The presence of aluminum is also considered to be disadvantageous for the nervous system. The lack of medicines for neurodegenerative diseases forces us to search for new therapies. The development of degenerations could be slowed down by chelators of toxic metals, but first, these diseases must be better understood. Adverse effects of high concentration of metal ions on brain functioning are not fully known. This knowledge is necessary to find effective drugs.

2

An investigation about the relationship between dysarthria level of speech and the neurological state of Parkinson’s patients

Karan Biswajit, Sekhar Sahu Sitanshu, Orozco-Arroyave Juan Rafael

Biocybernetics and Biomedical Engineering

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2022

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Vol. 42, no. 2

710--726

EN

Parkinson’s disease (PD) is the most common neurological disorder that typically affects elderly people. In the earlier stage of disease, it has been seen that 90% of the patients develop voice disorders namely hypokinetic dysarthria. As time passes, the severity of PD increases, and patients have difficulty performing different speech tasks. During the progression of the disease, due to less control of articulatory organs such as the tongue, jaw, and lips, the quality of speech signals deteriorates. Periodic medical evaluations are very important for PD patients; however, having access to a medical appointment with a neurologist is a privilege in most countries. Considering that the speech recording process is inexpensive and very easy to do, we want to explore in this paper the suitability of mapping information of the dysarthria level into the neurological state of patients and vice versa. Three levels of severity are considered in a multiclass framework using time-frequency (TF) features and random-forest along with an Error-Correcting Output Code (ECOC) approach. The multiclass classification task based on dysarthria level is performed using the TF features with words and diadochokinetic (DDK) speech tasks. The developed model shows an unweighted average recall (UAR) of 68.49% with the DDK task /pakata/ based on m-FDA level, and 48.8% with the word /petaka/ based on the UPDRS level using the Random Forest classifier. With the aim, to evaluate the neurological states using the dysarthria level, the developed models are used to predict the MDS-UPDRS-III level of patients. The highest matching accuracy of 32% with the word /petaka/ is achieved. Similarly, the multiclass classification framework based on MDS-UPDRS-III is applied to predict the dysarthria level of patients. In this case, the highest matching accuracy of 18% was obtained with the DDK tasks /pataka/.

3

Parkinson disease prediction using intrinsic mode function based features from speech signal

Karan Biswajit, Sahu Sitanshu Sekhar, Mahto Kartik

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

249--264

EN

Parkinson's disease (PD) is a progressive neurological disorder prevalent in old age. Past studies have shown that speech can be used as an early marker for identification of PD. It affects a number of speech components such as phonation, speech intensity, articulation, and respiration, which alters the speech intelligibility. Speech feature extraction and classification always have been challenging tasks due to the existence of non-stationary and discontinuity in the speech signal. In this study, empirical mode decomposition (EMD) based features are demonstrated to capture the speech characteristics. A new feature, intrinsic mode function cepstral coefficient (IMFCC) is proposed to efficiently represent the characteristics of Parkinson speech. The performances of proposed features are assessed with two different datasets: dataset-1 and dataset-2 each having 20 normal and 25 Parkinson affected peoples. From the results, it is demonstrated that the proposed intrinsic mode function cepstral coefficient feature provides superior classification accuracy in both data-sets. There is a significant increase of 10–20% in accuracy compared to the standard acoustic and Mel-frequency cepstral coefficient (MFCC) features.

4

Automatic Parkinson disease detection at early stages as a pre-diagnosis tool by using classifiers and a small set of vocal features

Solana-Lavalle Gabriel, Galán-Hernández Juan-Carlos, Rosas-Romero Roberto

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

505--516

EN

Recent research on Parkinson disease (PD) detection has shown that vocal disorders are linked to symptoms in 90% of the PD patients at early stages. Thus, there is an interest in applying vocal features to the computer-assisted diagnosis and remote monitoring of patients with PD at early stages. The contribution of this research is an increase of accuracy and a reduction of the number of selected vocal features in PD detection while using the newest and largest public dataset available. Whereas the number of features in this public dataset is 754, the number of selected features for classification ranges from 8 to 20 after using Wrappers feature subset selection. Four classifiers (k nearest neighbor, multi-layer perceptron, support vector machine and random forest) are applied to vocal-based PD detection. The proposed approach shows an accuracy of 94.7%, sensitivity of 98.4%, specificity of 92.68% and precision of 97.22%. The best resulting accuracy is obtained by using a support vector machine and it is higher than the one, which was reported on the first work to use the same dataset. In addition, the corresponding computational complexity is further reduced by selecting no more than 20 features.

5

Multidimensional neo-fuzzy-neuron for solving medical diagnostics tasks in online-mode

Mahmoud S. M. K., Perova I., Pliss I.

Journal of Applied Computer Science

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2017

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Vol. 25, nr 1

39--48

EN

In this paper neuro-fuzzy approach for medical data processing is considered. Special capacities for methods and systems of Computational Intelligence were introduced for Medical Data Mining tasks, like transparency and interpretability of obtained results, ability to classify nonconvex and overlapped classes that correspond to various diagnoses, necessity to process data in online mode and so on. Architecture based on the multidimensional neo-fuzzy-neuron was designed for situation of many diagnoses. For multidimensional neo-fuzzy-neuron adaptive learning algorithms that are a modification of Widrow-Hoff algorithm were introduced. This system was approbate on nervous system diseases data set from University of California Irvine (UCI) Repository and show high level of classification results.

6

Implementacja systemu diagnostyki choroby Parkinsona

Dobrowiecka B., Kornacki W., Kozłowski T., Mocny W., Pikiel M., Zając J.

Elektronika : konstrukcje, technologie, zastosowania

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2013

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Vol. 54, nr 4

72-77

PL

Celem artykułu jest przedstawienie kompleksowego systemu diagnostycznego choroby Parkinsona, zbudowanego na bazie opracowanego rigidometru stacjonarnego i mobilnego oraz systemu do badania stabilności postawy pacjenta (posturografu), zorientowanego na ocenę efektu sztywności kończyn i zaburzeń postawy. Szczególną uwagę zwrócono na implementację oprogramowania wraz z bazą danych.

EN

The aim of this article is to present the complex diagnostic system for Parkinson disease with the use of newly designed stationery and mobile rigidometer as well as system for patient posture stability assessment (posturograph), oriented on limb rigidity and posture instability assessment. The particular emphasis was put on software and data base implementation.

7

Oprogramowanie przenośnego systemu diagnostycznego pacjentów z chorobą Parkinsona

Dobrowiecka B., Kornacki W., Pikiel M., Zając J.

Elektronika : konstrukcje, technologie, zastosowania

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2010

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Vol. 51, nr 7

122-126

PL

W artykule przedstawiono oprogramowanie przenośnego systemu diagnostycznego pacjentów z chorobą Parkinsona ze szczególnym uwzględnieniem modułu interpretacji zaimplementowanego w stacji roboczej z prezentacją wyników badań oraz ich interpretacji.

EN

This paper presents the software of the portable diagnostic system for the Parkinson's disease diagnosis with particular emphasis on software interpretation modules built into working station as well as examinations results presentation and theirs interpretation.

8

Prototyp doświadczalny zintegrowanego systemu monitorującego na potrzeby diagnostyki pacjentów z chorobą Parkinsona

Dobrowiecka B., Kornacki W., Pikiel M., Zając J.

Elektronika : konstrukcje, technologie, zastosowania

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2009

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Vol. 50, nr 7

134-137

PL

W artykule przedstawiono prototypowy doświadczalny system monitorujący na potrzeby diagnostyki pacjentów z chorobą Parkinsona, ze szczególnym uwzględnieniem systemu oprogramowania zawierającym moduły oprogramowania wbudowanego w rejestrator tremorometryczny, oprogramowania serwera składającego się z modułu komunikacyjnego i bazy danych oraz oprogramowania stacji roboczej składającego się z interfejsu użytkownika i modułów przetwarzania danych osobowych i medycznych oraz modułów przetwarzania i analizy cyfrowych sygnałów drżeń.

EN

This paper presents the prototype of integrated monitoring system for the Parkinsons disease diagnosis with particular emphasis on soft-ware system with software modules built into tremorometer, server software with communication modules and data base as well as working station software with user interface and personal and medical data processing together with tremor digital signal processing and analysis modules.

9

Modelowanie i symulacja hipokinetycznymi, patologicznymi, minimalnymi drżeniami w chorobie Parkinsona (PD)

Trąbka J., Wójcik M.

Engineering of Biomaterials

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2007

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Vol. 10, no. 69-72

45-52

PL

Problematyka patofizjologii chorób neurologicznych, do których zaliczamy chorobę Alzheimera (AD), Parkinsona (PD), apopleksję, epilepsję stanowi ciągle aktualne wyzwanie dla badaczy, ponieważ mimo ogromnego postępu w rozwoju szeroko rozumianej medycyny i wyposażenia jej w nowoczesne narzędzia diagnostyczne choroby istnieją i zbierają swoje żniwa. Nadal nie znaleziono skutecznej formy walki z nimi. Istnieje uzasadniony pogląd, że choroby występują najczęściej samoistnie lub nie mają znanych przyczyn, co prowadzi do podejmowania badań w różnych kierunkach. Znając jednak objawy choroby podejmowane są próby leczenia farmakologicznego jak i operacyjnego. W pracy przede wszystkim skupiono się na problematyce choroby Parkinsona. We wstępie przedstawiono bardzo istotny teleologiczny pogląd naturalności ruchu ujawniający w pełni problematykę ruchu zarówno u osób zdrowych jak i chorych. Analiza ruchów dowolnych u ludzi zdrowych i chorych pozwala prześledzić różnice występujące w czynnościach zespołu hipokinetycznego, efektem czego może być inne podejście do patologii choroby i propozycja nowego rozwiązania praktycznego, pozwalającego choremu uzyskać lepszy komfort życia z przypadłościami choroby występującymi podczas wykonywania ruchów dowolnych. Analiza literaturowa prezentowanych wyników badań kinematycznych i dynamicznych ruchów dowolnych na wyselekcjonowanych różnych grupach z populacji zarówno pacjentów o różnym stopniu zaawansowania choroby jak i osób zdrowych w różnym wieku ujawniła charakterystyczne trajektorie ruchu kończyn górnych, który można opisać za pomocą różnych modeli matematycznych. W pracy zaprezentowano oryginalne, teoretyczne podejście do zagadnienia, które polega na analizie matematycznej układu mechanicznego składającego się z elementu sprężystego i tłumiącego jak również praktyczny sposób oparty na pomyśle konstrukcji urządzenia wspomagającego ruchy dowolne poprzez wytłumienie lub też eliminację charakterystycznego drżenia kończyn oraz dodatkowego elementu przyspieszającego zapoczątkowanie ruchu dowolnego. Urządzenie składać się będzie z pewnej konstrukcji antropogenicznej wykonanej z lekkich i wytrzymałych kompozytów polimerowych o konstrukcji panelowej, zawierających włókna węglowe o właściwościach magnetycznych i przewodzących. Konstrukcja panelowa pozwoli na wypełnienie jej przestrzeni aktywnym, ruchomym medium (również kontinuum) sterowanym za pomocą sprężysto-elastycznych układów, pozwalających zminimalizować lub wyeliminować patologiczne ruchy choroby Parkinsona.

EN

Pathophysiology of neurological diseases (ND): Alzheimer's disease (AD), Parkinson's disease (PD), stroke, epilepsy still constitute an actual challenge for medicine researches because despite of the great progress of technical facilities in medicine and diagnostic development diseases exist and toll of human life. Still did not find an effective form in struggle with these ND. It is reasonable notion that ND is usually generated autonomously, i.e. unknown reasons. It leads to undertaking of the various investigations. Pharmacological as well as surgery treatments are undertaken knowing symptoms of ND. The problem of PD was basically discussed and teleological view of the nature of movement was presented. Analysis of the voluntary movements of healthy as well as sick peoples permits to investigate the differences existing in the hypokinetic syndrome resulting in the proposition of the practical solution of the problem. Analysis of results of kinematics and dynamic voluntary movements on the selective group of patients with different stage of the disease advanced as well as healthy peoples reveal the characteristic movements trajectories of upper limbs that were described with the aim of the elaborated mathematical model. A new approach has been proposed and was shown in this paper for solution of the problem. There is a construction of the new device helping in voluntary movements by restrain or elimination of the characteristic tremor of the upper limbs typical ion PD. Usage of an additional elements can optionally accelerates for helping the first star of the kinetic tremor. Device is consisted from antropogenic panel construction made from light and tough carbon fibres with magnetic and conductive properties inserted into matrix base polymer composites. Panel construction permits to fill space by active motion medium. The springy-elastic systems were used for steering purposes. Construction allows for minimizing or even elimination of pathological movement of the PD.

10

The method of neuron weight vector initial values selection in Kohonen network

Chandzlik S.

Journal of Medical Informatics & Technologies

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2006

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Vol. 10

189--197

EN

Diagnosing of morbid conditions by means of automatic tools supported by computers is a significant and often used element in modern medicine. Some examples of these tools are automatic conclusion-making units of Parotec System for Windows (PSW). In the initial period of PSW system implementation, the units were used for recognition of orthopaedic diseases on the basis of the patient's walk and posture [15,17]. Subsequently, many additional options have been implemented, which have been used for purposes of diagnosing neurological diseases [1,2,3,9,12]. During automatic classification of diseases the additional units use elements of neural networks. The vectors based on normalised diagnostic measures [3] are inputs of the units. The measurements describe a patient's posture condition, his walk and overloads occurring on his feet. The Counter-Propagation (CP), two-layer network has been used in one of the automatic conclusion-making units. During CP network activity, we can see not only supervised but unsupervised learning processes as well. This is a characteristic feature of the CP network. The initial steps of the CP network learning process are very important, because the success of the network training process depends on them to a great extent. Therefore, a new method of weight vector initial values selection was proposed. The efficiency of the method was compared with classical methods. The results were very satisfactory. Owing to the proposed method, the time of the network training process as well as the mean-square error and the classification error was reduced. The research has been carried out using clinical cases of some neurological diseases: Parkinson's Disease, left-lateral hemiparesis and right-lateral hemiparesis after ischemic stroke. The measurements, which were made on a control group of patients without any neurological diseases, were the reference for these diagnostic classes.

11

Automatyczna ocena zaburzeń emisji głosu będących wynikiem procesów neurodegeneracyjnych w oparciu o analizę wyizolowanych głosek

Orzechowski T., Chmurzyńska K., Radkowski P.

Automatyka / Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie

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2006

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T. 10, z. 3

91-97

PL

Prezentowane wyniki stanowią początek badań nad automatyczną klasyfikacją głosu. W niniejszej pracy zarysowano teoretyczne podstawy fizjologiczne głosu, patologiczne zmiany w mowie powodowane dyzartrią, następnie scharakteryzowano dobór materiału lingwistycznego pod względem miejsca i sposobu artykulacji w systemie fonetycznym języka polskiego. Kolejne miejsce w pracy zajmuje opis rejestracji i wstępnej analizy głosu badanych (zmiany w realizacji głosek, natężenie głosek wymawianych wielokrotnie w izolacji, analiza widma dźwięków ciągłych). Zjawiska słyszane w badaniu subiektywnym patologa mowy, bądź neurologa zostały potwierdzone precyzyjnym badaniem obiektywnym. Uzyskane parametry pozwalają na sparametryzowanie wyników badań, umożliwiające kompleksową klasyfikację. Pozwoli to również na dokładną ocenę progresji choroby, niemożliwą w klasycznym badaniu subiektywnym.

EN

This paper presents results of preliminary research of voice pathological changes caused by dysarthria. Computer analysis of voice may lead to identification of parameters correlated with neurological diseases. The selection of linguistic material was characterized according to the place and manner of articulation in the phonetic system of Polish. Results of clinical examination allowed to determine simple markers of neurodegenerative diseases, which will serve as a basis for construction of objective examination model.

12

The diseases classification method on gait abnormalities characteristic contributions

Chandzlik S., Piecha J.

Journal of Medical Informatics & Technologies

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2005

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Vol. 9

187--194

EN

Present medicine uses computers in various applications, especially in a field of a diseases level classification and diagnosis. In many cases an automatic conclusion making units are the main goal of the computer systems usage. The software units are developed for the diseases classification or for monitoring of the disease medical treatment. An example application was described in this paper. It concerns a gait abnormalities level analysis that is described by a data records gathered by insoles of Parotec System for Windows (PSW) [17,18]. The PSW software package is used for visualisation of the gait characteristic static and dynamic characteristic features. In the authors' works many additional data components were distinguished. The field of the applications is located within the neurological gait characteristics also the source applications concern orthopaedics [16,18]. Careful analysis of the data provided the developers with new areas the PSW applications [4,11,13]. For conclusion making units the artificial networks theory was implemented [2,4,11,13]. For more effective training of the neural networks specific characteristic measures were introduced [4,5]. They allow controlling the training process more precisely, avoiding mistakes in current records classification.

13

The gait abnormalities review of several neurological diseases

Zbrojkiewicz J. S., Piecha J., Wajgt A.

Journal of Medical Informatics & Technologies

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2004

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Vol. 8

MM83--94

EN

This study was based on observations of 117 patients suffering from motor disturbances. Among them 42 cases with hemiparetic syndrome, mostly after cerebral stroke, 52 cases affected by acute sciatic neuralgia, and 23 patients with recognition of Parkinson - disease symptoms. To the control group 16 healthy adults was selected from our medical staff. All subjects were examined using pedobarographic equipment - Parotec System for Windows (PSW) [1]. Based on these observations several pattern solutions have been introduced. They concern gait disturbances in three distinguished neurological diseases. These findings extracted a new data from the PSW records and options and new diagnostic techniques based on the gait characteristics observation.

14

Bezinwazyjne metody pomiarowe drżenia kończyn górnych występującego przy chorobie Parkinsona

Michałek M.

Automatyka / Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie

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2003

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T. 7, z. 3

361-369

PL

Praca opisuje wybrane metody pomiarowe drżenia kończyn górnych, które występują przy chorobie Parkinsona. Na wstępie zamieszczono krótką genezę tej choroby i opisano jej cechy charakterystyczne. Podano również ogólne wiadomości odnośnie klasyfikacji drżenia. Artykuł zawiera opis podstawowych testów, które są wykorzystywane przez lekarzy do analizy i wstępnej oceny zaawansowania drżenia ze względu na amplitudę i częstotliwość. W pracy zaproponowano nową metodę pomiarową drżenia w przestrzeni jako alternatywę dla rozwiązań do tej pory stosowanych. Nowa metoda nie wymaga od pacjenta wykonywania żadnych dodatkowych czynności i jest przeznaczona głównie do pomiaru drżenia spoczynkowego, które jest cechą choroby Parkinsona. Inne metody, wykorzystujące na przykład tablety cyfrowe, wymagają odwzorowania spirali Archimedesa.

EN

This paper describes several measuring methods of tremor of upper limbs, which takes place in Parkinson's disease. At first the brief information about history, genesis and characteristic of that disease and generally about tremor is presented. The article contains description of basic tests, which are used by doctors to analyze of the stage of tremor with regard to amplitude and frequency. New measuring method of tremor proposed in this paper is an alternative for solutions applied to this time. This method does not require from patient any additional action to be executed. The proposed method is designed to measure mainly resting tremor, which it is the feature of Parkinson's disease. Different methods, using for example digital tablets, require utilizing the model of the Archimedes spiral.