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Tytuł:
Assessment of the quality of life in Moroccan Parkinson’s patients
Autorzy:
Ahmadou, Taher Moussa
Hanae, Benjebara
Ghita, Aboulem
Moussa, Toudou Daouda
Camara, Diankanagbe
Mariam, Jilla
Naima, Chtaou
Faouzi, Belahsen Mohammed
Touhami Ahami, Ahmed Omar
Powiązania:
https://bibliotekanauki.pl/articles/2106010.pdf
Data publikacji:
2020-03-10
Wydawca:
Fundacja Edukacji Medycznej, Promocji Zdrowia, Sztuki i Kultury Ars Medica
Tematy:
Parkinson’s disease
Neurocognitive disorder
Quality of life
Opis:
Parkinson’s disease can lead to disability and reduce the quality of life of its patients. The purpose of this study is to evaluate the quality of life of a group of people with Parkinson’s disease. The clinical and progressive characteristics of the disease, its motor and neuropsychological impact were evaluated in each Parkinsonian subject included in the study. A quality of life assessment was performed and collected from 60 Parkinsonian patients followed and hospitalized at Hassan II University Hospital in Fez. Different instruments were used, the Hoenh and Yahr scale and the Parkinson’s disease questionnaire (PDQ-39) UPDRS engine, MMS, clinical fact sheet. According to our results, through the different tests and scale of evaluation, we observed an impaired quality of life in the areas of physical discomfort, cognitive disorder, activity of daily living, mobility, and emotional well-being, especially in patients with duration of evolution more than 5 years. There was no significant difference between the two sexes. In addition, the severity of the disease tended to give the impression of an impaired quality of life with respect to the dimensions of activities of daily living and cognition, which is relevant to improving the quality of life patient life and clinical interventions.
Źródło:
Acta Neuropsychologica; 2020, 18(1); 67-76
1730-7503
2084-4298
Pojawia się w:
Acta Neuropsychologica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
STUDY OF UNILATERAL SPATIAL NEGLECT IN PARKINSONS PATIENTS
Autorzy:
Ahmadou, Taher Moussa
Salim, EL-Mossati Mohamed
Moussa, Toudou Daouda
Ghita, Aboulem
Faouzi, Belahsen Mohammed
Touhami Ahami, Ahmed Omar
Powiązania:
https://bibliotekanauki.pl/articles/2138041.pdf
Data publikacji:
2021-06-23
Wydawca:
Fundacja Edukacji Medycznej, Promocji Zdrowia, Sztuki i Kultury Ars Medica
Tematy:
Unilateral Spatial Negligence
Parkinson's Disease
Bell's test
Opis:
In Africa, few studies are interested in unilateral spatial neglect (NSU) in Parkinson's disease. However, this syndrome is a deficit to detect, respond to or orientate towards meaningful stimuli (Heil- man, KM 1973), observable after an injury affecting the non-dominant hemisphere for language. The significant handicap it entails justifies the need for early diagnosis and care. The NSU study is mo- tivated by its link with neurocognitive phenomena that are important on the theoretical level (attention, visuospatial and perceptual awareness). The objective is to study USN in Parkinson's pa tients, followed and hospitalized at the Neurology Department of Hassan II University Hospital in Fez. The visual-graphic test that has been used to detect this pathology is that of Bell's test. The test focuses on the detection of targets placed among several stimuli on a sheet of A4 paper. The material included 120 people: 60 Parkinsonian patients: 34 men (56,7%), and 26 women (43,3%) and 60 control subjects: 34 men (56,7%), and 26 women (43,3%). The groups were matched by age and sex. Different aspects of neglect have been observed throughout the Bell's test. It was found that total omission of bell figures was significantly influenced by age, being less frequent in the 35-49 age group in both groups, and higher in the elderly (50-80 years), as well the level of education. It have been reduced considerably with the increase in education. The hand used and the laterality had no effect; t = 3.76 degrees of freedom (df) = 108.27 and p = 0.000. Unilateral spatial neglect has a negative effect in subjects with Parkin- son's disease. It deserves to be systematically sought for a better clinical evaluation and therapeutic management of the patients.
Źródło:
Acta Neuropsychologica; 2021, 19(2); 219-229
1730-7503
2084-4298
Pojawia się w:
Acta Neuropsychologica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative analysis of computer typing of healthy people and people with Parkinson’s disease
Autorzy:
Anchimowicz, Anna
Derlatka, Marcin
Powiązania:
https://bibliotekanauki.pl/chapters/2215317.pdf
Data publikacji:
2022
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
Parkinson’s disease
keyboard typing
statistical analysis
Opis:
Nowadays, methods are being searched in order to detect Parkinson’s disease at an early stage. This would aid faster diagnosis and a more objective assessment of the severity of the condition. This paper focuses on examining whether typing differs between healthy people and people with varying degrees of Parkinson’s disease. The analysis used publicly available data from the physionet.org database [1], which contains results from 227 people over several experimental days. Data from only 108 subjects were used, with a maximum of 3 days of use of the Tappy application by one participant with at least 200 clicks considered. Computer keyboard typing parameters, such as button hold time, latency and flight time were taken into account. Statistical analysis of the data obtained using non-parametric Kruskal-Wallis tests showed that there were no statistically significant differences (α < 0.05) between the study groups (healthy people and people with varying degrees of Parkinson’s disease). However, the reason for this may be the small study group and the lack of consideration of medications taken when matching to groups.
Źródło:
Advances in biomedical engineering; 99-107
9788367185400
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Travel to altitude with neurological disorders
Autorzy:
Angelini, Corrado
Giardini, Guido
Falla, Marika
Powiązania:
https://bibliotekanauki.pl/articles/2098265.pdf
Data publikacji:
2021-07-21
Wydawca:
Państwowa Wyższa Szkoła Zawodowa w Tarnowie
Tematy:
altitude
mountaineering
migraine
stroke
epilepsy
seizures
Parkinson disease
Opis:
The present review examines several neurological conditions and the problems posed by travelling to high altitude, and in particular whether the underlying disease is likely to worsen. The neurological conditions include migraine and other types of headaches, transient ischemia of the brain, occlusive cerebral artery diseases, intracranial haemorrhage and vascular malformations, intracranial space occupying mass, multiple sclerosis, peripheral neuropathies, neuromuscular disorders, epileptic seizures, dementia and Parkinson’s disease. Attempts will be made to classify the risk posed by each condition and to provide recommendations regarding medical evaluation, advice for or against travelling to altitude and effective prophylactic measures. Some individual cases should only be advised after careful examination and risk evaluation either in an outpatient mountain medicine service or by a physician with knowledge of travelling and high altitude risks. Recent developments in diagnostic methods and treatment of neurological conditions are also mentioned.
Źródło:
Health Promotion & Physical Activity; 2021, 15, 2; 29-39
2544-9117
Pojawia się w:
Health Promotion & Physical Activity
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Temporomandibular joint disorder in patients with Parkinson’s disease – a pilot study
Zespół zaburzeń czynności stawu skroniowo-żuchwowego u pacjentów z chorobą Parkinsona – badanie pilotażowe
Autorzy:
Baumann, P.
Sági, A.
Perjés, B.
Prémusz, V.
Ács, P.
Marada, G.
Kovács, N.
Radnai, M.
Powiązania:
https://bibliotekanauki.pl/articles/2048528.pdf
Data publikacji:
2020
Wydawca:
Akademia Bialska Nauk Stosowanych im. Jana Pawła II w Białej Podlaskiej
Tematy:
Parkinson’s disease
temporomandibular joint disorder
quality of life
SF-36
oral health impact profile
choroba Parkinsona
zaburzenie czynności stawu skroniowo-żuchwowego
jakość życia
profil wpływu zdrowia jamy ustnej
Opis:
Background. The number of patients with temporomandibular joint disorders (TMD) is increasing in clinical dental practice. Our study aimed to determine whether a correlation between Parkinson’s disease and TMD symptoms can be established. Material and methods. The anamnestic and clinical dysfunctional indices and the correlations related to the quality of life (SF 36, QoL) of Parkinson’s disease patients (PG, n=35) and healthy controls (CG, n=42) were examined in a cross-sectional study. Statistical analysis was carried out using SPSS 24.0 software. Results. The mean value (7.0±7.7) of the PG in the OHIP-14 (Oral Health Impact Profile) questionnaire was significantly higher (p<0.001) than that of the CG (2.0±3.7). The ratio of belonging to the asymptomatic (Ai0) group was higher in the CG (71.4%) than in the PG (45.7%). The number of moderate or severe symptoms (DiII and DiIII) was higher in the PG (37.1%) than in the CG (2.4%). The mean value of QoL of the PG (60.9±20.1) was significantly lower (p<0.001) than that of the CG (75.9±15.3). Conclusions. Results of the study support that patients with Parkinson’s disease have a higher incidence of TMD. Using the SF-36, we were able to quantify lower QoL of the PG.
Wprowadzenie. W stomatologicznej praktyce klinicznej coraz częściej widuje się pacjentów z zaburzeniami czynności stawu skroniowo-żuchwowego (ang. temporomandibular joint disorder, TMD). Celem badania było ustalenie, czy istnieje zależność między objawami TMD a chorobą Parkinsona. Materiał i metody. W badaniu przekrojowym wzięto pod uwagę anamnestyczne i kliniczne wskaźniki dysfunkcji oraz korelacje związane z jakością życia (kwestionariusz oceny jakości życia SF-36) u pacjentów z chorobą Parkinsona (PG, n=35) i u osób zdrowych (CG, n=42). Analizę statystyczną przeprowadzono przy użyciu oprogramowania SPSS 24.0. Wyniki. Średnia wartość uzyskana na podstawie profilu wpływu zdrowia jamy ustnej (ang. Oral Health Impact Profile, OHIP-14) dla PG (7,0±7,7) była znacznie wyższa (p<0,001) niż wśród CG (2,0±3,7). Wskaźnik przynależności do grupy bezobjawowej (Ai0) okazał się wyższy w przypadku GK (71,4%) w porównaniu do PG (45,7%). Liczba umiarkowanych lub ciężkich objawów (DiII i DiIII) była większa u PG (37,1%) aniżeli u CG (2,4%). Średnia wartość jakości życia dla PG (60,9±20,1) była natomiast istotnie niższa (p<0,001) niż w przypadku CG (75,9±15,3). Wnioski. Wyniki badania potwierdzają, że pacjenci z chorobą Parkinsona częściej cierpią z powodu TMD. Dzięki zastosowaniu SF-36 określono ilościowo niższą jakość życia PG.
Źródło:
Health Problems of Civilization; 2020, 14, 3; 235-241
2353-6942
2354-0265
Pojawia się w:
Health Problems of Civilization
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Antioxidant properties of PF9601N, a novel MAO-B inhibitor: assessment of its ability to interact with reactive nitrogen species
Autorzy:
Bellik, Lydia
Dragoni, Stefania
Pessina, Federica
Sanz, Elisenda
Unzeta, Mercedes
Valoti, Massimo
Powiązania:
https://bibliotekanauki.pl/articles/1040409.pdf
Data publikacji:
2010
Wydawca:
Polskie Towarzystwo Biochemiczne
Tematy:
MAO-B inhibitors
peroxynitrite
l-deprenyl
nitric oxide
Parkinson's disease
Opis:
The novel MAO-B inhibitor PF9601N, its cytochrome P450-dependent metabolite FA72 and l-deprenyl were studied as potential peroxynitrite (ONOO-) scavengers and nitric oxide synthase (NOS) inhibitors. The scavenging activity of these compounds was evaluated by measuring the oxygen consumption through peroxynitrite-mediated oxidation of both linoleic acid and brain homogenate. FA72, PF9601N and l-deprenyl caused a concentration-dependent inhibition of ONOO--induced linoleic acid oxidation with an IC50 value of 60.2 µM, 82.8 µM and 235.8 µM, respectively. FA72 was the most potent also in inhibiting ONOO--induced brain homogenate oxidation with an IC50 value of 99.4 µM, while PF9601N and l-deprenyl resulted weaker inhibitors in the same experimental model, showing an IC50 value of 164.8 and 112.0 µM, respectively. Furthermore, both the novel MAO-B inhibitor as well as its metabolite were able to strongly inhibit rat brain neuronal NOS (IC50 of 183 µM and 192 µM, respectively), while l-deprenyl at the highest concentration used (3 mM), caused only a slight decrease of the enzyme activity. Moreover, inducible NOS was strongly inhibited by FA72 only. All these results suggest that PF9601N could be a promising therapeutic agent in neurodegenerative disorders such as Parkinson's disease.
Źródło:
Acta Biochimica Polonica; 2010, 57, 2; 235-239
0001-527X
Pojawia się w:
Acta Biochimica Polonica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid two-stage SqueezeNet and support vector machine system for Parkinson’s disease detection based on handwritten spiral patterns
Autorzy:
Bernardo, Lucas Salvador
Damaševičius, Robertas
de Albuquerque, Victor Hugo C.
Maskeliūnas, Rytis
Powiązania:
https://bibliotekanauki.pl/articles/2055162.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
Parkinson’s disease
spirography
convolutional neural network
deep learning
choroba Parkinsona
spirografia
sieć neuronowa konwolucyjna
uczenie głębokie
Opis:
Parkinson’s disease (PD) is the second most common neurological disorder in the world. Nowadays, it is estimated that it affects from 2% to 3% of the global population over 65 years old. In clinical environments, a spiral drawing task is performed to help to obtain the disease’s diagnosis. The spiral trajectory differs between people with PD and healthy ones. This paper aims to analyze differences between handmade drawings of PD patients and healthy subjects by applying the SqueezeNet convolutional neural network (CNN) model as a feature extractor, and a support vector machine (SVM) as a classifier. The dataset used for training and testing consists of 514 handwritten draws of Archimedes’ spiral images derived from heterogeneous sources (digital and paper-based), from which 296 correspond to PD patients and 218 to healthy subjects. To extract features using the proposed CNN, a model is trained and 20% of its data is used for testing. Feature extraction results in 512 features, which are used for SVM training and testing, while the performance is compared with that of other machine learning classifiers such as a Gaussian naive Bayes (GNB) classifier (82.61%) and a random forest (RF) (87.38%). The proposed method displays an accuracy of 91.26%, which represents an improvement when compared to pure CNN-based models such as SqueezeNet (85.29%), VGG11 (87.25%), and ResNet (89.22%).
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 4; 549--561
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of hand and face images for the purpose of engineering support for Parkinsons disease diagnosis
Analiza obrazów dłoni i twarzy na potrzeby inżynierskiego wsparcia diagnostyki choroby Parkinsona
Autorzy:
Białek, Kamila
Potulska-Chromik, Anna
Jakubowski, Jacek
Nojszewska, Monika
Kostera-Pruszczyk, Anna
Powiązania:
https://bibliotekanauki.pl/articles/2171782.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Technologiczno-Humanistyczny im. Kazimierza Pułaskiego w Radomiu
Tematy:
image processing
medical diagnosis
Parkinson’s disease
przetwarzanie obrazów
diagnoza medyczna
choroba Parkinsona
Opis:
Engineering support in the field of recognizing Parkinson's disease against the background of other diseases, its progression and monitoring the effectiveness of drugs is currently widely implementedas part of work devoted to the use of recording and analysis devices equipped with sensors of movement parameters attached to the patient's body, e.g. accelerometers and gyroscopes. This material touches on an alternative approach, in which the concept of using techniques for processing selected image data obtained during a clinical examination evaluating a patient using the unified UPDRS number scale is proposed. The research was conducted on a material that corresponded to selected components of the scale and included images of faces recorded in the visible light range and images of the outer surfaces of the hand recorded with a thermal imaging camera.This was aimed at assessing the possibility of differentiating personsin terms of detecting Parkinson's disease on the basis of registered modalities. Thus, tasks aimed at developing characteristics important in the binary classification process were carried out. The assessment of features was made in a modality-dependent manner based on available tools in the field of statistics and machine learning.
Wsparcie inżynierskie w zakresie rozpoznawania choroby Parkinsona na tle innych chorób, jej progresji oraz monitorowania skuteczności leków jest obecnie szeroko realizowane w ramach prac poświęconych wykorzystaniu urządzeń rejestrujących i analizujących wyposażonych w sensory parametrów ruchu przymocowanych do ciała pacjenta, np. akcelerometry i żyroskopy. W prezentowanej pracy przedstawiono alternatywne podejście, w którym proponuje się koncepcję wykorzystania technik przetwarzania wybranych danych obrazowych uzyskanych podczas badania klinicznego oceniającego pacjenta za pomocą ujednoliconej skali liczbowej UPDRS. Badania przeprowadzono na materiale, który odpowiadał wybranym składowym skali i obejmował obrazy twarzy utrwalone w zakresie światła widzialnego oraz obrazy zewnętrznych powierzchni dłoni rejestrowane kamerą termowizyjną. Wykonane badania miały na celu ocenę możliwości różnicowania osób pod względem wykrywania choroby Parkinsona na podstawie zarejestrowanych metod. W ten sposób zrealizowano zadania mające na celu opracowanie cech istotnych w procesie klasyfikacji binarnej. Ocena cech została dokonana w sposób zależny od modalności w oparciu o dostępne narzędzia z zakresu statystyki i uczenia maszynowego.
Źródło:
Journal of Automation, Electronics and Electrical Engineering; 2022, 4, 1; 13--20
2658-2058
2719-2954
Pojawia się w:
Journal of Automation, Electronics and Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Caffeine and neurodegenerative disorders
Autorzy:
BOGATKO, Karolina
SZOPA, Aleksandra
POLESZAK, Ewa
Powiązania:
https://bibliotekanauki.pl/articles/1033776.pdf
Data publikacji:
2014
Wydawca:
Zakład Opieki Zdrowotnej Ośrodek Umea Shinoda-Kuracejo
Tematy:
Alzheimer’s disease
Parkinson’s disease
adenosine
caffeine
Opis:
Neurodegenerative disorders are amongst the most dangerous diseases in modern society. At the end of 1990, adenosine receptor antagonists were used to block the adenosine A1 and A2A receptors causing less physical, cellular and molecular damage caused by Alzheimer’s and Parkinson’s diseases. In recent years, an increase in death rate caused by these diseases has been observed among people under 74. Caffeine, as NMDA receptor antagonist, prevents an uncontrolled influx of calcium ions into the interior of the cells exerting a neuroprotective effect and beneficial procognitive effects. There is much evidence that caffeine intake is associated with a reduced risk of Alzheimer’s and Parkinson’s diseases.
Źródło:
Medicina Internacia Revuo; 2014, 26, 103; 89-93
0465-5435
Pojawia się w:
Medicina Internacia Revuo
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel Parkinsons disease detection algorithm combined EMD, BFCC, and SVM classifier
Autorzy:
Boualoulou, Nouhaila
Mounia, Miyara
Nsiri, Benayad
Behoussine Drissi, Taoufiq
Powiązania:
https://bibliotekanauki.pl/articles/27313826.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
EMD
BFCC
MFCC
SVM
Parkinson’s disease
sztuczna sieć neuronowa
choroba Parkinsona
Opis:
Identifying and assessing Parkinson's disease in its early stages is critical to effectively monitoring the disease's progression. Methodologies based on machine learning enhanced speech analysis are gaining popularity as the potential of this field is revealed. Acoustic features, in particular, are used in a variety of algorithms for machine learning and could serve as indicators of the general health of subjects' voices. In this research paper, a novel method is introduced for the automated detection of Parkinson's disease through speech signal analysis, a support vector machines classifier (SVM) and an Artificial Neural Network (ANN) are used to evaluate and classify the data based on two acoustic features: Bark Frequency Cepstral Coefficients (BFCC) and Mel Frequency Cepstral Coefficients (MFCC). These features are extracted from the denoised signals using Empirical Mode Decomposition (EMD). The most relevant results obtained for a dataset of 38 participants are by the BFCC coefficients with an accuracy up to 92.10%. These results confirm that EMD-BFCC-SVM method can contribute to the detection of Parkinson's disease.
Źródło:
Diagnostyka; 2023, 24, 4; art. no. 2023404
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
CNN and LSTM for the classification of parkinsons disease based on the GTCC and MFCC
Autorzy:
Boualoulou, Nouhaila
Drissi, Taoufiq Belhoussine
Nsiri, Benayad
Powiązania:
https://bibliotekanauki.pl/articles/30148250.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
Parkinson's disease
voice signal
GTCC
MFCC
DWT
EMD
CNN and LSTM
Opis:
Parkinson's disease is a recognizable clinical syndrome with a variety of causes and clinical presentations; it represents a rapidly growing neurodegenerative disorder. Since about 90 percent of Parkinson's disease sufferers have some form of early speech impairment, recent studies on tele diagnosis of Parkinson's disease have focused on the recognition of voice impairments from vowel phonations or the subjects' discourse. This paper presents a new approach for Parkinson's disease detection from speech sounds that are based on CNN and LSTM and uses two categories of characteristics. These are Mel Frequency Cepstral Coefficients (MFCC) and Gammatone Cepstral Coefficients (GTCC) obtained from noise-removed speech signals with comparative EMD-DWT and DWT-EMD analysis. The proposed model is divided into three stages. In the first step, noise is removed from the signals using the EMD-DWT and DWT-EMD methods. In the second step, the GTCC and MFCC are extracted from the enhanced audio signals. The classification process is carried out in the third step by feeding these features into the LSTM and CNN models, which are designed to define sequential information from the extracted features. The experiments are performed using PC-GITA and Sakar datasets and 10-fold cross validation method, the highest classification accuracy for the Sakar dataset reached 100% for both EMD-DWT-GTCC-CNN and DWT-EMD-GTCC-CNN, and for the PC-GITA dataset, the accuracy is reached 100% for EMD-DWT-GTCC-CNN and 96.55% for DWT-EMD-GTCC-CNN. The results of this study indicate that the characteristics of GTCC are more appropriate and accurate for the assessment of PD than MFCC.
Źródło:
Applied Computer Science; 2023, 19, 2; 1-24
1895-3735
2353-6977
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The diseases classification method on gait abnormalities characteristic contributions
Autorzy:
Chandzlik, S.
Piecha, J.
Powiązania:
https://bibliotekanauki.pl/articles/333759.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
klasyfikacja chorób neurologicznych
choroba Parkinsona
niedowład
udar niedokrwienny mózgu
automatyczne zakończenie
sieci nuronowe
neurological disease classification
Parkinson disease
hemiparesis
ischemic stroke
automatic conclusion
neural networks
Opis:
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.
Źródło:
Journal of Medical Informatics & Technologies; 2005, 9; 187-194
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The interference spectrum extraction of a gait characteristics data record
Autorzy:
Chandzlik, S.
Piecha, J.
Powiązania:
https://bibliotekanauki.pl/articles/333704.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
szkolenia sieci neuronowych
analiza chodu
zaburzenia chodu
rozpoznanie niedowładu połowicznego
rozpoznanie choroby Parkinsona
neural network training
gait analysis
gait disturbances
hemiparesis diagnosis
Parkinson's disease diagnosis
Opis:
The paper shows several aspects of the gait data record analysis describing neurological diseases. The diagnosis of the gait abnormalities concerns interferences level of the patient physiological records. The disease source and level can be classified by the relevant interference functions. These functions were used for artificial records creation to multiply the necessary set of data needed for neural network training.
Źródło:
Journal of Medical Informatics & Technologies; 2004, 7; KB23-32
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The method of neuron weight vector initial values selection in Kohonen network
Autorzy:
Chandzlik, S.
Powiązania:
https://bibliotekanauki.pl/articles/333164.pdf
Data publikacji:
2006
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
neural networks
Kohonen network
neurological diseases diagnosis
Parkinson disease
hemiparesis after ischemic stroke
Opis:
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.
Źródło:
Journal of Medical Informatics & Technologies; 2006, 10; 189-197
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Do Gulf War veterans with high levels of deployment-related exposures display symptoms suggestive of Parkinson’s disease?
Autorzy:
Chao, Linda L.
Powiązania:
https://bibliotekanauki.pl/articles/2161963.pdf
Data publikacji:
2019-07-15
Wydawca:
Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
Tematy:
occupational exposure
pesticides
chemical exposure
Parkinson’s disease
basal ganglia
Gulf War
Opis:
Objectives Veterans of the 1991 Gulf War (GW) were exposed to a myriad of potentially hazardous chemicals during deployment. Epidemiological data suggest a possible link between chemical exposures and Parkinson’s disease (PD); however, there have been no reliable data on the incidence or prevalence of PD among GW veterans to date. This study included the following 2 questions: 1. Do deployed GW veterans display PD-like symptoms? and 2. Is there a relationship between the occurrence and quantity of PD-like symptoms, and the levels of deployment-related exposures in GW veterans? Material and Methods Self-reports of symptoms and exposures to deployment-related chemicals were filled out by 293 GW veterans, 202 of whom had undergone 3 Tesla volumetric measurements of basal ganglia volumes. Correlation analyses were used to examine the relationship between the frequency of the veterans’ self-reported exposures to deployment-related chemicals, motor and non-motor symptoms of PD, and the total basal ganglia volumes. Results Healthy deployed GW veterans self-reported few PD-like non-motor symptoms and no motor symptoms. In contrast, GW veterans with Gulf War illness (GWI) self-reported more PD-like motor and non-motor symptoms, and more GW-related exposures. Compared to healthy deployed veterans, those with GWI also had lower total basal ganglia volumes. Conclusions Although little is known about the long-term consequences of GWI, findings from this study suggest that veterans with GWI show more symptoms as those seen in PD/prodromal PD, compared to healthy deployed GW veterans. Int J Occup Med Environ Health. 2019;32(4):503–26
Źródło:
International Journal of Occupational Medicine and Environmental Health; 2019, 32, 4; 503-526
1232-1087
1896-494X
Pojawia się w:
International Journal of Occupational Medicine and Environmental Health
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 93

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