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Gotowe bibliografie tematyczne / PARKINSON'S DISEASE DETECTION

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Gotowa bibliografia na temat „PARKINSON'S DISEASE DETECTION”

Autor: Grafiati

Data publikacji: 11 września 2023

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Rozprawy doktorskie na temat "PARKINSON'S DISEASE DETECTION"

1

Saad, Ali. "Detection of Freezing of Gait in Parkinson's disease." Thesis, Le Havre, 2016. http://www.theses.fr/2016LEHA0029/document.

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Le risque de chute provoqué par le phénomène épisodique de ‘Freeze of Gait’ (FoG) est un symptôme commun de la maladie de Parkinson. Cette étude concerne la détection et le diagnostic des épisodes de FoG à l'aide d'un prototype multi-capteurs. La première contribution est l'introduction de nouveaux capteurs (télémètres et goniomètres) dans le dispositif de mesure pour la détection des épisodes de FoG. Nous montrons que l'information supplémentaire obtenue avec ces capteurs améliore les performances de la détection. La seconde contribution met œuvre un algorithme de détection basé sur des résea

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2

Chen, Lei [Verfasser]. "Computer-aided detection of Parkinson's Disease using transcranial sonography / Lei Chen." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2014. http://d-nb.info/1046712691/34.

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Taleb, Catherine. "Parkinson's desease detection by multimodal analysis combining handwriting and speech signals." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT039.

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La maladie de Parkinson (MP) est un trouble neurologique causé par une diminution du niveau de dopamine dans le cerveau. Cette maladie est caractérisée par des symptômes moteurs et non moteurs qui s'aggravent avec le temps. Aux stades avancés de la maladie de Parkinson, le diagnostic clinique est clair. Cependant, dans les premiers stades, lorsque les symptômes sont souvent incomplets ou subtils, le diagnostic devient difficile et, parfois, le sujet peut rester non diagnostiqué. En outre, il n'existe pas de méthodes efficaces et fiables permettant d'établir avec certitude un diagnostic précoce

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Jalloul, Nahed. "Development of a system of acquisition and movement analysis : application on Parkinson's disease." Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S096/document.

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Le travail présenté dans ce mémoire porte sur le développement d'un système de surveillance ambulatoire pour la détection de la dyskinésie induite par la Levodopa (LID) chez les patients de la maladie de Parkinson (PD). Le système est composé d’unités de mesure inertielle (IMUs) qui recueillent des signaux de mouvement chez des sujets sains et des patients parkinsoniens. Des méthodes différentes sont évaluées pour la détection de LID avec et sans classification des activités. Les données recueillies auprès des sujets sains sont utilisées pour concevoir un classificateur d'activité fiable. Par

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F, Miraglia. "Development of molecular biosensors for the detection of alpha-synuclein aggregation in cells." Doctoral thesis, Università di Siena, 2020. http://hdl.handle.net/11365/1096217.

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Introduction: Parkinson’s Disease (PD) is the second most common neurodegenerative disorder, which affects more than 6 million people worldwide. PD is a progressive multiorgan proteinopathy, also called synucleinopathy, because of the abnormal neuronal accumulation of misfolded alpha-synuclein (αS), an intrinsically disorder protein (IDP) of 140 amino acids. αS is expressed ubiquitously in the cells and has been particularly found associated with membranes in the pre-synaptic terminal, suggesting a role in the regulation of vesicle trafficking, synaptic transmission and synaptic plasticity. En

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Takač, Boris. "Context-aware home monitoring system for Parkinson's disease patietns : ambient and werable sensing for freezing of gait detection." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/668652.

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Parkinson’s disease (PD). It is characterized by brief episodes of inability to step, or by extremely short steps that typically occur on gait initiation or on turning while walking. The consequences of FOG are aggravated mobility and higher affinity to falls, which have a direct effect on the quality of life of the individual. There does not exist completely effective pharmacological treatment for the FOG phenomena. However, external stimuli, such as lines on the floor or rhythmic sounds, can focus the attention of a person who experiences a FOG episode and help her initiate gait. The optimal

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Ruffmann, Claudio. "Detection of alpha-synuclein conformational variants from gastro-intestinal biopsy tissue as a potential biomarker for Parkinson's disease." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:3cddebda-aaf4-40c5-b026-9365aa16fdd7.

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Gastrointestinal (GI) alpha-synuclein (ASN) detection may represent a clinically useful biomarker of Parkinson's disease (PD), but this has been challenged by conflicting results of recent studies employing different immunohistochemical (IHC) methods and reporting diverse morphological patterns with variable biological interpretation. To increase sensitivity and specificity, we applied three different techniques to detect different possible conformations of ASN in GI tissue derived from biopsies of the GI tract, which were obtained from a longitudinally followed, clinically well-characterized

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Hu, Kun. "Fine-grained Human Action Recognition for Freezing of Gait Detection." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/27286.

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Freezing of gait (FoG) presents as a sudden and brief episode of movement cessation despite the intention to continue walking. As a common symptom of Parkinson's Disease, early detection and quantification of FoG are of great importance in clinical practice. Therefore, this thesis focuses on vision-based and pressure-based FoG detection methods, which were seldom investigated in the past. The task can be treated as a human action recognition problem. Although various deep architectures have achieved encouraging performance for general action recognition, FoG events contain fine-grained pattern

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Ahlrichs, Claas [Verfasser], Michael [Akademischer Betreuer] Lawo, and Albert [Akademischer Betreuer] Samà. "Development and Evaluation of AI-based Parkinson's Disease Related Motor Symptom Detection Algorithms / Claas Ahlrichs. Gutachter: Michael Lawo ; Albert Samà. Betreuer: Michael Lawo." Bremen : Staats- und Universitätsbibliothek Bremen, 2015. http://d-nb.info/1075609321/34.

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10

Mohammadian, Rad Nastaran. "Deep Learning for Abnormal Movement Detection using Wearable Sensors: Case Studies on Stereotypical Motor Movements in Autism and Freezing of Gait in Parkinson's Disease." Doctoral thesis, Università degli studi di Trento, 2019. https://hdl.handle.net/11572/368163.

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Inertial measurement sensing technology with the capability of capturing disease-relevant data has a great potential for improving the current clinical assessments and enhancing the quality of life in patients with neuro-developmental and neuro-degenerative diseases such as autism spectrum disorders (ASD) and Parkinson's disease (PD). The current clinical assessments can be improved by developing objective tools for the disease diagnosis and continuous monitoring of patients in out of clinical settings. To this end, it is necessary to develop automatic abnormal movement detection methods with

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