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Prodromal Diagnosis of Lewy Body Diseases Based on Actigraphy

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU144831" target="_blank" >RIV/00216305:26220/22:PU144831 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216224:14740/22:00134704

  • Result on the web

    <a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9851316" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9851316</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TSP55681.2022.9851316" target="_blank" >10.1109/TSP55681.2022.9851316</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Prodromal Diagnosis of Lewy Body Diseases Based on Actigraphy

  • Original language description

    This paper is devoted to the computerized automated diagnosis of the prodromal state of Lewy body diseases (LBD) based on actigraphy. LBD is a group of neurodegenerative diseases that require early treatment to alleviate the course of the disease and improve the quality of the lives of patients. This work proposes a method of prodromal diagnosis of LBD based on quantitative analysis of actigraphic sleep data. A new method of sleep and wake detection based on the XGBoost classifier and the angle of the z-axis is introduced, which achieves 83% accuracy and surpasses the results of state-of-the-art methods. Furthermore, a method that can distinguish subjects with prodromal LBD (50 subjects with Parkinson's disease, dementia with Lewy bodies or mild cognitive impairment) and healthy controls (63 subjects) with 94% accuracy was introduced. The sensitivity of the method of 100% and specificity of 91% was considered sufficient for clinical practice and the proposed methods can help develop decision-making tools that maximize the potential for an early and objective diagnosis of LBD.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/NU20-04-00294" target="_blank" >NU20-04-00294: Diagnostics of Lewy body diseases in prodromal stage based on multimodal data analysis</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2022 45th International Conference on Telecommunications and Signal Processing (TSP)

  • ISBN

    978-1-6654-6948-7

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    403-406

  • Publisher name

    IEEE

  • Place of publication

    neuveden

  • Event location

    Prague

  • Event date

    Jul 13, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article