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@inproceedings{2370277,
author = {Mikulec, Marek and Galaz, Zoltan and Mekyska, Jiri and Mucha, Jan and Brabenec, Luboš and Morávková, Ivona and Rektorová, Irena},
address = {NEW YORK},
booktitle = {2022 45th International Conference on Telecommunications and Signal Processing (TSP)},
doi = {http://dx.doi.org/10.1109/TSP55681.2022.9851316},
keywords = {actigraphy; machine learning; neurodegenerative diseases; Lewy body diseases; RBD; SHAP values; sleep diary; XGBoost},
howpublished = {elektronická verze "online"},
language = {eng},
location = {NEW YORK},
isbn = {978-1-6654-6948-7},
pages = {403-406},
publisher = {IEEE},
title = {Prodromal Diagnosis of Lewy Body Diseases Based on Actigraphy},
url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9851316},
year = {2022}
}
TY - JOUR
ID - 2370277
AU - Mikulec, Marek - Galaz, Zoltan - Mekyska, Jiri - Mucha, Jan - Brabenec, Luboš - Morávková, Ivona - Rektorová, Irena
PY - 2022
TI - Prodromal Diagnosis of Lewy Body Diseases Based on Actigraphy
PB - IEEE
CY - NEW YORK
SN - 9781665469487
KW - actigraphy
KW - machine learning
KW - neurodegenerative diseases
KW - Lewy body diseases
KW - RBD
KW - SHAP values
KW - sleep diary
KW - XGBoost
UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9851316
N2 - 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 pro-dromal 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.
ER -
MIKULEC, Marek, Zoltan GALAZ, Jiri MEKYSKA, Jan MUCHA, Luboš BRABENEC, Ivona MORÁVKOVÁ a Irena REKTOROVÁ. Prodromal Diagnosis of Lewy Body Diseases Based on Actigraphy. Online. In \textit{2022 45th International Conference on Telecommunications and Signal Processing (TSP)}. NEW YORK: IEEE, 2022, s.~403-406. ISBN~978-1-6654-6948-7. Dostupné z: https://dx.doi.org/10.1109/TSP55681.2022.9851316.
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