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Duration: 01.05.2020 — 31.12.2023
Funding resources
Ministerstvo zdravotnictví ČR - Program na podporu zdravotnického aplikovaného výzkumu na léta 2020 – 2026 - 1. VS
- whole funder (2020-04-08 - not assigned)
On the project
Onemocnění s Lewyho tělísky (LBDs) je pojem označující skupinu neurodegenerativních onemocnění (tj. demenci s Lewyho tělísky a Parkinsonovu nemoc), u kterých je charakteristický patofyziologický proces akumulace synukleinu ve specifických oblastech mozku, což vede k vytváření Lewyho tělísek uvnitř neuronů a jejich následnému zániku. LBDs progredují plíživě a jsou většinou diagnostikovány v momentě, kdy neurodegenerativní proces dosáhl pokročilého stádia, ve kterém je již většina zasažených neuronů zničena. Možnost zachytit LBDs v jejich raném stádiu je rozhodující pro vývoj léčby, která by mohla proces neurodegenerace zastavit či léčit v jeho začátku. V rámci tohoto projektu využijeme komplexní multimodální analýzu za účelem identifikace prodromálních biomarkerů LBDs a k popisu patofyziologických procesů souvisejících s neurodegenerací. Tato znalost bude následně využita při tvorbě nového systému podpůrné diagnózy založeného na strojovém učení, který bude pomáhat LBDs hodnotit, diagnostikovat a monitorovat.
Description in EnglishLewy body diseases (LBDs) is a term describing a group of neurodegenerative disorders (i.e. dementia with Lewy bodies and Parkinson’s disease) characterized by pathophysiological process of alfa-synuclein accumulation in specific brain regions leading to the formation of Lewy bodies inside neurons and resulting in cell death. LBDs are progressing slowly and are usually diagnosed when the neurodegenerative process has reached severe degree in which most of the targeted neurons have already been damaged. Identification of LBDs at an early stage is crucial for development of disease-modifying treatment since the neurodegeneration may be possibly stopped or treated at the onset. In the frame of this project we are going to employ a complex multimodal analysis in order to identify prodromal biomarkers of LBDs and describe underlying pathophysiological processes. Consequently, this knowledge will be used to introduce a new machine-learning based decision support system that will help to assess, diagnose and monitor LBDs.
KeywordsOnemocnění s Lewyho tělísky; Parkinsonova nemoc; demence s Lewyho tělísky; demence u Parkinsonovy nemoci; systém podpůrné diagnózy; multimodální analýza; kvantitativní analýza; strojové učení; klinické vyšetření; elektroencefalografie; akustická analýza; aktigrafie; magnetická rezonance; transkraniální sonografie
Key words in Englishmagnetická rezonance, magnetic resonance imaging, biomarker, biomarker, Parkinsonova nemoc, electroencephalography, Machine learning, elektroencefalografie, acoustic analysis, Strojové učení, akustická analýza, Parkinson’s disease, aktigrafie, actigraphy, Transcranial Sonography, demence s Lewyho tělísky, dementia with Lewy bodies, onemocnění s Lewyho tělísky, demence u Parkinsonovy nemoci, systém podpůrné diagnózy, multimodální analýza, transkraniální sonografie, Lewy body diseases, Parkinson’s disease dementia, decision support system, multimodal analysis, prodromální příznak, individuální riziko, prodromal marker, individual risk
Mark
NU20-04-00294
Default language
Czech
People responsible
Galáž Zoltán, Ing., Ph.D. - fellow researcherMucha Ján, Ing., Ph.D. - fellow researcherMekyska Jiří, doc. Ing., Ph.D. - principal person responsible
Units
Department of Telecommunications- beneficiary (2019-06-19 - not assigned)
Results
GÓMEZ-RODELLAR, A.; PALACIOS-ALONSO, D.; FERRÁNDEZ VICENTE, J.; MEKYSKA, J.; ÁLVAREZ-MARQUINA, A.; GÓMEZ-VILDA, P. A Methodology to Differentiate Parkinson's Disease and Aging Speech Based on Glottal Flow Acoustic Analysis. INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2020, vol. 2050058, no. 1, p. 1-20. ISSN: 0129-0657.Detail
KOVÁČ, D. Quantitative Analysis of Vocal Tract Resonances in Patients with Parkinson’s Disease. In Proceedings II of the 30th Conference STUDENT EEICT 2024. Proceedings II of the Conference STUDENT EEICT. Brno: Brno University of Technology, Faculty of Elektronic Engineering and Communication, 2024. p. 146-150. ISBN: 978-80-214-6230-4. ISSN: 2788-1334.Detail
MIKULEC, M. Identification Of Sleep/Wake Stages In Actigraphy Data Utilising Gradient Boosting Algorithm. In Proceedings II of the 27st Conference STUDENT EEICT 2021 selected papers. 1. Brno: Brno University of Technology, Faculty of Electrical Engineering and Communication, 2021. p. 270-274. ISBN: 978-80-214-5943-4.Detail
KOVÁČ, D. Multilingual Analysis of Hypokinetic Dysarthria in Patients with Parkinson's disease. Proceedings I of the 27st Conference STUDENT EEICT 2021. BRNO: 2021. p. 566-570. ISBN: 978-80-214-5942-7.Detail
KOVÁČ, D.; MEKYSKA, J.; GALÁŽ, Z.; BRABENEC, L.; KOŠŤÁLOVÁ, M.; RAPCSAK, S.; REKTOROVÁ, I. Multilingual Analysis of Speech and Voice Disorders in Patients with Parkinson's Disease. In 2021 44th International Conference on Telecommunications and Signal Processing. NEW YORK: IEEE, 2021. p. 273-277. ISBN: 978-1-6654-2933-7.Detail
MIKULEC, M.; MEKYSKA, J.; SIGMUND, J.; GALÁŽ, Z.; BRABENEC, L.; MORÁVKOVÁ, I.; REKTOROVÁ, I. Automatic Segmentation of Actigraphy Data Utilising Gradient Boosting Algorithm. In 2021 44th International Conference on Telecommunications and Signal Processing. Brno, Czech Republic: IEEE, 2021. p. 399-402. ISBN: 978-1-6654-2933-7.Detail
FAUNDEZ-ZANUY, M.; MEKYSKA, J.; IMPEDOVO, D. Online Handwriting, Signature and Touch Dynamics: Tasks and Potential Applications in the Field of Security and Health. Cognitive Computation, 2021, vol. 13, no. 1, p. 1406-1421. ISSN: 1866-9956.Detail
BRABENEC, L.; KLOBUŠIAKOVÁ, P.; MEKYSKA, J.; REKTOROVÁ, I. Shannon entropy: A novel parameter for quantifying pentagon copying performance in non-demented Parkinson's disease patients. PARKINSONISM & RELATED DISORDERS, 2022, vol. 94, no. 1, p. 45-48. ISSN: 1353-8020.Detail
BRABENEC, L.; KLOBUŠIAKOVÁ, P.; MEKYSKA, J; REKTOROVÁ, I. Shannon entropy: A novel tool for assessing pentagon drawing in Parkinson's disease. MOVEMENT DISORDERS. 2021. p. S288 (S289 p.)ISSN: 0885-3185.Detail
MIKULEC, M.; MEKYSKA, J.; GÁLÁŽ Z. Parkinson’s Disease Recognition based on Sleep Metrics from Actigraphy and Sleep Diaries. In Proceedings II of the 28th Conference STUDENT EEICT 2022 Selected papers. 1. Brno, Czech Republic: Brno University of Technology, Faculty of Electronic Engineering and Communication, 2022. p. 281-285. ISBN: 978-80-214-6030-0.Detail
GALÁŽ, Z.; DROTÁR, P.; MEKYSKA, J.; GAZDA, M.; MUCHA, J.; ZVONČÁK, V.; SMÉKAL, Z.; FAÚNDEZ ZANUY, M.; CASTRILLON, R.; OROZCO-ARROYAVE, J.; RAPCSAK, S.; KINCSES, T.; BRABENEC, L.; REKTOROVÁ, I. Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson’s Disease Dysgraphia in a Multilingual Dataset. Frontiers in Neuroinformatics, 2022, vol. 16, no. 1, p. 1-18. ISSN: 1662-5196.Detail
MIKULEC, M.; GALÁŽ, Z.; MEKYSKA, J.; MUCHA, J.; BRABENEC, L.; MORÁVKOVÁ, I.; REKTOROVÁ, I. Prodromal Diagnosis of Lewy Body Diseases Based on Actigraphy. In 2022 45th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2022. p. 403-406. ISBN: 978-1-6654-6948-7.Detail
MUCHA, J.; GALÁŽ, Z.; MEKYSKA, J.; FAÚNDEZ ZANUY, M.; ZVONČÁK, V.; SMÉKAL, Z.; BRABENEC, L.; REKTOROVÁ, I. Exploration of Various Fractional Order Derivatives in Parkinson’s Disease Dysgraphia Analysis. In Lecture Notes in Computer Science. 1. Springer, Cham, 2022. p. 308-321. ISBN: 978-3-031-19745-1.Detail
GALÁŽ, Z.; MEKYSKA, J.; MUCHA, J.; ZVONČÁK, V.; SMÉKAL, Z.; FAÚNDEZ ZANUY, M.; BRABENEC, L.; MORÁVKOVÁ, I.; REKTOROVÁ, I. Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties. In Intertwining Graphonomics with Human Movements. 1. Springer, Cham, 2022. p. 255-268. ISBN: 978-3-031-19745-1.Detail
MRAČKOVÁ, M.; MAREČEK, R.; MEKYSKA, J.; KOŠŤÁLOVÁ, M.; REKTOROVÁ, I. The effect of levodopa on speech in patients with Parkinson’s disease. MOVEMENT DISORDERS. 2022. p. S86 (S86 p.)ISSN: 0885-3185.Detail
NOVOTNÝ, K.; MEKYSKA, J. Assessing Movement of Articulatory Organs in Patients with Parkinson’s Disease. In Proceedings I of the 28th Conference STUDENT EEICT 2022 General papers. 1. Brno: Brno University of Technology, Faculty of Electrical Engineering and Communication, 2023. p. 243-246. ISBN: 978-80-214-6029-4.Detail
KOVÁČ, D.; MEKYSKA, J.; AHARONSON, V.; HARÁR, P.; GALÁŽ, Z.; RAPCSAK, S.; OROZCO-ARROYAVE, J. R.; BRABENEC, L.; REKTOROVÁ, I. Exploring digital speech biomarkers of hypokinetic dysarthria in a multilingual cohort. BIOMED SIGNAL PROCES, 2023, vol. 88, no. 2, p. 1-11. ISSN: 1746-8094.Detail
MIKULEC, M.; BRABENEC, L.; MEKYSKA, J.; BOČKOVÁ, K.; GÁLÁŽ, Z.; REKTOROVÁ, I. Indirect Assessment of Hyperechogenicity of Substantia Nigra Utilizing Sleep-based Biomarkers. In 2023 14th International Conference on Intelligent Systems: Theories and Applications (SITA). 1. Casablanca, Morocco: Institute of Electrical and Electronics Engineers Inc., 2024. p. 1-6. ISBN: 9798350308211.Detail
KLOBUŠIAKOVÁ, P.; MEKYSKA, J.; BRABENEC, L.; GALÁŽ, Z.; ZVONČÁK, V.; MUCHA, J.; RAPCSAK, S.; REKTOROVÁ, I. Articulatory network reorganization in Parkinson's disease as assessed by multimodal MRI and acoustic measures. PARKINSONISM & RELATED DISORDERS, 2021, vol. 84, no. 1, p. 122-128. ISSN: 1353-8020.Detail