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Video analysis of hypomimia in Parkinson's disease and other synucleinopathies

M. Novotny (2023 - 2026)

Czech Ministry of Health: NU23J-04-00042
FIS ID: 2512301C000

Currently, no sufficiently accurate diagnostic or progressive biomarker of alfa-synucleinopathy (aSYN) is available that would allow early intervention to prevent the disease progression with potential neuroprotective therapies. Disruption or complete loss of spontaneous and deliberate facial movements, termed hypomimia, is a common motor manifestation of aSYN diseases such as Parkinson's disease (PD) or multiple system atrophy (MSA). Hypomimia is considered one of the earliest PD motor manifestations, developing up to 10 years before the clinical diagnosis. Even though hypomimia is a hallmark of PD, objective, precise, robust and easily interpretable tools to capture the disruption of facial movements are lacking. The current gold standard for hypomimia evaluation is a perceptual assessment based on a subjective, very simple 5-point rating scale, not allowing for a more detailed description of separate hypomimia aspects. The goal of this project is to develop and validate a robust objective tool for video analysis of facial expressivity in recordings of spontaneous speech and posed grimacing, sufficiently sensitive to detect (i) hypomimia in patients with REM sleep behavior disorder (RBD, a special case of prodromal aSYN), (ii) potential effects of short- and longterm dopaminergic medication on hypomimia in early PD, and (iii) differences in particular hypomimia patterns and its severity in parkinsonian variant of MSA compared to PD. Automated hypomimia analysis can become the important tool to recognize neurodegeneration in its earliest stage allowing for early initiation of an effective therapy once available. The hypomimia markers may also help to monitor different phenotype characteristics, disorder severity, and the pharmacological therapy effect. Moreover, better understanding of processes underlying hypomimia is essential for the correct choice of therapy aimed at alleviation of facial expressivity loss with significant impact on quality of patients’ life.



National institute for Neurological Research

J. Rusz (2022 - 2025)

Programme EXCELES, funded by the European Union – Next Generation EU: LX22NPO5107
FIS ID: 122/1662201C000/13131

In connection with the dramatically increasing average age of the population and the worldwide increase in the occurrence of neurological, and especially neurodegenerative diseases, with still unclear etiology and pathogenesis, and non-existent preventive or causal therapy, the urgent need for their focused research is increasing. This imperative is all the more significant as the health and economic impact on our society will be enormous in the coming decades. Therefore, the development of the necessary components of neurodegeneration research in the areas of clinical, imaging, electrophysiological, molecular genetic, biochemical and neuropathological markers, etiopathogenetic mechanisms and experimental therapies is clearly necessary.



Reducing speech-related side-effects of deep brain stimulation in Parkinson's Disease via automated speech analysis

J. Rusz (2021 - 2023)

Czech Science Foundation: 21-14216L
FIS ID: 301-3012102C000-13131

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective treatment of motor symptoms of Parkinson’s disease (PD), but its effects on speech are equivocal. Although some aspects of speech might improve with STN-DBS, stimulation-induced dysarthria represents the most common side effect, with a prevalence of up to 90%. The human ear has very limited capacities in the qualitative and quantitative evaluation of speech. Thus improvement of STN-DBS induced dysarthria is still an unmet need. New methods of automated speech assessment based on acoustic analysis and machine-learning algorithms have quantified subtle speech alterations and distinguished different types of dysarthria. Systematic implementation of automated speech analysis would facilitate not only time-consuming postoperative management but also improve overall outcomes of STN-DBS and thus. The results of this project will provide the first step towards fully automatized closed-loop DBS based on speech as a biomarker, allowing to improve outcomes of DBS and quality of life in PD patients in the near future.



Smart Speech Biomarkers for Parkinson’s Disease and Other Synucleinopathies

J. Rusz (2020 - 2023)

Czech Ministry of Health: NU20-08-00445
FIS ID: 13131/251/2512001C000

The early recognition of Parkinson’s disease (PD) and other synucleinopathies in prodromal stages has crucial implications for the future development of neuroprotective therapy. With no validated diagnostic biomarker, there is no way to identify people at risk for PD or to establish strategies for the prevention of PD. Speech is highly susceptible to neurodegeneration. This project aims to discover for the first time preclinical stages of PD in “at high risk” patients with REM sleep behavior disorder based on longitudinal speech monitoring through regular smartphone calls in a naturalistic environment and high-end pattern analysis. Developed complex system based on speech assesment (SMARTSPEECH) would have very high potential to revolutionize the diagnostic process in PD and provide robust biomarker of disease progression. Quick, inexpensive, and non-invasive vocal assessment by smartphone may result in faster implementation of treatment strategies and bolster early presymptomatic diagnosis of synucleinopathy allowing rapid access to neuroprotective therapy once it will be available.



Former/Finished


Objective investigation of distinct speech phenotypes in newly diagnosed Parkinson's disease including effects of pharmacotherapy
T. Tykalová (2019 - 2022)
Czech Ministry of Health: NV19-04-00120
FIS ID: 13131/252/2521901C000


Population standard of acoustic-phonetic characteristics in children's speech
R. Čmejla (2019 - 2021)
Czech Science Foundation: 19-20887S


Automatic acoustic speech analysis and REM sleep behaviour disorder for detecting subjects at high risk for Parkinson's disease and other alpha-synucleinopathies
J. Rusz (2017 - 2021)
Michael J Fox Foundation (MJFF): 12546
[MJFF link][Project info]
FIS ID: 6611701C000


Biological Signals and Their Processing
J. Rusz (2020 - 2022)
Grant Agency of the Czech Technical University in Prague: SGS20/168/OHK3/3T/13
FIS ID: TBC


R. Čmejla (2017 - 2020)
Význam funkční a strukturální reorganizace mozkových sítí v patogenezi kognitivního deficitu a epilepsie po cévní mozkové příhodě
Czech Ministry of Health: NV17-28427A

R. Čmejla (2018 - 2019)
Analysis and processing of bio-signals for diagnostics of neurological disruptions
Grant Agency of the Czech Technical University in Prague SGS18/137/OHK3/2T/13

R. Čmejla (2016 - 2018)
Age-related changes in acoustic characteristics of adult speech
Czech Science Foundation GACR 16-19975S

J. Rusz (2016 - 2018)
Investigation of pathomechanisms responsible for speech and voice disorders in multiple sclerosis using new methods of objective acoustic analysis
Czech Science Foundation GACR 16-03322S

J. Rusz & R. Čmejla (2015 - 2018)
Speech disorders and analysis of their mechanism in Parkinson's disease and other movement disorders
Czech Ministry of Health AZV ČR 15-28038A

R. Čmejla (2015 - 2018)
Analýza funkční organizace epileptogenních sítí s využitím teorie grafů: význam pro předoperační diagnostiku pacientů s neokortikální epilepsií
Czech Ministry of Health AZV ČR 15-29835A

R. Janča (2015 - 2018)
Prevence motorických deficitů po epileptochirurgických výkonech u dětí
Czech Ministry of Health AZV ČR 15-30456A

R. Čmejla (2015-2017)
Analysis and Processing of Biological Signals
Grant Agency of the Czech Technical University SGS15/198/OHK3/3T/13

J. Rusz (2015-2017)
Acoustic Analyses and Processing of Speech Signals in Patients with Central Nervous System Disorders
Grant Agency of the Czech Technical University SGS15/199/OHK3/3T/13

R. Čmejla (2014-2016)
Large-scale dynamics and critical transitions in neuronal networks and their role in limbic seizure genesis
Czech Science Foundation GAČR

R. Čmejla (2013-2015)
Understanding of functional organization of temporal lobe epilepsy neuronal networks
Czech Ministry of Health NT14489

R. Čmejla (2012-2015)
Acoustic Voice and Speech Analysis in Patients with Central Nervous System Disorders
Czech Science Foundation GAČR 102/12/2230

R. Čmejla (2013-2014)
Biological Signals Analysis and Processing
Grant Agency of the Czech Technical University SGS13/138/OHK3/2T/13

J. Rusz (2012-2014)
Acoustic Analyses and New Evaluation Methods for Objectification of Voice and Speech Disorders in Neurological Illnesses
Grant Agency of the Czech Technical University SGS 12/185/OHK4/3T/13

R. Čmejla (2010 - 2013)
Intracranial EEG signal processing; epileptogenic zone identification in non-lesional refractory epilepsy patients
Czech Ministry of Health NT11460-4/2010

J. Rusz (2011)
Complex measurement of lung ventilation
Czech Ministry of Education FRV G3 328

R. Čmejla (2010-2011)
Analysis of intracranial EEG recording
Grant Agency of the Czech Technical University SGS10/272/OHK4/3T/13

J. Rusz (2010 - 2011)
Assesment of voice and speech impairment
Grant Agency of the Czech Technical University SGS 10/180/OHK3/2T/13

D. Špulák (2010-2011)
Analysis of signals induced by mechanical activity of heart
Grant Agency of the Czech Technical University SGS 10/273/OHK3/3T/13

R. Čmejla (2010)
Voice and audio signal analysis
Czech Ministry of Education FRV F3a 316

R. Čmejla (2008 - 2011)
Analysis and Modelling Biomedical and Speech Signals
Czech Science Foundation GAČR GD102/08/H008
Contact:
Czech Technical University in Prague, Faculty of Electrical Engineering
Department of Circuit Theory
Technicka 2, 166 27 Prague 6, Czech Republic
Phone: +420 2435 2236, e-mail: cmejla at fel.cvut.cz