Search Results for author: Zdenek Smekal

Found 7 papers, 1 papers with code

Exploration of Various Fractional Order Derivatives in Parkinson's Disease Dysgraphia Analysis

no code implementations20 Jan 2023 Jan Mucha, Zoltan Galaz, Jiri Mekyska, Marcos Faundez-Zanuy, Vojtech Zvoncak, Zdenek Smekal, Lubos Brabenec, Irena Rektorova

Therefore, in this study, we follow up on our previous research, and we aim to explore the utilization of various approaches of fractional order derivative (FD) in the analysis of PD dysgraphia.


Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties

no code implementations20 Jan 2023 Zoltan Galaz, Jiri Mekyska, Jan Mucha, Vojtech Zvoncak, Zdenek Smekal, Marcos Faundez-Zanuy, Lubos Brabenec, Ivona Moravkova, Irena Rektorova

To this date, studies focusing on the prodromal diagnosis of Lewy body diseases (LBDs) based on quantitative analysis of graphomotor and handwriting difficulties are missing.

Perceptual Features as Markers of Parkinson's Disease: The Issue of Clinical Interpretability

no code implementations21 Mar 2022 Jiri Mekyska, Zdenek Smekal, Zoltan Galaz, Zdenek Mzourek, Irena Rektorova, Marcos Faundez-Zanuy, Karmele Lopez-de-Ipina

Up to 90% of patients with Parkinson's disease (PD) suffer from hypokinetic dysathria (HD) which is also manifested in the field of phonation.


Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation

no code implementations18 Mar 2022 Jan Mucha, Zoltan Galaz, Jiri Mekyska, Tomas Kiska, Vojtech Zvoncak, Zdenek Smekal, Ilona Eliasova, Martina Mrackova, Milena Kostalova, Irena Rektorova, Marcos Faundez-Zanuy, Jesus B. Alonso-Hernandez

In this work, we analysed the power of conventional speech features quantifying imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy speech.


Towards Robust Voice Pathology Detection

no code implementations13 Jul 2019 Pavol Harar, Zoltan Galaz, Jesus B. Alonso-Hernandez, Jiri Mekyska, Radim Burget, Zdenek Smekal

Automatic objective non-invasive detection of pathological voice based on computerized analysis of acoustic signals can play an important role in early diagnosis, progression tracking and even effective treatment of pathological voices.

Anomaly Detection

Voice Pathology Detection Using Deep Learning: a Preliminary Study

no code implementations12 Jul 2019 Pavol Harar, Jesus B. Alonso-Hernandez, Jiri Mekyska, Zoltan Galaz, Radim Burget, Zdenek Smekal

This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN).


Improving Machine Hearing on Limited Data Sets

2 code implementations21 Mar 2019 Pavol Harar, Roswitha Bammer, Anna Breger, Monika Dörfler, Zdenek Smekal

In this contribution we investigate how input and target representations interplay with the amount of available training data in a music information retrieval setting.

Information Retrieval Music Information Retrieval +1

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