Search Results for author: Jiri Mekyska

Found 16 papers, 0 papers with code

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.

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.


Contribution of the Temperature of the Objects to the Problem of Thermal Imaging Focusing

no code implementations30 Mar 2022 Virginia Espinosa-Duró, Marcos Faundez-Zanuy, Jiri Mekyska

When focusing an image, depth of field, aperture and distance from the camera to the object, must be taking into account, both, in visible and in infrared spectrum.

A Naturalistic Database of Thermal Emotional Facial Expressions and Effects of Induced Emotions on Memory

no code implementations29 Mar 2022 Anna Esposito, Vincenzo Capuano, Jiri Mekyska, Marcos Faundez-Zanuy

This work defines a procedure for collecting naturally induced emotional facial expressions through the vision of movie excerpts with high emotional contents and reports experimental data ascertaining the effects of emotions on memory word recognition tasks.

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.


Multi-focus thermal image fusion

no code implementations16 Mar 2022 Radek Benes, Pavel Dvorak, Marcos Faundez-Zanuy, Virginia Espinosa-Duro, Jiri Mekyska

To the best of our knowledge, this is the first work devoted to multi-focus thermal image fusion.

A multimodal approach for Parkinson disease analysis

no code implementations10 Mar 2022 Marcos Faundez-Zanuy, Antonio Satue-Villar, Jiri Mekyska, Viridiana Arreola, Pilar Sanz, Carles Paul, Luis Guirao, Mateu Serra, Laia Rofes, Pere Clavé, Enric Sesa-Nogueras, Josep Roure

Parkinson's disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0. 1-1 %, and an annual incidence between 1. 3-2. 0/10000 inhabitants.

A Preliminary Study on Aging Examining Online Handwriting

no code implementations8 Mar 2022 Marcos Faundez-Zanuy, Enric Sesa-Nogueras, Josep Roure-Alcobé, Anna Esposito, Jiri Mekyska, Karmele López-de-Ipiña

This paper contributes to this research line analyzing a selected set of online handwriting parameters provided by a healthy group of population aged from 18 to 70 years.

Online handwriting, signature and touch dynamics: tasks and potential applications in the field of security and health

no code implementations24 Feb 2022 Marcos Faundez-Zanuy, Jiri Mekyska, Donato Impedovo

Background: An advantageous property of behavioural signals , e. g. handwriting, in contrast to morphological ones, such as iris, fingerprint, hand geometry, etc., is the possibility to ask a user for a very rich amount of different tasks.

A comparative study of in-air trajectories at short and long distances in online handwriting

no code implementations23 Feb 2022 Carlos Alonso-Martinez, Marcos Faundez-Zanuy, Jiri Mekyska

Methods In this paper, we will analyze a large set of databases (BIOSECURID, EMOTHAW, PaHaW, Oxygen-Therapy and SALT), which contain a total amount of 663 users and 17951 files.

Thermal hand image segmentation for biometric recognition

no code implementations23 Feb 2022 Xavier Font-Aragones, Marcos Faundez-Zanuy, Jiri Mekyska

In this paper we present a method to identify people by means of thermal (TH) and visible (VIS) hand images acquired simultaneously with a TESTO 882-3 camera.

Dimensionality Reduction Image Segmentation +1

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).


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