activity
20192024
most citedEvaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease

363 citations · 767 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2024★ 363 cited

Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease

Peter Drotár, Jiří Mekyska, Irena Rektorová +3

Objective: We present the PaHaW Parkinson's disease handwriting database, consisting of handwriting samples from Parkinson's disease (PD) patients and healthy controls. Our goal is…

cs.HC2024★ 4 cited

Assessment of Developmental Dysgraphia Utilising a Display Tablet

Jiri Mekyska, Zoltan Galaz, Katarina Safarova +9

Even though the computerised assessment of developmental dysgraphia (DD) based on online handwriting processing has increasing popularity, most of the solutions are based on a setu…

eess.IV2023★ 2 cited

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

Zoltan Galaz, Jiri Mekyska, Jan Mucha +6

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. In th…

eess.SY2023★ 3 cited

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

Jan Mucha, Zoltan Galaz, Jiri Mekyska +5

Parkinson's disease (PD) is a common neurodegenerative disorder with a prevalence rate estimated to 2.0% for people aged over 65 years. Cardinal motor symptoms of PD such as rigidi…

cs.SD2022★ 19 cited

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

Jiri Mekyska, Zdenek Smekal, Zoltan Galaz +4

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

eess.SP2022★ 46 cited

Contribution of Different Handwriting Modalities to Differential Diagnosis of Parkinson's Disease

Peter Drotár, Jiří Mekyska, Zdeněk Smékal +3

In this paper, we evaluate the contribution of different handwriting modalities to the diagnosis of Parkinson's disease. We analyse on-surface movement, in-air movement and pressur…

cs.SD2022

Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation

Jan Mucha, Zoltan Galaz, Jiri Mekyska +9

Up to 90 % of patients with Parkinson's disease (PD) suffer from hypokinetic dysarthria (HD). In this work, we analysed the power of conventional speech features quantifying imprec…

cs.SD2022★ 129 cited

Robust and Complex Approach of Pathological Speech Signal Analysis

Jiri Mekyska, Eva Janousova, Pedro Gomez-Vilda +8

This paper presents a study of the approaches in the state-of-the-art in the field of pathological speech signal analysis with a special focus on parametrization techniques. It pro…

cs.SD2022★ 33 cited

Assessing Progress of Parkinson s Disease Using Acoustic Analysis of Phonation

Jiri Mekyska, Zoltan Galaz, Zdenek Mzourek +9

This paper deals with a complex acoustic analysis of phonation in patients with Parkinson's disease (PD) with a special focus on estimation of disease progress that is described by…

cs.SD2019★ 68 cited

Towards Robust Voice Pathology Detection

Pavol Harar, Zoltan Galaz, Jesus B. Alonso-Hernandez +3

Automatic objective non-invasive detection of pathological voice based on computerized analysis of acoustic signals can play an important role in early diagnosis, progression track…

eess.AS2019★ 96 cited

Voice Pathology Detection Using Deep Learning: a Preliminary Study

Pavol Harar, Jesus B. Alonso-Hernandez, Jiri Mekyska +3

This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN). We used voice recordings of sustained vowel /a/ produced at normal p…

cs.SD2019★ 4 cited

Improving Machine Hearing on Limited Data Sets

Pavol Harar, Roswitha Bammer, Anna Breger +2

Convolutional neural network (CNN) architectures have originated and revolutionized machine learning for images. In order to take advantage of CNNs in predictive modeling with audi…