Zdenek Smekal

Zdenek Smekal
Brno University of Technology · Department of Telecommunications

Prof.

About

129
Publications
32,266
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,581
Citations
Introduction
Additional affiliations
November 1991 - April 2015
Brno University of Technology
Position
  • Professor

Publications

Publications (129)
Article
Full-text available
Parkinson's disease dysgraphia (PDYS), one of the earliest signs of Parkinson's disease (PD), has been researched as a promising biomarker of PD and as the target of a noninvasive and inexpensive approach to monitoring the progress of the disease. However, although several approaches to supportive PDYS diagnosis have been proposed (mainly based on...
Preprint
This article 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 provides a~description of 92 speech features where some of them are already widely used in this field of science and some of them have not been tried yet (they come from d...
Preprint
Full-text available
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 monoloudness, monopitch or hoarse voice are usually quantified by conventional clinical interpretable features (jitter, shimmer, harmonic-to-noise ratio, etc.). This paper provides...
Preprint
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 7 different clinical scales (e.\,g. Unified Parkinson's disease rating scale or Beck depression inventory). The analysis is based on parametrization of 5 Czech vowels pr...
Preprint
Full-text available
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 imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy...
Preprint
Full-text available
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 7 different clinical scales ,e. g. Unified Parkinson's disease rating scale or Beck depression inventory. The analysis is based on parametrization of 5 Czech vowels pron...
Preprint
Full-text available
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 provides a description of 92 speech features where some of them are already widely used in this field of science and some of them have not been tried yet (they come from dif...
Article
Full-text available
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. In search towards such a robust voice pathology detection system, we investigated three distinct classifiers wit...
Article
Full-text available
The Table 3 was published incorrectly in the original publication of the article.
Article
The objective of this paper is to present the state of-the-art relating to automatic speech and voice analysis techniques as applied to the monitoring of patients suffering from Alzheimer's disease as well as to shed light on possible future research topics. This work reviews more than 90 papers in the existing literature and focuses on the main fe...
Article
Full-text available
School-aged children spend 31–60%of their time at school performing handwriting, which is a complex perceptual-motor skill composed of a coordinated combination of fine graphomotor movements. As up to 30% of them experience graphomotor difficulties (GD), timely diagnosis of these difficulties and therapeutic intervention are of great importance. At...
Article
Full-text available
Dysgraphia (D) is a complex specific learning disorder with a prevalence of up to 30%, which is linked with handwriting issues. The factors recognized for assessing these issues are legibility and performance time. Two questionnaires, the Handwriting Proficiency Screening Questionnaire (HPSQ) for teachers and its modification for children (HPSQ-C),...
Article
Full-text available
Beat detection systems are widely used in the music information retrieval (MIR) research field for the computation of tempo and beat time positions in audio signals. One of the most important parts of these systems is usually onset detection. There is an understandable tendency to employ the most accurate onset detector. However, there are options...
Article
Full-text available
Graphomotor disabilities (GD) are present in up to 30% of school-aged children and are associated with several symptoms in the field of kinematics. Although the basic kinematic features such as velocity, acceleration, and jerk were proved to effectively quantify these symptoms, a recent body of research identified that the theory of fractional calc...
Preprint
Full-text available
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. In search towards such a robust voice pathology detection system we investigated 3 distinct classifiers within su...
Preprint
Full-text available
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 pitch from German corpus Saarbruecken Voice Database (SVD). This corpus contains voice recordings and electroglottograph signals of more than 2 000 speakers. The idea behi...
Preprint
Recent, extremely successful methods in deep learning, such as convolutional neural networks (CNNs) have originated in machine learning for images. When applied to music signals and related music information retrieval (MIR) problems, researchers often apply standard FFT-based signal processing methods in order to create an image from the raw audio...
Conference Paper
The majority of Parkinson's disease (PD) patients suffer from handwriting abnormalities commonly called as Parkinsonic dysgraphia. Several approaches of PD dysgraphia analysis exist, e.g. based on online handwriting processing. However, a small and unilingual cohort of PD patients is often an issue in quantitative PD dysgraphia analysis studies. Th...
Presentation
Full-text available
The majority of Parkinson’s disease (PD) patients suffer from handwriting abnormalities commonly called as Parkinsonic dysgraphia. Several approaches of PD dysgraphia analysis exist, e.g. based on online handwriting processing. However, a small and unilingual cohort of PD patients is often an issue in quantitative PD dysgraphia analysis studies. Th...
Article
Full-text available
Parkinson's disease dysgraphia affects the majority of Parkinson's disease (PD) patients and is the result of handwriting abnormalities mainly caused by motor dysfunctions. Several effective approaches to quantitative PD dysgraphia analysis, such as online handwriting processing, have been utilized. In this study, we aim to deeply explore the impac...
Article
Full-text available
Hypokinetic dysarthria (HD) and freezing of gait (FOG) are both axial symptoms that occur in patients with Parkinson’s disease (PD). It is assumed they have some common pathophysiological mechanisms and therefore that speech disorders in PD can predict FOG deficits within the horizon of some years. The aim of this study is to employ a complex quant...
Article
Full-text available
Hypokinetic dysarthria, which is associated with Parkinson's disease (PD), affects several speech dimensions, including phonation. Although the scientific community has dealt with a quantitative analysis of phonation in PD patients, a complex research revealing probable relations between phonatory features and progress of PD is missing. Therefore,...
Conference Paper
Parkinson's disease (PD) is one of the most frequent neurodegenerative disorder with progressive decline in several motor and non-motor skills. Due to time-consuming and partially subjective conventional PD diagnosis, several more effective approaches based on signal processing and machine learning, e.g. online handwriting analysis, have been propo...
Conference Paper
Full-text available
Determining the place of origin of the musical compositions is a modern area of research in the field of music information retrieval (MIR). The musical interpretation of one piece carries a variety of author's intentions that influence the musical character of the resulting composition. These aspects may include rhythm, dynamics, timbre, or tonalit...
Article
Full-text available
Introduction: Hypokinetic dysarthria (HD) is a common symptom of Parkinson's disease (PD) which does not respond well to PD treatments. We investigated acute effects of repetitive transcranial magnetic stimulation (rTMS) of the motor and auditory feedback area on HD in PD using acoustic analysis of speech. Methods: We used 10 Hz and 1 Hz stimula...
Article
Full-text available
Neurodegenerative pathologies as Parkinson's Disease (PD) show important distortions in speech, affecting fluency, prosody, articulation and phonation. Classically, measurements based on articulation gestures altering formant positions, as the Vocal Space Area (VSA) or the Formant Centralization Ratio (FCR) have been proposed to measure speech dist...
Conference Paper
Parkinson’s disease (PD) is the second most frequent neurodegenerative disorder. One typical hallmark of PD is disruption in execution of practised skills such as handwriting. This paper introduces a new methodology of kinematic features calculation based on fractional derivatives applied on PD handwriting. Discrimination power of basic kinematic f...
Poster
Full-text available
In search towards a robust voice pathology detection system (VPD), we investigated three distinct classifiers within supervised learning and anomaly detection paradigms on data from four different databases with the aim to: 1) Investigate whether it is possible to build a robust VPD system using currently available resources and mentioned classifie...
Presentation
Full-text available
Lots of voice pathologies are not being diagnosed and treated due to a lack of training, time or appropriate equipment of general practitioners. We are aiming for early diagnosis using quick preventive tests, without extensive training and without the need for expensive equipment. Which would point the patient to a specialized voice therapist if ne...
Article
Full-text available
Aim: The research described is intended to give a description of articulation dynamics as a correlate of the kinematic behavior of the jaw-tongue biomechanical system, encoded as a probability distribution of an absolute joint velocity. This distribution may be used in detecting and grading speech from patients affected by neurodegenerative illness...
Conference Paper
Full-text available
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 pitch from German corpus Saarbruecken Voice Database (SVD). This corpus contains voice recordings and electroglottograph signals of more than 2 000 speakers. The idea behi...
Conference Paper
Hypokinetic dysarthria (HD) and freezing of gait (FOG) are frequent symptoms of Parkinson's disease (PD). The aim of this work is to reveal pathological mechanisms common for HD and FOG, and use acoustic analysis of dysarthric speech to assess the gait difficulties in PD. We used a correlation analysis to investigate a relationship between speech f...
Conference Paper
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 imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy s...
Conference Paper
Neurodegenerative pathologies produce important distortions in speech. Parkinson’s Disease (PD) leaves marks in fluency, prosody, articulation and phonation. Certain measurements based in configurations of the articulation organs inferred from formant positions, as the Vocal Space Area (VSA) or the Formant Centralization Ratio (FCR) have been class...
Article
Developmental dysgraphia, being observed among 10–30% of school-aged children, is a disturbance or difficulty in the production of written language that has to do with the mechanics of writing. The objective of this study is to propose a method that can be used for automated diagnosis of this disorder, as well as for estimation of difficulty level...
Article
Background Impairment of speech prosody is characteristic for Parkinson's disease (PD) and does not respond well to dopaminergic treatment. Objectives We assessed whether baseline acoustic parameters, alone or in combination with other predominantly non-dopaminergic symptoms may predict global cognitive decline as measured by the Addenbrooke's cog...
Chapter
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 monoloudness, monopitch or hoarse voice are usually quantified by conventional clinical interpretable features (jitter, shimmer, harmonic-to-noise ratio, etc.). This paper provides...
Article
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 to show that kinematic features and pressure features in handwriting can be used for the differential diagnosis of PD. Methods and material: The database contains rec...
Article
Background and objective: Hypokinetic dysarthria (HD) is a frequent speech disorder associated with idiopathic Parkinson's disease (PD). It affects all dimensions of speech production. One of the most common features of HD is dysprosody that is characterized by alterations of rhythm and speech rate, flat speech melody, and impairment of speech inte...
Data
Full-text available
The Parkinson's Disease Handwriting Database (PaHaW) consists of multiple handwriting samples from 37 parkinsonian patients (19 men/18 women) and 38 gender and age matched controls (20 men/18 women). The database was acquired in cooperation with the Movement Disorders Center at the First Department of Neurology, Masaryk University and St. Anne's Un...
Article
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 provides a description of 92 speech features where some of them are already widely used in this field of science and some of them have not been tried yet (they come from dif...
Code
Analysis of dysarthric speech is usually performed in combination with some form of visualization of parametric space computed in direction of extracting clinically interpretable information about speech production deterioration. This toolbox (Dysarthric Speech Visualization tool – DSV tool) enables users to visualize several world-renown methods s...
Article
Feature selection is a significant part of many machine learning applications dealing with small-sample and high-dimensional data. Choosing the most important features is an essential step for knowledge discovery in many areas of biomedical informatics. The increased popularity of feature selection methods and their frequent utilisation raise chall...
Conference Paper
Full-text available
This paper deals with an acoustic analysis of hypokinetic dysarthria in patients with Parkinson's disease (PD). The analysis is based on parametrization of five basic Czech vowels using conventional features and parameters based on empirical mode decomposition (EMD). Experimental dataset consists of 84 PD patients with different disease progress an...
Code
In the field of biomedical signal processing (such as the speech signal processing, hand-written text processing, etc.), it often happens that the result of the parametrization process (parametrization serves us to quantify the useful information stored in the data with so called parameters) is a high-dimensional parametrization space. It describes...
Code
Preliminary statistical analysis is used as a tool to obtain a statistical insight into the analysed dataset. In the field of pathological signal processing the common methodology is to perform so called parametrization process in order to extract clinically useful information from the data to describe the deterioration of the speech production. Th...
Conference Paper
Full-text available
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 7 different clinical scales (e. g. Unified Parkinson's disease rating scale or Beck depression inventory). The analysis is based on parametrization of 5 Czech vowels pro...
Conference Paper
Full-text available
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 pressure exerted on the tablet surface. Especially in-air movement and pressure-based features have been rarely taken into account in previous studies. We show that pressure and...
Article
The feature selection is inevitable part of machine learning techniques in biomedical engineering and bioinformatics. Feature selection methods are used to select the most discriminative features, e.g. for disease classification. Even if there are plenty of feature selection methods the stability of these algorithms is still open question. Another...
Article
Full-text available
This work discusses fully automated extraction of brain tumor and edema in 3D MR volumes. The goal of this work is the extraction of the whole pathological area using such an algorithm that does not require a human intervention. For the good visibility of these kinds of tissues both T2-weighted and FLAIR images were used. The proposed method was te...
Article
Background and Objective Parkinson's disease (PD) is the second most common neurodegenerative disease affecting significant portion of elderly population. One of the most frequent hallmarks and usually also the first manifestation of PD is deterioration of handwriting characterized by micrographia and changes in kinematics of handwriting. There is...
Article
Full-text available
Parkinson's disease (PD) is a neurodegenerative disorder which impairs motor skills, speech, and other functions such as behavior, mood, and cognitive processes. One of the most typical clinical hallmarks of PD is handwriting deterioration, usually the first manifestation of PD. The aim of this study is twofold: (a) to find a subset of handwriting...
Article
Aim: The aim of this study was to assess micrographia in patients with Parkinson's disease (PD) as compared to healthy controls (HC) using a digitizing tablet Methods: We included 40 PD (mean 68.6 +/- 11.36 years, duration of illness 8.02 +/- 4.79 years) and 40 age- and sex-matched HC (mean 62.55 +/- 11. 22 years). All subjects were right-handed, w...
Conference Paper
One of the most frequent clinical hallmarks of Parkinson's disease (PD) is micrographia. Micrographia in PD is characterized by the decreased letter size and by changes in the kinematic aspects including increased movement time, decreased velocities and accelerations, and increased number of changes in velocity and acceleration. Based on the litera...
Conference Paper
Full-text available
Parkinsons disease (PD) is neurodegenerative disorder with very high prevalence rate occurring mainly among elderly. One of the most typical symptoms of PD is deterioration of handwriting that is usually the first manifestation of Parkinsons disease. In this study, a new modality — in-air trajectory during handwriting — is proposed to efficiently d...
Conference Paper
This article deals with methods for automatic detection of moving objects in non-standard situations in secure areas, such as nuclear power plants, storage of hazardous materials, etc. Speed and direction, respectively, slow motion to a stop is detected for the monitored object. Specifically: the automatic detection of movement in the opposite dire...