Who we are

The Brain Diseases Analysis Laboratory (BDALab) is an international multidisciplinary research group focusing on the research and development of digital biomarkers.

What we do

Using state-of-the-art techniques of biomedical signal processing, data science, and wearable technologies we provide experts with digital biomarkers facilitating diagnosis, assessment and monitoring of a large spectrum of disorders such as Parkinson’s disease, Alzheimer’s disease, Lewy body dementia, neurodevelopmental dysgraphia, etc.

What we offer

We offer a design and implementation of software that can objectively analyse different modalities such as speech, handwriting, and sleep. All solutions provided by BDALab are individualized depending on customer’s requirements.

Our Mission

To provide experts with trustworthy and interpretable digital biomarkers.

Our Vision

To improve patients quality of life.

Our Skills

We mainly deal with speech signal and online handwriting processing, but besides we process sleep data from actigraphs, develop mHealth apps etc.

Digital Biomarkers

Machine Learning

Signal Processing

mHealth Apps

Our Team

Meet our team
Projects we have done
Cooperating partners

Our Partners

Applied Neuroscience research group, CEITEC
FN Brno
Hospital de Mataró
University of Haifa
Edinburgh Napier University
University of Antioquia
University of Arizona
University of Szeged
Universita degli Studi di Bari Aldo Moro
Universitat Wien
Comenius University in Bratislava
The University of Edinburgh
University Hospital Olomouc
Czech National eHealth Center
Czech Academy of Sciences
Universidad Rey Juan Carlos
Universitat Pompeu Fabra

Our Research Topics

See what we are currently working on.

Speech/voice and audio processing

    speech/voice and audio processing
  • Diagnosis of Lewy body diseases in the prodromal stage based on acoustic analysis of speech/voice. (in cooperation with CEITEC, FNUSA)
  • Research of a new method of hypokinetic dysarthria treatment based on the repetitive transcranial magnetic stimulation and transcranial direct current stimulation. (in cooperation with CEITEC, FNUSA)
  • Differential analysis of several neurodegenerative diseases in a multilingual (CZ, US, HU) cohort. (in cooperation with CEITEC, FNUSA, UA, USZ)
  • Automatic discrimination between hypokinetic dysarthria and apraxia of speech. (in cooperation with CEITEC, FNUSA, UA)
  • Neural correlates of speech disorders in Parkinson’s disease. (in cooperation with CEITEC, FNUSA)
  • Monitoring the effect of pharmacological treatment on speech in patients with Parkinson’s disease. (in cooperation with CEITEC, FNUSA)
  • Prediction of cognitive decline in patients with Parkinson’s disease. (in cooperation with CEITEC, FNUSA)
  • Research of new speech/voice pathology parameterisation methods. (in cooperation with UPM, URJC, UPF, UED)
  • Objectivization of the dysarthric Test 3F. (in cooperation with FNBRNO)
  • Development of a remote and passive speech analysis system. (in cooperation with CEITEC, FNUSA)
  • Automatic assessment of voice pathology according to the GRBAS scale. (in cooperation with UNIVIE, UNIBA)
  • Individualisation of musicotherapy in patients with epilepsy. (in cooperation with CEITEC, FNUSA)

Online handwriting processing

    online handwriting processing
  • Design of a new scale providing an objective assessment of graphomotor and handwriting difficulties in school-aged children. (in cooperation with MU, CAS, UPF, ULPGC)
  • Design of new features quantifying manifestations associated with developmental dysgraphia. (in cooperation with MU, CAS, UPF, ULPGC)
  • Development of software enabling objective assessment of graphomotor difficulties. (in cooperation with MU, CAS, PROPSYCO)
  • Research of a new method of Parkinson's disease dysgraphia treatment based on the repetitive transcranial magnetic stimulation. (in cooperation with CEITEC, FNUSA)
  • Diagnosis of Parkinson's disease dysgraphia in a multilingual (CZ, US, HU, CO) cohort. (in cooperation with CEITEC, FNUSA, UA, USZ, TUKE, UDEA)
  • Assessment of cognitive functions in patients with Lewy body diseases. (in cooperation with CEITEC, FNUSA)
  • Design of new features (e.g. employing fractional-order derivatives, modulation spectra, tunable q-factor wavelet transform) enabling advanced analysis of online handwriting. (in cooperation with UPF, ULPGC, EHU)
  • Diagnosis of handwriting difficulties based on convolutional neural networks. (in cooperation with TUKE, MU, CAS)

Other topics

    other topics
  • Development of remote and passive Parkinson’s disease monitoring system. (in cooperation with CEITEC, FNUSA)
  • Sleep analysis based on actigraphy. (in cooperation with CEITEC, FNUSA, UED)
  • Diagnosis of Lewy body diseases in the prodromal stage based on data from actigraphy. (in cooperation with CEITEC, FNUSA)
  • Analysis of hypomimia in patients with Parkinson’s disease based on action units. (in cooperation with CEITEC, FNUSA)
  • Development of mobile apps applied in the field of Health 4.0. (in cooperation with CEITEC, FNUSA)
  • Research of deep learning approaches enabling better learning on small-sample data sets. (in cooperation with UNIVIE)

We were the first who quantified in-air movement in parkinsonic dysgraphia analysis.

Our Projects

Selected projects we participated on.

  • LX22NPO5107 - National institute for Neurological Research (2022-2025, Czech Ministry of Education, Youth and Sports)
  • NU23J-04-00005 - Language and Lewy body diseases: Sentence comprehension problems and modifying noninvasive brain stimulation treatment (2023-2026, Czech Ministry of Health)
  • NU22J-04-00074 - Home-based non-invasive brain stimulation in combination with Lee Silverman Voice Treatment on hypokinetic dysarthria in Parkinson's disease (2022-2025, Czech Ministry of Health)
  • NU20-04-00294 - Diagnostics of Lewy body diseases in prodromal stage based on multimodal data analysis (2020-2023, Czech Ministry of Health)
  • niCE-life - Development of an integrated concept for the deployment of innovative technologies and services allowing independent living of frail elderly (2019-2021, Interreg CENTRAL EUROPE)
  • 18-16835S - Research of advanced developmental dysgraphia diagnosis and rating methods based on quantitative analysis of online handwriting and drawing (2018-2020, Czech Science Foundation)
  • CoBeN - Novel Network-Based Approaches for Studying Cognitive Dysfunction in Behavioral Neurology (2017-2021, Marie Skłodowska-Curie Research and Innovation Staff Exchange)
  • 16-30805A - Effects of non-invasive brain stimulation on hypokinetic dysarthria, micrographia, and brain plasticity in patients with Parkinson's disease (2016-2019, Czech Ministry of Health)
  • NT13499 - Speech, its impairment and cognitive performance in Parkinson's disease (2012-2015, Czech Ministry of Health)
  • GAP102/12/1104 - Study of metabolism and localization of high grade glioma using MR imaging techniques (2012-2014, Czech Science Foundation)
  • COST IC1206 - De-Identification for Privacy Protection in Multimedia Content (2013-2016, European Union)
  • OC08057 - Analysis and Enhancement of Speech and Image Signals form Noise for Cross-Modal Analysis of Verbal and Non-verbal Communication (2008-2010, Ministry of Education, Youth and Sports)
  • EE. - Support for incorporating R&D teams in international cooperation in the area of image and audio signal processing (2011-2014, Ministry of Education, Youth and Sports)


Use our databases and software for your research.

Parkinson's Disease Handwriting Database (PaHaW)


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 University Hospital in Brno, Czech Republic.

handwriting template

Each subject was asked to complete a handwriting task according to the prepared filled template at a comfortable speed. The completed task sheet is depicted on the right. The completed template was shown to the subjects; no restrictions about the number of repetitions of syllables/words in tasks or their height were given.

A tablet was overlaid with a empty paper template (containing only printed lines and square box specifying area for Archimedean spiral), and a conventional ink pen was held in a normal fashion, allowing for immediate full visual feedback. The signals were recorded using the Intuos 4M (Wacom technology) digitizing tablet with 150 Hz sampling frequency.

Digitized signals were acquired during the movements executed while exerting pressure on the writing surface and during the movement above the writing surface. We denote these signals as on-surface movement and in-air movement, respectively. The perpendicular pressure exerted on the tablet surface was also recorded. The recordings started when the pen touched the surface of the digitizer and finished when the task was completed. the tablet captured the following dynamic features (time-sequences): x-coordinate; y-coordinate; time stamp; button status; pressure; tilt; and elevation. Button status is a binary variable, being 0 for pen-up state (in-air movement) and 1 for pen-down state (on-surface movement).

Access to the database

Please fill in a license agreement that can be downloaded in DOCX or PDF and send it to mekyska@vut.cz with CC to peter.drotar@tuke.sk and irena.rektorova@fnusa.cz. You will consequently get an access to the database.


Check what's going on at our laboratory.