Developmental coordination disorder in children - experimental work and data annotation
Lukáš Vareka1, Petr Bruha1, Roman Moucek1
1University of West Bohemia, Univerzitni 8, 306 14, Plzen, Czech Republic.
Insights
Researchers explored electroencephalography (EEG) to aid in diagnosing developmental coordination disorder (DCD). This study collected and annotated EEG data from children with and without DCD, aiming for better diagnostic tools.
Area of Science:
- Neuroscience
- Developmental Psychology
- Biomedical Engineering
Background:
- Developmental Coordination Disorder (DCD) is a motor skill disorder impacting daily activities and academic achievement.
- Electrophysiological studies suggest potential differences in brain activity between children with and without motor coordination issues.
- The event-related potentials (ERP) technique offers a potential avenue for diagnosing DCD.
Purpose of the Study:
- To investigate the utility of electroencephalography (EEG) data for diagnosing Developmental Coordination Disorder (DCD).
- To collect and meticulously annotate raw EEG data with relevant metadata for future research and long-term data sustainability.
- To establish a foundation for potential diagnostic criteria for DCD using neurophysiological measures.
Main Methods:
- Collected electroencephalography (EEG) data from 32 school children, comprising 16 diagnosed with DCD and 16 controls.
- Annotated datasets with crucial metadata including age, gender, motor test results, and hearing thresholds, adhering to data sharing standards.
- Estimated artifact-damaged ERP trials and averaged ERP data across participants and conditions, providing analysis-ready results.
Main Results:
- Provided raw EEG data and comprehensive metadata for 32 participants (16 DCD, 16 controls).
- Included artifact estimation and averaged ERP plots to facilitate usability assessment of individual datasets.
- Ensured data annotation followed international standards for neurophysiological data sharing.
Conclusions:
- The study provides a valuable dataset and methodology for exploring EEG-based diagnosis of DCD.
- The annotated data and analysis-ready ERPs aim to promote further research into the neurophysiological underpinnings of DCD.
- This work represents a step towards utilizing electrophysiological techniques for improved diagnosis and understanding of DCD.
Background:
Developmental coordination disorder (DCD) is described as a motor skill disorder characterized by a marked impairment in the development of motor coordination abilities that significantly interferes with performance of daily activities and/or academic achievement. Since some electrophysiological studies suggest differences between children with/without motor development problems, we prepared an experimental protocol and performed electrophysiological experiments with the aim of making a step toward a possible diagnosis of this disorder using the event-related potentials (ERP) technique. The second aim is to properly annotate the obtained raw data with relevant metadata and promote their long-term sustainability.
Results:
The data from 32 school children (16 with possible DCD and 16 in the control group) were collected. Each dataset contains raw electroencephalography (EEG) data in the BrainVision format and provides sufficient metadata (such as age, gender, results of the motor test, and hearing thresholds) to allow other researchers to perform analysis. For each experiment, the percentage of ERP trials damaged by blinking artifacts was estimated. Furthermore, ERP trials were averaged across different participants and conditions, and the resulting plots are included in the manuscript. This should help researchers to estimate the usability of individual datasets for analysis.
Conclusions:
The aim of the whole project is to find out if it is possible to make any conclusions about DCD from EEG data obtained. For the purpose of further analysis, the data were collected and annotated respecting the current outcomes of the International Neuroinformatics Coordinating Facility Program on Standards for Data Sharing, the Task Force on Electrophysiology, and the group developing the Ontology for Experimental Neurophysiology. The data with metadata are stored in the EEG/ERP Portal.
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