Academic Journal
Review of public motor imagery and execution datasets in brain-computer interfaces
| العنوان: | Review of public motor imagery and execution datasets in brain-computer interfaces |
|---|---|
| المؤلفون: | Daeun Gwon, Kyungho Won, Minseok Song, Chang S. Nam, Sung Chan Jun, Minkyu Ahn |
| المصدر: | Frontiers in Human Neuroscience, Vol 17 (2023) |
| بيانات النشر: | Frontiers Media S.A. |
| سنة النشر: | 2023 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | brain-computer interface (BCI), motor imagery, motor execution, public dataset, data quality, meta-analysis, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571 |
| الوصف: | The demand for public datasets has increased as data-driven methodologies have been introduced in the field of brain-computer interfaces (BCIs). Indeed, many BCI datasets are available in various platforms or repositories on the web, and the studies that have employed these datasets appear to be increasing. Motor imagery is one of the significant control paradigms in the BCI field, and many datasets related to motor tasks are open to the public already. However, to the best of our knowledge, these studies have yet to investigate and evaluate the datasets, although data quality is essential for reliable results and the design of subject− or system-independent BCIs. In this study, we conducted a thorough investigation of motor imagery/execution EEG datasets recorded from healthy participants published over the past 13 years. The 25 datasets were collected from six repositories and subjected to a meta-analysis. In particular, we reviewed the specifications of the recording settings and experimental design, and evaluated the data quality measured by classification accuracy from standard algorithms such as Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA) for comparison and compatibility across the datasets. As a result, we found that various stimulation types, such as text, figure, or arrow, were used to instruct subjects what to imagine and the length of each trial also differed, ranging from 2.5 to 29 s with a mean of 9.8 s. Typically, each trial consisted of multiple sections: pre-rest (2.38 s), imagination ready (1.64 s), imagination (4.26 s, ranging from 1 to 10 s), the post-rest (3.38 s). In a meta-analysis of the total of 861 sessions from all datasets, the mean classification accuracy of the two-class (left-hand vs. right-hand motor imagery) problem was 66.53%, and the population of the BCI poor performers, those who are unable to reach proficiency in using a BCI system, was 36.27% according to the estimated accuracy distribution. Further, we analyzed the CSP features and found that each ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1662-5161 |
| Relation: | https://www.frontiersin.org/articles/10.3389/fnhum.2023.1134869/full; https://doaj.org/toc/1662-5161; https://doaj.org/article/73b268d26a3049de98418f407f8cd573 |
| DOI: | 10.3389/fnhum.2023.1134869 |
| الاتاحة: | https://doi.org/10.3389/fnhum.2023.1134869 https://doaj.org/article/73b268d26a3049de98418f407f8cd573 |
| رقم الانضمام: | edsbas.EBDC4E75 |
| قاعدة البيانات: | BASE |
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