A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface
| العنوان: | A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface |
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| المؤلفون: | Dheeraj Rathee, Haider Raza, Sujit Roy, Girijesh Prasad |
| المصدر: | Scientific Data, Vol 8, Iss 1, Pp 1-10 (2021) Rathee, D, Raza, H, Roy, S & Prasad, G 2021, ' A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface ', Scientific Data, vol. 8, no. 1, 120 . https://doi.org/10.1038/s41597-021-00899-7Test Scientific Data |
| بيانات النشر: | Nature Portfolio, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Adult, Male, Statistics and Probability, Data Descriptor, Computer science, Speech recognition, Science, Neuroimaging, Brain imaging, 02 engineering and technology, Motor Activity, Library and Information Sciences, Pattern Recognition, Automated, Education, Machine Learning, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Motor imagery, Cognition, 0202 electrical engineering, electronic engineering, information engineering, medicine, Humans, Brain–computer interface, medicine.diagnostic_test, Subtraction, Magnetoencephalography, Computer Science Applications, Brain-Computer Interfaces, Pattern recognition (psychology), 020201 artificial intelligence & image processing, Female, Statistics, Probability and Uncertainty, Biomedical engineering, 030217 neurology & neurosurgery, Mental image, Information Systems |
| الوصف: | Recent advancements in magnetoencephalography (MEG)-based brain-computer interfaces (BCIs) have shown great potential. However, the performance of current MEG-BCI systems is still inadequate and one of the main reasons for this is the unavailability of open-source MEG-BCI datasets. MEG systems are expensive and hence MEG datasets are not readily available for researchers to develop effective and efficient BCI-related signal processing algorithms. In this work, we release a 306-channel MEG-BCI data recorded at 1KHz sampling frequency during four mental imagery tasks (i.e. hand imagery, feet imagery, subtraction imagery, and word generation imagery). The dataset contains two sessions of MEG recordings performed on separate days from 17 healthy participants using a typical BCI imagery paradigm. The current dataset will be the only publicly available MEG imagery BCI dataset as per our knowledge. The dataset can be used by the scientific community towards the development of novel pattern recognition machine learning methods to detect brain activities related to motor imagery and cognitive imagery tasks using MEG signals. Measurement(s) brain physiology trait Technology Type(s) Magnetoencephalography Factor Type(s) age group • sex Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13561976 |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2052-4463 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b642826a8c1af02867e74097976ddacTest https://doaj.org/article/275f143ab0d1404595e3d033152d8f9cTest |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....7b642826a8c1af02867e74097976ddac |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20524463 |
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