A Review and Classification of Widely used Offline Brain Datasets
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 2
Abstract
Brain Computer Interfaces (BCI) are a natural extension to Human Computer Interaction (HCI) technologies. BCI is especially useful for people suffering from diseases, such as Amyotrophic Lateral Sclerosis (ALS) which cause motor disabilities in patients. To evaluate the effectiveness of BCI in different paradigms, the need of benchmark BCI datasets is increasing rapidly. Although, such datasets do exist, a comparative study of such datasets is not available to the best of our knowledge. In this paper, we provided a comprehensive overview of various BCI datasets. We briefly describe the characteristics of these datasets and devise a classification scheme for them. The comparative study provides feature extractors and classifiers used for each dataset. Moreover, potential use-cases for each dataset are also provided.
Authors and Affiliations
Muhammad Wasim, Farheen Ramzan, Usman Ghani Khan, Waqar Mahmood
Keywords
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- EP ID EP277055
- DOI 10.14569/IJACSA.2018.090254
- Views 60
- Downloads 0
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