Downloads provided by UsageCounts
The data accompanies the research described in yet unpublished paper: "On the influence of aging on classification performance in the visual EEG oddball paradigm using statistical and temporal features" by Omejc, N., Peskar, M., Miladinović, A., Kavcic, V., Džeroski, S., Marusic, U. The package includes raw data, that were measured by 32-channel EEG set and stored as hpf5 file, preprocessed data. that were preprocessed using custom scripts that utilize EEGLAB and its plugins, and data that was at the end used in the classification task and includes two types of datasets, one with temporal features and another with ERP statistical features, as in more detail described in the paper. Additionally, the package includes locations of 32 channels on the head, the event mappings for both the older and the younger group, as well as some general information about the subjects.
machine learning, classification, aging, EEG, BCI, visual oddball study, electroencephalography
machine learning, classification, aging, EEG, BCI, visual oddball study, electroencephalography
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 20 | |
| downloads | 82 |

Views provided by UsageCounts
Downloads provided by UsageCounts