--- tags: - time series - time series classification - monster - EEG pretty_name: STEW license: cc-by-4.0 size_categories: - 10K. |STEW|| |-|-:| |Category|EEG| |Num. Examples|28,512| |Num. Channels|14| |Length|256| |Sampling Freq.|128 Hz| |Num. Classes|2| |License|[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)| |Citations|[1] [2]| ***STEW*** comprises raw EEG recordings from 48 participants involved in a multitasking workload experiment [1]. Additionally, the subjects' baseline brain activity at rest was recorded before the test. The data was captured using the Emotiv Epoc device with a sampling frequency of 128Hz and 14 channels, resulting in 2.5 minutes of EEG recording for each case. Participants were instructed to assess their perceived mental workload after each stage using a rating scale ranging from 1 to 9, and these ratings are available in a separate file. The dataset has been divided into cross-validation folds based on individual participants. Additionally, binary class labels have been assigned to the data, categorizing workload ratings above 4 as "high" and those below or equal to 4 as "low". We utilize these labels for our specific problem. STEW can be accessed upon request through the IEEE DataPort [2]. The processed dataset consists of 28,512 multivariate time series each of length 256 (i.e., representing 2 seconds of data at 128 Hz). [1] Wei Lun Lim, Olga Sourina, and Lipo Wang. (2018). STEW: Simultaneous task EEG workload data set. *IEEE Transactions on Neural Systems and Rehabilitation Engineering*, 26(11):2106–2114. [2] Wei Lun Lim, Olga Sourina, and Lipo Wang. (2020). STEW: Simultaneous task EEG workload data set. https://ieee-dataport.org/open-access/stew-simultaneous-task-eeg-workload-dataset. CC BY 4.0.