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  ---
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  tags:
 
 
 
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  - EEG
 
 
 
 
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  ---
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  Part of MONSTER: <https://arxiv.org/abs/2502.15122>.
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  ***CrowdsSourced*** consists of EEG data collected as part of a study investigating brain activity during a resting state task, which included two conditions: *eyes open* and *eyes closed*, each lasting 2 minutes. The dataset contains EEG recordings from 60 participants, but only 13 successfully completed both conditions. The recordings were captured using 14-channel EEG headsets—specifically the *Emotiv EPOC+*, *EPOC X*, and *EPOC* devices. These devices provide high-quality, wireless brainwave data that is ideal for analyzing resting-state brain activity [1].
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  The data was initially recorded at a high frequency of 2048 Hz and later downsampled to 128 Hz for processing. To segment the data for analysis, we used a 2-second window (equivalent to 256 time steps) with a 32 time-step stride to capture the dynamics of brain activity while maintaining a manageable data size. The raw EEG data for the 13 participants, along with preprocessing steps, analysis scripts, and visualization tools, are openly available on the Open Science Framework [2]. This version of the dataset has been split into cross-validation folds based on participant.
 
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  ---
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  tags:
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+ - time series
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+ - time series classification
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+ - monster
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  - EEG
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+ pretty_name: CrowdSource
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+ license: other
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+ size_categories:
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+ - 10K<n<100K
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  Part of MONSTER: <https://arxiv.org/abs/2502.15122>.
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+ |CornellWhaleChallenge||
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+ |-|-:|
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+ |Category|Audio|
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+ |Num. Examples|12,289|
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+ |Num. Channels|14|
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+ |Length|256|
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+ |Sampling Freq.|128 Hz|
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+ |Num. Classes|2|
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+ |License|Other|
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+ |Citations|[1] [2]|
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+
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  ***CrowdsSourced*** consists of EEG data collected as part of a study investigating brain activity during a resting state task, which included two conditions: *eyes open* and *eyes closed*, each lasting 2 minutes. The dataset contains EEG recordings from 60 participants, but only 13 successfully completed both conditions. The recordings were captured using 14-channel EEG headsets—specifically the *Emotiv EPOC+*, *EPOC X*, and *EPOC* devices. These devices provide high-quality, wireless brainwave data that is ideal for analyzing resting-state brain activity [1].
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  The data was initially recorded at a high frequency of 2048 Hz and later downsampled to 128 Hz for processing. To segment the data for analysis, we used a 2-second window (equivalent to 256 time steps) with a 32 time-step stride to capture the dynamics of brain activity while maintaining a manageable data size. The raw EEG data for the 13 participants, along with preprocessing steps, analysis scripts, and visualization tools, are openly available on the Open Science Framework [2]. This version of the dataset has been split into cross-validation folds based on participant.