Ear Emoload Dataset

Ear-EmoLoad is an ear-EEG dataset for studying emotion and cognitive load in naturalistic listening and learning scenarios. The dataset is collected using a custom ear-worn EEG system embedded in in-ear headphones, enabling unobtrusive neural sensing during everyday tasks.Participants engaged in audio-visual learning and listening activities designed to elicit variations in emotional valenceand cognitive load. The dataset supports joint investigation of affective responses and mental workload in an e-learning–like context.Ear-EmoLoad primarily includes multi-channel ear-EEG recordings with synchronized task markers and annotations. Each data segment is labeled with emotion-related and cognitive load information, along with subject-level metadata. Preprocessing steps are applied to ensure signal quality suitable for ear-EEG analysis.This dataset is intended for research in affective computing, cognitive load assessment, wearable brain–computer interfaces, and EEG representation learning.All data were collected with informed consent and are anonymized for research use only.