
This dataset contains multimodal data acquired for the MUSMET project, which is funded under the Horizon Europe Framework Program (HORIZON) (grant agreement 101184379). For more information about the project, visit https://musmet.eu/. In this dataset, a musician’s performance was recorded in the PatchXR virtual environment. Simultaneously, EEG data was collected using the .g.tec Unicorn Hybrid Black system. The musician performed 8 pieces of music, each expressing one of four emotions: anger, sadness, happiness, and relaxation. These emotions were repeated twice in a randomized order across the sessions. The dataset is organized into 4 folders: VR MUSMET recording Happy VR MUSMET recording Sad VR MUSMET recording Relaxed VR MUSMET recording Anger Each folder contains data from two performances of the corresponding emotion, stored in subfolders labeled V1 and V2. The root folder also includes video recordings. The EEG data is provided in two open formats: BDF and CSV. Each EEG file contains 8 channels of EEG data and an empty trigger channel.
| 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 |
