Data for "Eye Movement Analysis for Activity Recognition Using Electrooculography"

DOI

This dataset was recorded to investigate the problem of recognising common office activities from eye movements. The experimental scenario involved five office-based activities - copying a text, reading a printed paper, taking handwritten notes, watching a video, and browsing the Web - and periods during which participants took a rest (the NULL class). The dataset has the following characteristics:

~8 hours of eye movement data recorded using a wearable Electrooculography (EOG) system 8 participants (2 female, 6 male), aged between 23 and 31 years 2 experimental runs for each participant, each run involving them in a sequence of five different, randomly ordered office activities and a period of rest separate horizontal and vertical EOG channels, joint sampling frequency of 128Hz fully ground truth annotated (5 activity classes plus NULL)

The data is only to be used for non-commercial scientific purposes.

Identifier
DOI https://doi.org/10.18419/darus-3135
Related Identifier IsCitedBy https://doi.org/10.1145/1620545.1620552
Related Identifier IsCitedBy https://doi.org/10.1109/TPAMI.2010.86
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/darus-3135
Provenance
Creator Bulling, Andreas ORCID logo
Publisher DaRUS
Contributor Bulling, Andreas
Publication Year 2022
Funding Reference Feodor Lynen Research Fellowship of the Alexander von Humboldt Foundation, Germany ; Alexander von Humboldt Foundation
Rights info:eu-repo/semantics/openAccess
OpenAccess true
Contact Bulling, Andreas (Universität Stuttgart)
Representation
Resource Type Raw signals; Dataset
Format text/plain; application/matlab-mat
Size 134; 695509; 1117820; 1610934; 828243; 1635399; 1644064; 1535193; 1498876; 1557301; 1345571; 1601233; 1414244; 1366090; 1326795; 1485578; 1399872; 3005
Version 1.0
Discipline Other