Characterization and reconstruction of VOG noise with power spectral density analysis
Författare
Summary, in English
Characterizing noise in eye movement data is important for data analysis, as well as for the comparison of research results across systems. We present a method that characterizes and reconstructs the noise in eye movement data from video-oculography (VOG) systems taking into account the uneven sampling in real recordings due to track loss and inherent system features. The proposed method extends the Lomb-Scargle periodogram, which is used for the estimation of the power spectral density (PSD) of unevenly sampled data [Hocke and Kampfer 2009]. We estimate the PSD of fixational eye movement data and reconstruct the noise by applying a random phase to the inverse Fourier transform so that the reconstructed signal retains the amplitude of the original noise at each frequency. We apply this method to the EMRA/COGAIN Eye Data Quality Standardization project's dataset, which includes recordings from 11 commercially available VOG systems and a Dual Pukinje Image (DPI) eye tracker. The reconstructed noise from each VOG system was superimposed onto the DPI data and the resulting eye movement measures from the same original behaviors were compared.
Avdelning/ar
Publiceringsår
2016-03-14
Språk
Engelska
Sidor
217-220
Publikation/Tidskrift/Serie
Proceedings - ETRA 2016: 2016 ACM Symposium on Eye Tracking Research and Applications
Volym
14
Dokumenttyp
Konferensbidrag
Förlag
Association for Computing Machinery (ACM)
Ämne
- Other Humanities not elsewhere specified
- Computer and Information Science
Nyckelord
- Eye tracking
- Noise modeling
- Power spectral analysis
Conference name
9th Biennial ACM Symposium on Eye Tracking Research and Applications, ETRA 2016
Conference date
2016-03-14 - 2016-03-17
Conference place
Charleston, United States
Status
Published
Projekt
- Eye Data Quality Standardisation
ISBN/ISSN/Övrigt
- ISBN: 9781450341257