Microsaccade detection using pupil and corneal reflection signals
Niehorster, Diederick C LU
and Nyström, Marcus
LU
(2018)
The 2018 ACM Symposium on Eye Tracking Research & Applications
- Abstract
- In contemporary research, microsaccade detection is typically performed using the calibrated gaze-velocity signal acquired from a video-based eye tracker. To generate this signal, the pupil and corneal reflection (CR) signals are subtracted from each other and a differentiation filter is applied, both of which may prevent small microsaccades from being detected due to signal distortion and noise amplification. We propose a new algorithm where microsaccades are detected directly from uncalibrated pupil-, and CR signals. It is based on detrending followed by windowed correlation between pupil and CR signals. The proposed algorithm outperforms the most commonly used algorithm in the field (Engbert & Kliegl, 2003), in particular for small... (More)
- In contemporary research, microsaccade detection is typically performed using the calibrated gaze-velocity signal acquired from a video-based eye tracker. To generate this signal, the pupil and corneal reflection (CR) signals are subtracted from each other and a differentiation filter is applied, both of which may prevent small microsaccades from being detected due to signal distortion and noise amplification. We propose a new algorithm where microsaccades are detected directly from uncalibrated pupil-, and CR signals. It is based on detrending followed by windowed correlation between pupil and CR signals. The proposed algorithm outperforms the most commonly used algorithm in the field (Engbert & Kliegl, 2003), in particular for small amplitude microsaccades that are difficult to see in the velocity signal even with the naked eye. We argue that it is advantageous to consider the most basic output of the eye tracker, i.e. pupil-, and CR signals, when detecting small microsaccades. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4e31ead5-6739-47cc-89b7-c735e81341b1
- author
- Niehorster, Diederick C
LU
and Nyström, Marcus
LU
- organization
- publishing date
- 2018-04-23
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications : ETRA '18 - ETRA '18
- article number
- 57
- pages
- 5 pages
- publisher
- Association for Computing Machinery (ACM)
- conference name
- The 2018 ACM Symposium on Eye Tracking Research & Applications
- conference location
- Warsaw, Poland
- conference dates
- 2018-06-14 - 2018-06-17
- external identifiers
-
- scopus:85049693031
- ISBN
- 9781450357067
- DOI
- 10.1145/3204493.3204573
- language
- English
- LU publication?
- yes
- id
- 4e31ead5-6739-47cc-89b7-c735e81341b1
- date added to LUP
- 2018-05-17 09:22:22
- date last changed
- 2023-01-15 01:56:30
@inproceedings{4e31ead5-6739-47cc-89b7-c735e81341b1,
abstract = {{In contemporary research, microsaccade detection is typically performed using the calibrated gaze-velocity signal acquired from a video-based eye tracker. To generate this signal, the pupil and corneal reflection (CR) signals are subtracted from each other and a differentiation filter is applied, both of which may prevent small microsaccades from being detected due to signal distortion and noise amplification. We propose a new algorithm where microsaccades are detected directly from uncalibrated pupil-, and CR signals. It is based on detrending followed by windowed correlation between pupil and CR signals. The proposed algorithm outperforms the most commonly used algorithm in the field (Engbert & Kliegl, 2003), in particular for small amplitude microsaccades that are difficult to see in the velocity signal even with the naked eye. We argue that it is advantageous to consider the most basic output of the eye tracker, i.e. pupil-, and CR signals, when detecting small microsaccades.}},
author = {{Niehorster, Diederick C and Nyström, Marcus}},
booktitle = {{Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications : ETRA '18}},
isbn = {{9781450357067}},
language = {{eng}},
month = {{04}},
publisher = {{Association for Computing Machinery (ACM)}},
title = {{Microsaccade detection using pupil and corneal reflection signals}},
url = {{https://lup.lub.lu.se/search/files/52189182/etra_2018_final.pdf}},
doi = {{10.1145/3204493.3204573}},
year = {{2018}},
}