Uncovering and Addressing Blink-Related Challenges in Using Eye Tracking for Interactive Systems

Authors

Jesse W Grootjen

Henrike Weingärtner

Sven Mayer

Preface

This document developed for improving quality of eye tracking analysis in interactive systems and an initial step for co-design standards for HCI eye tracking studies.

Versions

V1.0 Initial Version at CHI publication 29.02.2024

Citing

These guidelines are supplementary material for our paper, Uncovering and Addressing Blink-Related Challenges in Using Eye Tracking for Interactive Systems at CHI. If you are using the guidelines in this webpage, please cite our paper using the following BibTeX.

@inproceedings{grootjen2024uncovering,
title = {Uncovering and Addressing Blink-Related Challenges in Using Eye Tracking for Interactive Systems},
author = { Jesse W. Grootjen and Henrike Weing\"{a}rtner and Sven Mayer},
url = {https://sven-mayer.com/wp-content/uploads/2024/02/grootjen2024uncovering.pdf
https://eyetrackingguidelines.github.io},
doi = {10.1145/3613904.3642086},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {CHI \'24},
abstract = {Currently, interactive systems use physiological sensing to enable advanced functionalities. While eye tracking is a promising means to understand the user, eye tracking data inherently suffers from missing data due to blinks, which may result in reduced system performance. We conducted a literature review to understand how researchers deal with this issue. We uncovered that researchers often implemented their use-case-specific pipeline to overcome the issue, ranging from ignoring missing data to artificial interpolation. With these first insights, we run a large-scale analysis on 11 publicly available datasets to understand the impact of the various approaches on data quality and accuracy. By this, we highlight the pitfalls in data processing and which methods work best. Based on our results, we provide guidelines for handling eye tracking data for interactive systems. Further, we propose a standard data processing pipeline that allows researchers and practitioners to pre-process and standardize their data efficiently.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

Contribution

We appreciate any feedback and contribution to improve these guidelines in future versions. Please refer to github repository for downloading the files of current version.