# Combining Automation and Expertise: A Semi-automated Approach to Correcting Eye Tracking Data in Reading Tasks

arXiv: https://arxiv.org/abs/2501.06977 · HTML: https://mlsanity.com/paper/2501.06977/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jan 2025.

## Built on by (most cited first, 1 of 1)

- [Sure About That Line? Approaching Confidence-Based, Real-Time Line Assignment in Reading Gaze Data](https://mlsanity.com/paper/2605.00033/) (2026)

## Abstract (arXiv)

In reading tasks drift can move fixations from one word to another or even another line, invalidating the eye tracking recording. Manual correction is time-consuming and subjective, while automated correction is fast yet limited in accuracy. In this paper we present Fix8 (Fixate), an open-source GUI tool that offers a novel semi-automated correction approach for eye tracking data in reading tasks. The proposed approach allows the user to collaborate with an algorithm to produce accurate corrections faster without sacrificing accuracy. Through a usability study (N=14) we assess the time benefits of the proposed technique, and measure the correction accuracy in comparison to manual correction. In addition, we assess subjective workload through NASA Task Load Index, and user opinions through Likert-scale questions. Our results show that on average the proposed technique was 44% faster than manual correction without any sacrifice in accuracy. In addition, users reported a preference for the proposed technique, lower workload, and higher perceived performance compared to manual correction. Fix8 is a valuable tool that offers useful features for generating synthetic eye tracking data, visualization, filters, data converters, and eye movement analysis in addition to the main contribution in data correction.