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Open Access

Pupillometry Analysis of Rapid Serial Visual Presentation at Five Presentation Rates

School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
School of Medicine, Tsinghua University, Beijing 100084, China
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Abstract

In this study, the effect of presentation rates on pupil dilation is investigated for target recognition in the Rapid Serial Visual Presentation (RSVP) paradigm. In this experiment, the RSVP paradigm with five different presentation rates, including 50, 80, 100, 150, and 200 ms, is designed. The pupillometry data of 15 subjects are collected and analyzed. The pupillometry results reveal that the peak and average amplitudes for pupil size and velocity at the 80-ms presentation rate are considerably higher than those at other presentation rates. The average amplitude of pupil acceleration at the 80-ms presentation rate is significantly higher than those at the other presentation rates. The latencies under 50- and 80-ms presentation rates are considerably lower than those of 100-, 150-, and 200-ms presentation rates. Additionally, no considerable differences are observed in the peak, average amplitude, and latency of pupil size, pupil velocity, and acceleration under 100-, 150-, and 200-ms presentation rates. These results reveal that with the increase in the presentation rate, pupil dilation first increases, then decreases, and later reaches saturation. The 80-ms presentation rate results in the largest point of pupil dilation. No correlation is observed between pupil dilation and recognition accuracy under the five presentation rates.

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Tsinghua Science and Technology
Pages 543-552

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Cite this article:
Luo X, Lin Y, Guo R, et al. Pupillometry Analysis of Rapid Serial Visual Presentation at Five Presentation Rates. Tsinghua Science and Technology, 2024, 29(2): 543-552. https://doi.org/10.26599/TST.2023.9010029

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Received: 09 February 2023
Revised: 30 March 2023
Accepted: 06 April 2023
Published: 22 September 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).