short-paper

Detection of Saccades and Quick-Phases in Eye Movement Recordings with Nystagmus

Authors:

Sai Akanksha Punuganti,

Jorge Otero-Millan PhDAuthors Info & Claims

ETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and Applications

Article No.: 8, Pages 1 - 5

https://doi.org/10.1145/3379156.3391353

Published: 02 June 2020 Publication History

Abstract

Benign Paroxysmal Positional Vertigo (BPPV) is the most common cause of vertigo and dizziness. Patients with those symptoms can be diagnosed by the presence of a specific pattern of nystagmus during the Dix-Hallpike maneuver. However, almost half of dizzy patients visiting Emergency Department (ED) are misdiagnosed, leading to significant morbidity and high medical costs. This can be attributed to the lack of specialized expertise of front-line physicians and to the lack of validated automatic commercial devices and software for nystagmus detection and quantification. Here we aim to enhance saccade detection thereby improving automatic nystagmus quantification. The proposed method is evaluated on a nystagmus dataset recorded from patients in the ED as they undergo the Dix-Hallpike maneuver. Additionally, the proposed method is also tested on a publicly available saccade dataset and compared with state-of-the-art eye movement detection methods.

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Zhao ZMeng HLi SWang SWang JGao S(2025)High-Accuracy Intermittent Strabismus Screening via Wearable Eye-Tracking and AI-Enhanced Ocular Feature AnalysisBiosensors10.3390/bios1502011015:2(110)Online publication date: 14-Feb-2025
https://doi.org/10.3390/bios15020110
Hassan MYin XZhuang YAldridge CMcMurry TSoutherland ARohde G(2024)A Digital Camera-Based Eye Movement Assessment Method for NeuroEye ExaminationIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2023.328594028:2(655-665)Online publication date: Feb-2024
https://doi.org/10.1109/JBHI.2023.3285940
Abul Hassan MAldridge CZhuang YYin XMcMurry TRohde GSoutherland A(2023)Approach to Quantify Eye Movements to Augment Stroke Diagnosis With a Non-Calibrated Eye-TrackerIEEE Transactions on Biomedical Engineering10.1109/TBME.2022.322701570:6(1750-1757)Online publication date: Jun-2023
https://doi.org/10.1109/TBME.2022.3227015
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cover image ACM Conferences

ETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and Applications

June 2020

305 pages

ISBN:9781450371346

DOI:10.1145/3379156

Editors:
Andreas Bulling
University of Stuttgart, Germany
,
Anke Huckauf
Ulm University, Germany
,
Eakta Jain
University of Florida, USA
,
Ralph Radach
University of Wuppertal, Germany
,
Daniel Weiskopf
University of Stuttgart, Germany

Copyright © 2020 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 02 June 2020

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June 2 - 5, 2020

Stuttgart, Germany

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Overall Acceptance Rate 69 of 137 submissions, 50%

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Cited By

Zhao ZMeng HLi SWang SWang JGao S(2025)High-Accuracy Intermittent Strabismus Screening via Wearable Eye-Tracking and AI-Enhanced Ocular Feature AnalysisBiosensors10.3390/bios1502011015:2(110)Online publication date: 14-Feb-2025
https://doi.org/10.3390/bios15020110
Hassan MYin XZhuang YAldridge CMcMurry TSoutherland ARohde G(2024)A Digital Camera-Based Eye Movement Assessment Method for NeuroEye ExaminationIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2023.328594028:2(655-665)Online publication date: Feb-2024
https://doi.org/10.1109/JBHI.2023.3285940
Abul Hassan MAldridge CZhuang YYin XMcMurry TRohde GSoutherland A(2023)Approach to Quantify Eye Movements to Augment Stroke Diagnosis With a Non-Calibrated Eye-TrackerIEEE Transactions on Biomedical Engineering10.1109/TBME.2022.322701570:6(1750-1757)Online publication date: Jun-2023
https://doi.org/10.1109/TBME.2022.3227015
Newman JPhillips JCox S(2021)1D Convolutional Neural Networks for Detecting NystagmusIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2020.302538125:5(1814-1823)Online publication date: May-2021
https://doi.org/10.1109/JBHI.2020.3025381

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