Automated detection of quiet eye durations in archery using electrooculography and comparative deep learning models

Automated detection of quiet eye durations in archery using electrooculography and comparative deep learning models

Abstract This study presents a deep learning-based approach for the automated detection of Quiet Eye (QE) durations from electrooculography (EOG) signals in archery. QE—the final fixation or tracking of the gaze before executing a motor action—is a critical factor in precision sports. Traditional de...

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Bibliographic Details
Main Authors: Fatma Söğüt, Hüseyin Yanık, Evren Değirmenci, İnci Kesilmiş, Ülkü Çömelekoğlu
Format: Article
Language:English
Published: BMC 2025-08-01
Series:BMC Sports Science, Medicine and Rehabilitation
Subjects:
Quiet eye
Electrooculography
Wavelet transform
Convolutional neural networks
Long-short term memory
Transformer
Online Access:https://doi.org/10.1186/s13102-025-01284-2
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https://doi.org/10.1186/s13102-025-01284-2

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