Automated screening of Parkinson's Disease using Smooth Pursuit Eye Movements
Abstract
Smooth pursuit eye movements are frequently altered in Parkinson's disease, but previous studies have relied mainly on conventional parameters that describe the relationship between gaze and target. This study investigates whether complexity and nonlinear dynamics measures of the gaze position sequences can support the automatic screening of Parkinson's disease. Gaze position sequences were recorded with a video eye tracker in 41 participants with early Parkinson's disease and 47 healthy controls during 12 smooth pursuit tasks. Four experimental frameworks and four embedding delay strategies were compared. The selected experimental setting combined baseline wander removal with a fixed embedding delay. After feature selection, a support vector machine was trained for each task and axis and their outputs were combined in a mixture of experts. The pipeline was developed in 70 participants and evaluated on an external test set of 18 participants. On the external test set, the pipeline obtained an area under the receiver operating characteristic curve of 0.86. The most informative features described less persistent and more irregular gaze position sequences in Parkinson's disease, mainly along the horizontal axis. These results support complexity and nonlinear dynamics measures of smooth pursuit as candidate markers for Parkinson's disease screening, pending validation in larger independent cohorts.
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BibTeX
@misc{puertaacevedo2026automated,
title = {{Automated screening of Parkinson's Disease using Smooth Pursuit Eye Movements}},
author = {J. Camilo Puerta-Acevedo and Maria F. Alcala-Durand and Julián D. Arias-Londoño and Elisa Luque-Buzo and Francisco Grandas-Pérez and Juan I. Godino-Llorente},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.33359},
eprint = {2610.33359},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.33359},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Automated screening of Parkinson's Disease using Smooth Pursuit Eye Movements
AU - J. Camilo Puerta-Acevedo
AU - Maria F. Alcala-Durand
AU - Julián D. Arias-Londoño
AU - Elisa Luque-Buzo
AU - Francisco Grandas-Pérez
AU - Juan I. Godino-Llorente
PY - 2026
DA - 2026/10/23
PB - arXiv
DO - 10.48550/arxiv.2610.33359
UR - https://arxiv.org/abs/2610.33359
AB - Smooth pursuit eye movements are frequently altered in Parkinson's disease, but previous studies have relied mainly on conventional parameters that describe the relationship between gaze and target. This study investigates whether complexity and nonlinear dynamics measures of the gaze position sequences can support the automatic screening of Parkinson's disease. Gaze position sequences were recorded with a video eye tracker in 41 participants with early Parkinson's disease and 47 healthy controls during 12 smooth pursuit tasks. Four experimental frameworks and four embedding delay strategies were compared. The selected experimental setting combined baseline wander removal with a fixed embedding delay. After feature selection, a support vector machine was trained for each task and axis and their outputs were combined in a mixture of experts. The pipeline was developed in 70 participants and evaluated on an external test set of 18 participants. On the external test set, the pipeline obtained an area under the receiver operating characteristic curve of 0.86. The most informative features described less persistent and more irregular gaze position sequences in Parkinson's disease, mainly along the horizontal axis. These results support complexity and nonlinear dynamics measures of smooth pursuit as candidate markers for Parkinson's disease screening, pending validation in larger independent cohorts.
ER -