Objectives: To determine if participants with saccadic dysfunction improved after participating in a standardized oculomotor training program. A secondary objective was to accurately quantify change in saccades after training using eye tracking technology. A third objective was to examine patients' neurobehavioral symptoms before and after oculomotor training using the Neurobehavioral Symptom Inventory (NSI).
Design: A prospective study involving treatment and control group pre-post intervention design.
Setting: Data were collected in eye clinics with a standardized eye tracking equipment setup.
Participants: Participants in the bottom 25th percentile for saccadic eye movements (N=92; intervention=46, control=46) who were currently asymptomatic of specific disorder.
Interventions: Participants were randomly assigned to the control or intervention group. The intervention group engaged in 10 minutes of oculomotor training daily for 5 days.
Main Outcome Measures: The ratio of the peak saccadic velocity over its average velocity (the Q ratio), saccadic targeting, and NSI.
Results: Results revealed significant interactions between control and intervention groups (=.013). The control group increased 7% from pre to post; however, the intervention group exhibited a 6% decreased from pre to post. Participants in the intervention group demonstrated a 25% improvement in targeting saccade accuracy (=.021). Additionally, there was a significant reduction in all neurobehavioral factors on the NSI in the intervention group, specifically the affective and cognitive factors relating to poor saccades.
Conclusions: For this population, oculomotor training (Q ratio and saccade accuracy) resulted improved saccadic metrics and a significant reduction in overall symptoms as shown on the NSI. Future participants reported improved symptoms pre- and postintervention. Further research is needed to understand saccadic performance and gaze stability during specific tasks (such as reading).
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http://dx.doi.org/10.1016/j.arrct.2021.100126 | DOI Listing |
Med Sci Educ
December 2024
Department of Anesthesiology and Intensive Care, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
Introduction: Virtual reality-based simulation is an educational tool that has been proven to increase participants' self-perceived, confidence, and skill. However, the use of VR is associated with virtual reality sickness (VRS). The purpose of this study is to determine related factors of VRS in an emergency setting simulation-based training, hence providing information and mitigation plan to enhance and optimize learning outcomes.
View Article and Find Full Text PDFJ Neural Transm (Vienna)
January 2025
Neurology Department, LR18SP03, Razi University Hospital, Tunis, Tunisia.
Amyotrophic Lateral Sclerosis(ALS) has traditionally been managed as a neuromuscular disorder. However, recent evidence suggests involvement of non-motor domains. This study aims to evaluate the impact of APOE and MAPT genotypes on the cognitive features of ALS.
View Article and Find Full Text PDFVision (Basel)
December 2024
Department of Optometry and Vision Science, Faculty of Science and Technology, University of Latvia, LV-1004 Riga, Latvia.
Virtual reality (VR) can challenge the visual system, leading to temporary oculomotor changes, though the degree of change varies among individuals. While the vergence and accommodation system plays a crucial role in VR perception, it remains unclear whether individuals whose visual functions fall outside clinical norms experience larger changes. Thus, our study aimed to investigate whether changes in vergence and accommodation responses following VR gameplay differ between individuals with and without non-strabismic binocular and accommodative disorders.
View Article and Find Full Text PDFOphthalmic Physiol Opt
December 2024
Optometry and Vision Sciences Research Group, Aston University, Birmingham, UK.
Purpose: To propose a novel artificial intelligence (AI)-based virtual assistant trained on tabular clinical data that can provide decision-making support in primary eye care practice and optometry education programmes.
Method: Anonymised clinical data from 1125 complete optometric examinations (2250 eyes; 63% women, 37% men) were used to train different machine learning algorithm models to predict eye examination classification (refractive, binocular vision dysfunction, ocular disorder or any combination of these three options). After modelling, adjustment, mining and preprocessing (one-hot encoding and SMOTE techniques), 75 input (preliminary data, history, oculomotor test and ocular examinations) and three output (refractive, binocular vision status and eye disease) features were defined.
NPJ Parkinsons Dis
December 2024
Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
Oculomotor behaviour changes in patients with Parkinson's disease (PD) are a promising source of prodromal disease markers. Capitalizing on this phenomenon to facilitate early diagnosis requires oculomotor assessment in prodromal cohorts. We examined oculomotor behaviour in non-manifesting LRRK2 G2019S mutation carriers (LRRK2-NM), who have heightened PD risk.
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