ArticleNPJ digital medicine2026
iPad Eye Tracking Reproduces Clinical Grade Oculomotor Differences in Parkinson's Disease.
Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
10 authors.
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Abstract
iPad-based eye tracking could support Parkinson's disease (PD) screening and longitudinal monitoring by enabling objective, low-cost, portable assessment of oculomotor function. We previously validated an iPad-based eye-tracking system against the EyeLink 1000 Plus for temporal and spatial saccade metrics. Here, in a convenience sample of 19 healthy controls (HC) and 12 patients with PD, we recorded eye movements simultaneously with both devices during pro-saccade, anti-saccade (AS), memory-guided saccade (MGS), and self-generated saccade tasks. Across all pre-specified metrics, statistically significant PD-HC differences and null results were concordant between devices. In addition, saccade-level mixed-effects models showed small group × device interaction effects that remained below literature-based benchmarks for clinically meaningful PD-HC differences, indicating that iPad-based measurements preserved benchmark clinical-grade group-level effects. A compact three-metric iPad-based classifier comprising AS directional error rate, AS gain, and MGS gain supported strong subject-level PD-HC discrimination, with an area under the receiver operating characteristic curve of 0.98, sensitivity of 0.91, specificity of 1.00, and accuracy of 0.96. These findings support scalable tablet-based oculomotor assessment for PD-related screening and longitudinal monitoring.
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Registered trials
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