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We aid in neurocognitive monitoring outside the hospital environment byenabling app-based measurements of visual reaction time (saccade latency) anderror rate in a cohort of subjects spanning the adult age spectrum. Methods: Wedeveloped an iOS app to record subjects with the frontal camera during pro- andanti-saccade tasks. We further developed automated algorithms for measuringsaccade latency and error rate that take into account the possibility that itmight not always be possible to determine the eye movement from app-basedrecordings. Results: To measure saccade latency on a tablet, we ensured thatthe absolute timing error between on-screen task presentation and the camerarecording is within 5 ms. We collected over 235,000 eye movements in 80subjects ranging in age from 20 to 92 years, with 96% of recorded eye movementseither declared good or directional errors. Our error detection code achieved asensitivity of 0.97 and a specificity of 0.97. Confirming prior reports, weobserved a positive correlation between saccade latency and age while therelationship between error rate and age was not significant. Finally, weobserved significant intra- and inter-subject variations in saccade latency anderror rate distributions, which highlights the importance of individualizedtracking of these visual digital biomarkers. Conclusion and Significance: Oursystem and algorithms allow ubiquitous tracking of saccade latency and errorrate, which opens up the possibility of quantifying patient state on a finertimescale in a broader population than previously possible.

App-based saccade latency and error determination across the adult age spectrum