Paper Info
Title
Determination of Saccade Latency Distributions using Video Recordings from Consumer-grade Devices.
Abstract
Quantitative and accurate tracking of neurocognitive decline remains an ongoing challenge. We seek to address this need by focusing on robust and unobtrusive measurement of saccade latency - the time between the presentation of a visual stimulus and the initiation of an eye movement towards the stimulus - which has been shown to be altered in patients with neurocognitive decline or neurodegenerative diseases. Here, we present a novel, deep convolutional-neuralnetwork-based method to measure saccade latency outside of the clinical environment using a smartphone camera without the need for supplemental or special-purpose illumination. We also describe a model-based approach to estimate saccade latency that is less sensitive to noise compared to conventional methods. With this flexible and robust system, we collected over 11,000 saccade-latency measurements from 21 healthy individuals and found distinctive saccade-latency distributions across subjects. When analyzing intra-subject variability across time, we observed noticeable variations in the mean saccade latency and associated standard deviation. We also observed a potential learning effect that should be further characterized and potentially accounted for when interpreting saccade latency measurements.
Year
DOI
Venue
2018
10.1109/EMBC.2018.8512281
EMBC
Field
DocType
Volume
Computer vision,Task analysis,Latency (engineering),Computer science,Visualization,Speech recognition,Eye movement,Artificial intelligence,Stimulus (physiology),Saccade,Standard deviation,Neurocognitive
Conference
2018
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Gladynel Saavedra-Peña100.34
Hsin-Yu Lai222.39
V. Sze3100758.98
Thomas Heldt429.54