Introduction:Widespread screening for cognitive decline is an important challenge to address as the aging population grows, but there is currently a shortage of clinical infrastructure to meet the demand for in-person evaluation. Remotely delivered assessments that utilize eye-tracking data from webcams, such as visual paired comparison (VPC) tasks, could increase access to remote, asynchronous neuropsychological screening for cognitive decline but further validation against clinical-grade eye trackers is required.Methods:To demonstrate equivalence between a novel automated scoring system for eye-tracking metrics acquired through a laptop-embedded camera and a gold-standard eye tracker, we analyzed VPC data from 18 subjects aged 50+ with normal cognitive function across three visits. The eye tracker data were scored by the manufacturer's software, and the webcam data were scored by a novel algorithm.Results:Automated scoring of webcam-based VPC data revealed strong correlations with the clinical-grade eye-tracking camera. Correlation of mean VPC performance across all time points was robust: r = 0.95 (T1 r = 0.97; T2 r = 0.88; T3 r = 0.97; p's < 0.001). Correlation of per-trial performance across time points was also robust: r = 0.88 (T1 r = 0.85; T2 r = 0.89; T3 r = 0.92; p's < 0.001). Mean differences between performance data acquired by each device were 0.00.Conclusion:These results suggest that device-embedded cameras are a valid and scalable alternative to traditional laboratory-based equipment for gaze-based tasks measuring cognitive function. The validation of this technique represents an important technical advance for the field of teleneuropsychology.
Keywords: e-health; m-health; telehealth; telemedicine; teleneurology.