Nicholas T Bott1,2,3, Erica N Madero1, Jordan M Glenn1, Alex R Lange1, John J Anderson1, Doug O Newton1, Adam H Brennan1, Elizabeth A Buffalo1,4, Dorene M Rentz1,5,6, Stuart M Zola1,7. 1. Neurotrack Technologies, Inc., Redwood City, California. 2. Department of Medicine, School of Medicine, Stanford University, Stanford, California. 3. PGSP-Stanford PsyD Consortium, Department of Clinical Psychology, Palo Alto University, Palo Alto, California. 4. Department of Physiology and Biophysics, University of Washington, Seattle, Washington. 5. Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts. 6. Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts. 7. Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia.
Abstract
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.
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.