This paper is in the following e-collection/theme issue:

New Methods (909) Dementia and Cognitive Decline (426) Cognitive and Neurorehabilitation (236) Diagnostic Tools in Mental Health (222)

Published on in Vol 20, No 7 (2018): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11143, first published .
Device-Embedded Cameras for Eye Tracking–Based Cognitive Assessment: Validation With Paper-Pencil and Computerized Cognitive Composites

Device-Embedded Cameras for Eye Tracking–Based Cognitive Assessment: Validation With Paper-Pencil and Computerized Cognitive Composites

Device-Embedded Cameras for Eye Tracking–Based Cognitive Assessment: Validation With Paper-Pencil and Computerized Cognitive Composites

Authors of this article:

Nicholas Bott1, 2 Author Orcid Image ;   Erica N Madero2 Author Orcid Image ;   Jordan Glenn2 Author Orcid Image ;   Alexander Lange2 Author Orcid Image ;   John Anderson2 Author Orcid Image ;   Doug Newton2 Author Orcid Image ;   Adam Brennan2 Author Orcid Image ;   Elizabeth A. Buffalo2, 3 Author Orcid Image ;   Dorene Rentz4, 5 Author Orcid Image ;   Stuart Zola2, 6 Author Orcid Image
Article Authors Cited by (28) Tweetations (20) Metrics

Journals

  1. Bott N, Madero E, Glenn J, Lange A, Anderson J, Newton D, Brennan A, Buffalo E, Rentz D, Zola S. Device-Embedded Cameras for Eye Tracking-Based Cognitive Assessment: Implications for Teleneuropsychology. Telemedicine and e-Health 2020;26(4):477 View
  2. Zhang K, Li X, He L, Guo C, Yang Y, Dong Z, Yang H, Zhu Y, Chen C, Zhou X, Li W, Liu Z, Wu X, Liu X, Lin H. A human-in-the-loop deep learning paradigm for synergic visual evaluation in children. Neural Networks 2020;122:163 View
  3. Glenn J, Madero E, Gray M, Fuseya N, Ikeda M, Kawamura T, Arita Y, Bott N. Engagement With a Digital Platform for Multimodal Cognitive Assessment and Multidomain Intervention in a Japanese Population: Pilot, Quasi-Experimental, Longitudinal Study. JMIR mHealth and uHealth 2019;7(10):e15733 View
  4. Horan B, Heckenberg R, Maruff P, Wright B. Development of a new virtual reality test of cognition: assessing the test-retest reliability, convergent and ecological validity of CONVIRT. BMC Psychology 2020;8(1) View
  5. Snegireva N, Derman W, Patricios J, Welman K. Eye tracking technology in sports-related concussion: a systematic review and meta-analysis. Physiological Measurement 2018;39(12):12TR01 View
  6. Piau A, Wild K, Mattek N, Kaye J. Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review. Journal of Medical Internet Research 2019;21(8):e12785 View
  7. Tao L, Wang Q, Liu D, Wang J, Zhu Z, Feng L. Eye tracking metrics to screen and assess cognitive impairment in patients with neurological disorders. Neurological Sciences 2020;41(7):1697 View
  8. Gills J, Bott N, Madero E, Glenn J, Gray M. A short digital eye-tracking assessment predicts cognitive status among adults. GeroScience 2021;43(1):297 View
  9. Gills J, Glenn J, Madero E, Bott N, Gray M. Validation of a digitally delivered visual paired comparison task: reliability and convergent validity with established cognitive tests. GeroScience 2019;41(4):441 View
  10. Soufian M, Nefti-Mezian S, Drake J. Toward Kinecting cognition by behaviour recognition-based deep learning and big data. Universal Access in the Information Society 2022;21(1):33 View
  11. Gray M, Gills J, Glenn J, Vincenzo J, Walter C, Madero E, Hall A, Fuseya N, Bott N. Cognitive decline negatively impacts physical function. Experimental Gerontology 2021;143:111164 View
  12. Udeh-Momoh C, Watermeyer T, Price G, de Jager Loots C, Reglinska-Matveyev N, Ropacki M, Ketter N, Fogle M, Raghavan N, Arrighi M, Brashear R, Di J, Baker S, Giannakopoulou P, Robb C, Bassil D, Cohn M, McLellan-Young H, Crispin J, Lakey K, Lisa C, Chowdary Seemulamoodi Y, Kafetsouli D, Perera D, Car J, Majeed A, Ward H, Ritchie K, Perneczky R, Kivipelto M, Scott D, Bracoud L, Saad Z, Novak G, Ritchie C, Middleton L. Protocol of the Cognitive Health in Ageing Register: Investigational, Observational and Trial Studies in Dementia Research (CHARIOT): Prospective Readiness cOhort (PRO) SubStudy. BMJ Open 2021;11(6):e043114 View
  13. Gray M, Gills J, Glenn J. Cognitive management in a digital world. Aging 2021;13(13):16900 View
  14. Öhman F, Hassenstab J, Berron D, Schöll M, Papp K. Current advances in digital cognitive assessment for preclinical Alzheimer's disease. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 2021;13(1) View
  15. Bastardo R, Pavão J, Martins A, Silva A, Rocha N. A Scoping Review of Digital Solutions that Might be Used as Cognitive Screening Instruments of Community-Dwelling Older Adults. Procedia Computer Science 2022;196:956 View
  16. Campitelli A, Paulson S, Gills J, Jones M, Madero E, Myers J, Glenn J, Gray M. A Novel Digital Digit-Symbol Substitution Test Measuring Processing Speed in Adults At Risk for Alzheimer Disease: Validation Study. JMIR Aging 2023;6:e36663 View
  17. Papangelou A, Boorman D, Sharifpour M, Patel H, Cassim T, García P. Associations of an eye-tracking task and pupillary metrics with age and ASA physical status score in a preoperative cohort. Journal of Clinical Monitoring and Computing 2023;37(3):795 View
  18. Gills J, Campitelli A, Jones M, Paulson S, Myers J, Madero E, Glenn J, Komorowski J, Gray M. Acute Inositol-Stabilized Arginine Silicate Improves Cognitive Outcomes in Healthy Adults. Nutrients 2021;13(12):4272 View
  19. de Villers-Sidani É, Voss P, Guitton D, Cisneros-Franco J, Koch N, Ducharme S. A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson’s disease. Frontiers in Neurology 2023;14 View
  20. Wolf A, Tripanpitak K, Umeda S, Otake-Matsuura M. Eye-tracking paradigms for the assessment of mild cognitive impairment: a systematic review. Frontiers in Psychology 2023;14 View
  21. Soldevila-Domenech N, De Toma I, Forcano L, Diaz-Pellicer P, Cuenca-Royo A, Fagundo B, Lorenzo T, Gomis-Gonzalez M, Sánchez-Benavides G, Fauria K, Sastre C, Fernandez De Piérola Í, Molinuevo J, Verdejo-Garcia A, de la Torre R. Intensive assessment of executive functions derived from performance in cognitive training games. iScience 2023;26(6):106886 View
  22. Castilla D, Del Tejo Catalá O, Pons P, Signol F, Rey B, Suso-Ribera C, Perez-Cortes J. Improving the understanding of web user behaviors through machine learning analysis of eye-tracking data. User Modeling and User-Adapted Interaction 2024;34(2):293 View
  23. Glenn J, Bryk K, Myers J, Anderson J, Onguchi K, McFarlane J, Ozaki S. The efficacy and practicality of the Neurotrack Cognitive Battery assessment for utilization in clinical settings for the identification of cognitive decline in an older Japanese population. Frontiers in Aging Neuroscience 2023;15 View
  24. Fu Y, Zhang J, Cao Y, Ye L, Zheng R, Li Q, Shen B, Shi Y, Cao J, Fang J. Recognition memory deficits detected through eye‐tracking in well‐controlled children with self‐limited epilepsy with centrotemporal spikes. Epilepsia 2024;65(4):1128 View
  25. Boujelbane M, Trabelsi K, Salem A, Ammar A, Glenn J, Boukhris O, AlRashid M, Jahrami H, Chtourou H. Eye Tracking During Visual Paired-Comparison Tasks: A Systematic Review and Meta-Analysis of the Diagnostic Test Accuracy for Detecting Cognitive Decline. Journal of Alzheimer's Disease 2024;99(1):207 View

Books/Policy Documents

  1. Bastardo R, Pavão J, Martins A, Silva A, Rocha N. Digital Science. View