open access publication

Article, 2019

Aging and eye tracking: in the quest for objective biomarkers

Future Neurology, ISSN 1748-6971, 1479-6708, Volume 14, 4, Page fnl33, 10.2217/fnl-2019-0012

Contributors

Marandi, Ramtin Zargari 0000-0001-9233-1656 [1] Gazerani, Parisa 0000-0003-0109-3600 (Corresponding author) [1]

Affiliations

  1. [1] Aalborg University
  2. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Recent applications of eye tracking for diagnosis, prognosis and follow-up of therapy in age-related neurological or psychological deficits have been reviewed. The review is focused on active aging, neurodegeneration and cognitive impairments. The potential impacts and current limitations of using characterizing features of eye movements and pupillary responses (oculometrics) as objective biomarkers in the context of aging are discussed. A closer look into the findings, especially with respect to cognitive impairments, suggests that eye tracking is an invaluable technique to study hidden aspects of aging that have not been revealed using any other noninvasive tool. Future research should involve a wider variety of oculometrics, in addition to saccadic metrics and pupillary responses, including nonlinear and combinatorial features as well as blink- and fixation-related metrics to develop biomarkers to trace age-related irregularities associated with cognitive and neural deficits.

Keywords

active aging, age, age-related, aspects of aging, biomarkers, cognitive impairment, combinatorial features, context, context of aging, deficits, diagnosis, eye movements, eye tracking, eyes, features, features of eye movements, findings, follow-up, follow-up of therapy, impact, impairment, limitations, metrics, movement, neural deficits, neurodegeneration, noninvasive tool, objective biomarkers, oculometrics, potential impact, prognosis, psychological deficits, pupillary response, research, response, review, saccade metrics, technique, therapy, tools, tracking

Data Provider: Digital Science