354
Views
9
CrossRef citations to date
0
Altmetric
Original

Eye tracking technology: A fresh approach in delirium assessment?

&
Pages 8-14 | Published online: 11 Jul 2009
 

Abstract

The objective of this paper is to highlight the potential role of eye tracking technology (ETT) in the assessment of delirious patients. Delirium occurs in one in five general hospital admissions (Siddiqi, 2006) and its frequency will increase as society gets older. Despite its frequency and significant independent impact upon morbidity and mortality, delirium remains under studied and is frequently missed, detected late, or misdiagnosed (Farrell & Ganzani, 1995; Inouye, 2001; Kakuma, 2003). Detection is a key target for both clinical and research efforts. Assessment of attention is key to diagnosing delirium, yet nurses and non-research medical staff often fail to correctly identify inattention (Inouye et al., Citation; Lemiengre et al., Citation; Ryan et al., 2008). Eye tracking measures have been used in a plethora of key areas of psychiatric research (Crawford et al., Citation; Corden, Chilvers, & Skuse, 2008; Hardin, Schroth, Pine, & Ernst, 2007; Holzman, Leonard, Proctor, & Hughes, 1973), and provide an accurate and non-invasive method in the assessment of cognitive function. The potential of ETT for direct clinical applications in the assessment of attention and comprehension, key cognitive symptoms of delirium, are promising. This paper considers potential new approaches which recent advancements in non-invasive ETT may bring to the examination and understanding of delirium.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 770.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.