Evidence map›Paper›PMID 30042093›Full record

ArticleJournal of medical Internet research2018

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

Nicholas Bott, Erica N Madero, Jordan Glenn, Alexander Lange, John Anderson, Doug Newton, Adam Brennan, Elizabeth A Buffalo, Dorene Rentz, Stuart Zola

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Nicholas BottClinical Excellence Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0000-0001-5709-4261
Erica N MaderoNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0002-5112-2441
Jordan GlennNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0002-2563-4291
Alexander LangeNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0001-9281-9678
John AndersonNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0001-7823-9378
Doug NewtonNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0001-5247-4687
Adam BrennanNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0002-6475-0957
Elizabeth A BuffaloNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0001-6326-9187
Dorene RentzDepartment of Neurology, Massachusetts General Hospital, Boston, MA, United States.ORCID 0000-0002-6318-9213
Stuart ZolaNeurotrack Technologies, Inc, Redwood City, CA, United States.ORCID 0000-0001-9546-6513
Neurotrack Technologies (United States) · USBrigham and Women's Hospital · USEmory University · USUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs eye tracking-based assessment of cognition becomes more widely used in older adults, particularly those at risk for dementia, reliable and scalable methods to collect high-quality data are required. Eye tracking-based cognitive tests that utilize device-embedded cameras have the potential to reach large numbers of people as a screening tool for preclinical cognitive decline. However, to fully validate this approach, more empirical evidence about the comparability of eyetracking-based paradigms to existing cognitive batteries is needed.

objectiveUsing a population of clinically normal older adults, we examined the relationship between a 30-minute Visual Paired Comparison (VPC) recognition memory task and cognitive composite indices sensitive to a subtle decline in domains associated with Alzheimer disease. Additionally, the scoring accuracy between software used with a commercial grade eye tracking camera at 60 frames per second (FPS) and a manually scored procedure used with a laptop-embedded web camera (3 FPS) on the VPC task was compared, as well as the relationship between VPC task performance and domain-specific cognitive function.

methodsA group of 49 clinically normal older adults completed a 30-min VPC recognition memory task with simultaneous recording of eye movements by a commercial-grade eye-tracking camera and a laptop-embedded camera. Relationships between webcam VPC performance and the Preclinical Alzheimer Cognitive Composite (PACC) and National Institutes of Health Toolbox Cognitive Battery (NIHTB-CB) were examined. Inter-rater reliability for manually scored tests was analyzed using Krippendorff's kappa formula, and we used Spearman's Rho correlations to investigate the relationship between VPC performance scores with both cameras. We also examined the relationship between VPC performance with the device-embedded camera and domain-specific cognitive performance.

resultsModest relationships were seen between mean VPC novelty preference and the PACC (r=.39, P=.007) and NIHTB-CB (r=.35, P=.03) composite scores, and additional individual neurocognitive task scores including letter fluency (r=.33, P=.02), category fluency (r=.36, P=.01), and Trail Making Test A (-.40, P=.006). Robust relationships were observed between the 60 FPS eye tracker and 3 FPS webcam on both trial-level VPC novelty preference (r=.82, P<.001) and overall mean VPC novelty preference (r=.92 P<.001). Inter-rater agreement of manually scored web camera data was high (kappa=.84).

conclusionsIn a sample of clinically normal older adults, performance on a 30-minute VPC task correlated modestly with computerized and paper-pencil based cognitive composites that serve as preclinical Alzheimer disease cognitive indices. The strength of these relationships did not differ between camera devices. We suggest that using a device-embedded camera is a reliable and valid way to assess performance on VPC tasks accurately and that these tasks correlate with existing cognitive composites.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseCognition DisordersCognitive DysfunctionComputersEye MovementsFemaleHumansMaleMiddle AgedNeuropsychological TestsReproducibility of ResultsVideo Recordingeye trackingneuropsychological testingpreclinical Alzheimer’s diseasevisual paired comparison

Identifiers

PMID30042093
PMCPMC6081607
OpenAlexW2832962474

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.