Evidence map›Paper›PMID 35370913›Full record

ArticleFrontiers in neurology2022

Eye and Head Movement Recordings Using Smartphones for Telemedicine Applications: Measurements of Accuracy and Precision.

T Maxwell Parker, Shervin Badihian, Ahmed Hassoon, Ali S Saber Tehrani, Nathan Farrell, David E Newman-Toker, Jorge Otero-Millan

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Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Article
  2. Review
  3. Observational
  4. Review
  5. Non-nystagmus hyperkinetic eye movement disorders.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
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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

7 authors.

T Maxwell ParkerDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Shervin BadihianDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Ahmed HassoonDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Ali S Saber TehraniDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Nathan FarrellDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
David E Newman-TokerDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Jorge Otero-MillanDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Smartphones have shown promise in the assessment of neuro-ophthalmologic and vestibular disorders. We have shown that the head impulse test results recorded using our application are comparable with measurements from clinical video-oculography (VOG) goggles. The smartphone uses ARKit's capability to acquire eye and head movement positions without the need of performing a calibration as in most eye-tracking devices. Here, we measure the accuracy and precision of the eye and head position recorded using our application. Methods: We enrolled healthy volunteers and asked them to direct their eyes, their heads, or both to targets on a wall at known eccentricities while recording their head and eye movements with our smartphone application. We measured the accuracy as the error between the eye or head movement measurement and the location of each target and the precision as the standard deviation of the eye or head position for each of the target positions. Results: The accuracy of head recordings (15% error) was overall better than the accuracy of eye recordings (23% error). We also found that the accuracy for horizontal eye movements (17% error) was better than for vertical (27% error). Precision was also better for head movement (0.8 degrees) recordings than eye movement recordings (1.3 degrees) and variability tended to increase with eccentricity. Conclusion: Our results provide basic metrics evaluating the utility of smartphone applications in the quantitative assessment of head and eye movements. While the new method may not replace the more accurate dedicated VOG devices, they provide a more accessible quantitative option. It may be advisable to include a calibration recording together with any planned clinical test to improve the accuracy.

Indexed as

ARKiteye trackingneurologic examinationsmartphonestrokevertigo

Identifiers

PMID35370913
PMCPMC8975177

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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.