Evidence map›Paper›PMID 38253934›Full record

ArticleExperimental brain research2024

The role of vision in sensory integration models for predicting motion perception and sickness.

Varun Kotian, Tugrul Irmak, Daan Pool, Riender Happee

Open access · hybridAbstract read
In one paragraph

Article in Experimental brain research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Article
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

4 authors at 2 institutions in 1 country.

Varun KotianCognitive Robotics, TU Delft Faculty of Mechanical, Maritime and Materials Engineering, Mekelweg, Delft, 2628 CD, Zuid-Holland, The Netherlands. v.kotian@tudelft.nl.ORCID http://orcid.org/0000-0001-9753-9229
Tugrul IrmakCognitive Robotics, TU Delft Faculty of Mechanical, Maritime and Materials Engineering, Mekelweg, Delft, 2628 CD, Zuid-Holland, The Netherlands.ORCID http://orcid.org/0000-0002-7633-394X
Daan PoolControl and Simulation, TU Delft Faculty of Aerospace Engineering, Kluyverweg, Delft, 2629 HS, Zuid-Holland, The Netherlands.ORCID http://orcid.org/0000-0001-9535-2639
Riender HappeeCognitive Robotics, TU Delft Faculty of Mechanical, Maritime and Materials Engineering, Mekelweg, Delft, 2628 CD, Zuid-Holland, The Netherlands.ORCID http://orcid.org/0000-0001-5878-3472
Delft University of Technology · NLUniversity Medical Center Utrecht · NL

Funding

Horizon 2020 101006664
6 · The paper itself

Abstract

Users of automated vehicles will engage in other activities and take their eyes off the road, making them prone to motion sickness. To resolve this, the current paper validates models predicting sickness in response to motion and visual conditions. We validate published models of vestibular and visual sensory integration that have been used for predicting motion sickness through sensory conflict. We use naturalistic driving data and laboratory motion (and vection) paradigms, such as sinusoidal translation and rotation at different frequencies, Earth-Vertical Axis Rotation, Off-Vertical Axis Rotation, Centrifugation, Somatogravic Illusion, and Pseudo-Coriolis, to evaluate different models for both motion perception and motion sickness. We investigate the effects of visual motion perception in terms of rotational velocity (visual flow) and verticality. According to our findings, the SVC

Indexed as

IllusionsMotion PerceptionMotion SicknessHumansRotationSpace PerceptionComfortModelingMotion perceptionMotion sicknessVision

Identifiers

PMID38253934
PMCPMC10894782
OpenAlexW4391116282

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.