Evidence map›Paper›PMID 38404740›Full record

Articlei-Perception

Effects of self-avatar cast shadow and foot vibration on telepresence, virtual walking experience, and cybersickness from omnidirectional movie.

Junya Nakamura, Yasushi Ikei, Michiteru Kitazaki

Open access · goldAbstract read
In one paragraph

Article in i-Perception. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 2 institutions in 1 country.

Junya NakamuraToyohashi University of Technology, Japan.ORCID https://orcid.org/0000-0002-9359-7971
Yasushi IkeiThe University of Tokyo, Japan.
Michiteru KitazakiToyohashi University of Technology, Japan.ORCID https://orcid.org/0000-0003-0966-4842
Toyohashi University of Technology · JPThe University of Tokyo · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human locomotion is most naturally achieved through walking, which is good for both mental and physical health. To provide a virtual walking experience to seated users, a system utilizing foot vibrations and simulated optical flow was developed. The current study sought to augment this system and examine the effect of an avatar's cast shadow and foot vibrations on the virtual walking experience and cybersickness. The omnidirectional movie and the avatar's walking animation were synchronized, with the cast shadow reflecting the avatar's movement on the ground. Twenty participants were exposed to the virtual walking in six conditions (with/without foot vibrations and no/short/long shadow) and were asked to rate their sense of telepresence, walking experience, and occurrences of cybersickness. Our findings indicate that the synchronized foot vibrations enhanced telepresence as well as self-motion, walking, and leg-action sensations, while also reducing instances of nausea and disorientation sickness. The avatar's cast shadow was found to improve telepresence and leg-action sensation, but had no impact on self-motion and walking sensation. These results suggest that observation of the self-body cast shadow does not directly improve walking sensation, but is effective in enhancing telepresence and leg-action sensation, while foot vibrations are effective in improving telepresence and walking experience and reducing instances of cybersickness.

Indexed as

avatarcast shadowomnidirectional movietactile perceptionwalking

Identifiers

PMID38404740
PMCPMC10894555
OpenAlexW4392112968

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.