Evidence map›Paper›PMID 37293199›Full record

ArticleProceedings of the ACM on computer graphics and interactive techniques2023

ManiLoco: A VR-Based Locomotion Method for Concurrent Object Manipulation.

Dayu Wan, Xiaolei Guo, Jiahui Dong, Christos Mousas, Yingjie Chen

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the ACM on computer graphics and interactive techniques, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 1 institution in 1 country.

Dayu WanPurdue University, USA.
Xiaolei GuoPurdue University, USA.
Jiahui DongPurdue University, USA.
Christos MousasPurdue University, USA.
Yingjie ChenPurdue University, USA.
Purdue University West Lafayette · US

Funding

Virtual Reality Augmented Hands-on Cryo-EM TrainingR25EY029127 · NEI · PURDUE UNIVERSITY · PI CHEN, YINGJIE, JIANG, WEN · 2018 to 2023
$761k
NEI NIH HHS R25 EY029127
6 · The paper itself

Abstract

The use of virtual reality (VR) in laboratory skill training is rapidly increasing. In such applications, users often need to explore a large virtual environment within a limited physical space while completing a series of hand-based tasks (e.g., object manipulation). However, the most widely used controller-based teleport methods may conflict with the users' hand operation and result in a higher cognitive load, negatively affecting their training experiences. To alleviate these limitations, we designed and implemented a locomotion method called ManiLoco to enable hands-free interaction and thus avoid conflicts and interruptions from other tasks. Users can teleport to a remote object's position by taking a step toward the object while looking at it. We evaluated ManiLoco and compared it with state-of-the-art Point & Teleport in a within-subject experiment with 16 participants. The results confirmed the viability of our foot- and head-based approach and better support concurrent object manipulation in VR training tasks. Furthermore, our locomotion method does not require any additional hardware. It solely relies on the VR head-mounted display (HMD) and our implementation of detecting the user's stepping activity, and it can be easily applied to any VR application as a plugin.

Indexed as

LocomotionObject ManipulationRoom-scale VRTeleportationVirtual Reality Training

Identifiers

PMID37293199
PMCPMC10249678
OpenAlexW4376640253

What OpenQuestion holds

Textmetadata
LicenceTDM
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.