Evidence map›Paper›PMID 35095164›Full record

ArticleThe International journal, advanced manufacturing technology2022

A novel AR remote collaborative platform for sharing 2.5D gestures and gaze.

Yue Wang, Peng Wang, Zhiyong Luo, Yuxiang Yan

Abstract read
In one paragraph

Article in The International journal, advanced manufacturing technology, 2022. 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
–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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Yue WangSchool of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chong Qing, 400065 China.
Peng WangSchool of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chong Qing, 400065 China.
Zhiyong LuoSchool of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chong Qing, 400065 China.
Yuxiang YanCyber-Physical Interaction Lab, Northwestern Polytechnical University, Xi'an, 710072 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although sharing gestures and gaze can improve AR remote collaboration, most current systems only enable collaborators to share 2D or 3D gestures, and the unimodal HCI interface remains dominant. To address this problem, we describe a novel remote collaborative platform based on 2.5D gestures and gaze (2.5DGG), which supports an expert who collaborates with a worker (e.g., during assembly or training tasks). We investigate the impact of sharing the remote site's 2.5DGG using spatial AR (SAR) remote collaboration in manufacturing. Compared to other systems, there is a key advantage that it can provide more natural and intuitive multimodal interaction based on 2.5DGG. We track the remote experts' gestures and eye gaze using Leap Motion and aGlass, respectively, in a VR space displaying the live video stream of the local physical workspace and visualize them onto the local work scenario by a projector. The results of an exploratory user study demonstrate that 2.5DGG has a clear difference in performance time and collaborative experience, and it is better than the traditional one.

Indexed as

Augmented realityGestures and gazeMultimodal interactionPhysical tasksRemote collaboration

Identifiers

PMID35095164
PMCPMC8782427

What OpenQuestion holds

Textmetadata
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.