Evidence map›Paper›PMID 37288339›Full record

ArticleScience China. Technological sciences2023

Interactive method research of dual mode information coordination integration for astronaut gesture and eye movement signals based on hybrid model.

HongChao Zhuang, YiLu Xia, Ning Wang, WeiHua Li, Lei Dong, Bo Li

Open access · bronzeAbstract read
In one paragraph

Article in Science China. Technological sciences, 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
0.9field-weighted citation impact, top 26% 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, 5 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

6 authors at 3 institutions in 1 country.

HongChao ZhuangSchool of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin, 300222 China.
YiLu XiaSchool of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin, 300222 China.
Ning WangSchool of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin, 300222 China.
WeiHua LiSchool of Automotive Engineering, Harbin Institute of Technology (Weihai), Weihai, 264209 China.
Lei DongSchool of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin, 300222 China.
Bo LiTianjin Institute of Aerospace Mechanical and Electrical Equipment, Tianjin, 300458 China.
Tianjin University of Technology and Education · CNTianjin Special Equipment Supervision and Inspection Technology Research Institute · CNWeihai Science and Technology Bureau · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lightweight human-robot interaction model with high real-time, high accuracy, and strong anti-interference capability can be better applied to future lunar surface exploration and construction work. Based on the feature information inputted from the monocular camera, the signal acquisition and processing fusion of the astronaut gesture and eye-movement modal interaction can be performed. Compared with the single mode, the human-robot interaction model of bimodal collaboration can achieve the issuance of complex interactive commands more efficiently. The optimization of the target detection model is executed by inserting attention into YOLOv4 and filtering image motion blur. The central coordinates of pupils are identified by the neural network to realize the human-robot interaction in the eye movement mode. The fusion between the astronaut gesture signal and eye movement signal is performed at the end of the collaborative model to achieve complex command interactions based on a lightweight model. The dataset used in the network training is enhanced and extended to simulate the realistic lunar space interaction environment. The human-robot interaction effects of complex commands in the single mode are compared with those of complex commands in the bimodal collaboration. The experimental results show that the concatenated interaction model of the astronaut gesture and eye movement signals can excavate the bimodal interaction signal better, discriminate the complex interaction commands more quickly, and has stronger signal anti-interference capability based on its stronger feature information mining ability. Compared with the command interaction realized by using the single gesture modal signal and the single eye movement modal signal, the interaction model of bimodal collaboration is shorter about 79% to 91% of the time under the single mode interaction. Regardless of the influence of any image interference item, the overall judgment accuracy of the proposed model can be maintained at about 83% to 97%. The effectiveness of the proposed method is verified.

Indexed as

CBAMgesture and eye movementhuman-robot interactionhybrid modelYOLOv4

Identifiers

PMID37288339
PMCPMC10182537
OpenAlexW4376616857

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.