Evidence map›Paper›PMID 36616835›Full record

ArticleSensors (Basel, Switzerland)2022

Hybrid Target Selections by "Hand Gestures + Facial Expression" for a Rehabilitation Robot.

Yi Han, Xiangliang Zhang, Ning Zhang, Shuguang Meng, Tao Liu, Shuoyu Wang, Min Pan, Xiufeng Zhang, Jingang Yi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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
–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

0 citing papers in PubMed.

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

9 authors.

Yi HanThe State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China.
Xiangliang ZhangThe State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China.
Ning ZhangKey Laboratory of Rehabilitation Technical Aids Technology and System of the Ministry of Civil Affairs, National Research Center for Rehabilitation Technical Aids, Beijing 100176, China.
Shuguang MengFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650000, China.
Tao LiuThe State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China.ORCID 0000-0002-2797-0264
Shuoyu WangDepartment of Intelligent Mechanical Systems Engineering, Kochi University of Technology, 185 Miyanokuchi, Tosayamada-Cho, Kochi 782-8502, Japan.
Min PanDepartment of Mechanical Engineering, University of Bath, Bath BA2 7AY, UK.
Xiufeng ZhangKey Laboratory of Rehabilitation Technical Aids Technology and System of the Ministry of Civil Affairs, National Research Center for Rehabilitation Technical Aids, Beijing 100176, China.
Jingang YiDepartment of Mechanical and Aerospace Engineering, Rutgers University, Piscataway, NJ 08854, USA.

Funding

Key Research and Development Program of Zhejiang 2021C03051Key Research and Development Program of Zhejiang 2022C03103National Key R&D Program of China 2020YFC2007800National Science Foundation of China 52175033National Science Foundation of China U21A20120Zhejiang Provincial Natural Science Foundation LZ20E050002
6 · The paper itself

Abstract

In this study we propose a "hand gesture + face expression" human machine interaction technique, and apply this technique to bedridden rehabilitation robot. "Hand gesture + Facial expression" interactive technology combines the input mode of gesture and facial expression perception. It involves seven basic facial expressions that can be used to determine a target selecting task, while hand gestures are used to control a cursor's location. A controlled experiment was designed and conducted to evaluate the effectiveness of the proposed hybrid technology. A series of target selecting tasks with different target widths and layouts were designed to examine the recognition accuracy of hybrid control gestures. An interactive experiment applied to a rehabilitation robot is designed to verify the feasibility of this interactive technology applied to rehabilitation robots. The experimental results show that the "hand + facial expression" interactive gesture has strong robustness, which can provide a novel guideline for designing applications in VR interfaces, and it can be applied to the rehabilitation robots.

Indexed as

RoboticsAlgorithmsFacial ExpressionGesturesHandHumansRecognition, PsychologyUpper Extremityfacial expressionhybrid control gesturesinteractive tasksrehabilitation robottarget selection

Identifiers

PMID36616835
PMCPMC9824727

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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.