Evidence map›Paper›PMID 38099199›Full record

ReviewFrontiers in neuroscience2023

Research status of elderly-care robots and safe human-robot interaction methods.

Donghui Zhao, Xingwang Sun, Bo Shan, Zihao Yang, Junyou Yang, Houde Liu, Yinlai Jiang, Yokoi Hiroshi

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

Donghui ZhaoSchool of Electrical Engineering, Shenyang University of Technology, Shenyang, China.
Xingwang SunSchool of Electrical Engineering, Shenyang University of Technology, Shenyang, China.
Bo ShanSchool of Electrical Engineering, Shenyang University of Technology, Shenyang, China.
Zihao YangSchool of Electrical Engineering, Shenyang University of Technology, Shenyang, China.
Junyou YangSchool of Electrical Engineering, Shenyang University of Technology, Shenyang, China.
Houde LiuTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Yinlai JiangDepartment of Mechanical Engineering and Intelligent Systems, University of Electro-Communications, Tokyo, Japan.
Yokoi HiroshiDepartment of Mechanical Engineering and Intelligent Systems, University of Electro-Communications, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Faced with the increasingly severe global aging population with fewer children, the research, development, and application of elderly-care robots are expected to provide some technical means to solve the problems of elderly care, disability and semi-disability nursing, and rehabilitation. Elderly-care robots involve biomechanics, computer science, automatic control, ethics, and other fields of knowledge, which is one of the most challenging and most concerned research fields of robotics. Unlike other robots, elderly-care robots work for the frail elderly. There is information exchange and energy exchange between people and robots, and the safe human-robot interaction methods are the research core and key technology. The states of the art of elderly-care robots and their various nursing modes and safe interaction methods are introduced and discussed in this paper. To conclude, considering the disparity between current elderly care robots and their anticipated objectives, we offer a comprehensive overview of the critical technologies and research trends that impact and enhance the feasibility and acceptance of elderly care robots. These areas encompass the collaborative assistance of diverse assistive robots, the establishment of a novel smart home care model for elderly individuals using sensor networks, the optimization of robot design for improved flexibility, and the enhancement of robot acceptability.

Indexed as

acceptabilityelderly-care robotsnursing modepracticalitysafe interaction methods

Identifiers

PMID38099199
PMCPMC10720664

What OpenQuestion holds

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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.