Evidence map›Paper›PMID 40422089›Full record

ReviewBiomimetics (Basel, Switzerland)2025

Research Status and Development Trend of Lower-Limb Squat-Assistant Wearable Devices.

Lin Li, Zehan Chen, Rong Hong, Yanping Qu, Xinqin Gao, Xupeng Wang

Abstract readReview
In one paragraph

Review in Biomimetics (Basel, Switzerland), 2025. 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

6 authors.

Lin LiSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.
Zehan ChenDepartment of Industrial Design, Xi'an University of Technology, Xi'an 710054, China.
Rong HongDepartment of Industrial Design, Xi'an University of Technology, Xi'an 710054, China.
Yanping QuSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.
Xinqin GaoSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.
Xupeng WangSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China.

Funding

Xi'an Science and Technology Bureau 24RKYJ0073
6 · The paper itself

Abstract

The accelerating population aging and increasing demand for higher work efficiency have made the research and the application of lower-limb assistive exoskeletons a primary focus in recent years. This paper reviews the research progress of lower-limb squat assistive wearable devices, with a focus on classification methods, research outcomes, and products from both domestic and international markets. It also analyzes the key technologies involved in their development, such as mechanical mechanisms, control strategies, motion sensing, and effectiveness validation. From an industrial design perspective, the paper also explores the future prospects of lower-limb squat assistive wearable devices in four key areas: multi-signal sensing, intelligent control, human-machine collaboration, and experimental validation. Finally, the paper discusses future development trends in this field.

Indexed as

exoskeletonexperimental evaluationmotion perceptionsquat assistsummarize

Identifiers

PMID40422089
PMCPMC12109048

What OpenQuestion holds

Textmetadata
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.