Evidence map›Paper›PMID 31235870›Full record

ArticleScientific reports2019

Suit-type Wearable Robot Powered by Shape-memory-alloy-based Fabric Muscle.

Seong Jun Park, Cheol Hoon Park

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

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

  1. Upper limb soft robotic wearable devices: a systematic review.Journal of neuroengineering and rehabilitation · 2022
    Pooled it
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  17. Wearables and their applications for the rehabilitation of elderly people.Medical & biological engineering & computing · 2022
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  19. Recent Progress in Active Mechanical Metamaterials and Construction Principles.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
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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

2 authors.

Seong Jun ParkDepartment of Robotics & Mechatronics, Korea Institute of Machinery & Materials, Daejeon, 34103, Korea.
Cheol Hoon ParkDepartment of Robotics & Mechatronics, Korea Institute of Machinery & Materials, Daejeon, 34103, Korea. parkch@kimm.re.kr.ORCID http://orcid.org/0000-0001-7942-7311

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A suit-type wearable robot (STWR) is a new type of soft wearable robot (SWR) that can be worn easily anywhere and anytime to assist the muscular strength of wearers because it can be worn like normal clothes and is comfortable to wear even with no power supply. This paper proposes an STWR, in which a shape-memory-alloy-based fabric muscle (SFM) is used as the actuator. The STWR, which weighs less than 1 kg, has a simple structure, with the following components: SFMs, wire encoders for measuring the contraction length of the SFMs, and BOA that fix the actuators on the forearms. In this study, a position controller for the SFM using the wire encoder was developed, and a prototype STWR was fabricated using this position controller. Moreover, by putting the STWR on a mannequin, step-response experiments were performed in which the arms of the mannequin lifted barbells weighing 2 kg and 4 kg to a certain target position. A fast response of moving to the target position in less than 1 s was observed in all steps except for the initial heating step for the 2 kg barbell. The response speed of the SFM was noticeably slower for the 4 kg barbell compared to that for the 2 kg barbell; it moved to the target position in approximately 3 s in all the steps except for the initial heating step. The SFM-applied STWR could overcome the limitations of conventional robots in terms of weight and inconvenience, thereby demonstrating the application potential of STWRs.

Identifiers

PMID31235870
PMCPMC6591235

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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.