Evidence map›Paper›PMID 38534814›Full record

ArticleBiomimetics (Basel, Switzerland)2024

A Wearable Upper Limb Exoskeleton System and Intelligent Control Strategy.

Qiang Wang, Chunjie Chen, Xinxing Mu, Haibin Wang, Zhuo Wang, Sheng Xu, Weilun Guo, Xinyu Wu, Weimin Li

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

9 authors.

Qiang WangShandong Zhongke Advanced Technology Co., Ltd., Jinan 250100, China.
Chunjie ChenGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.ORCID 0000-0003-4855-9914
Xinxing MuShandong Zhongke Advanced Technology Co., Ltd., Jinan 250100, China.
Haibin WangShandong Zhongke Advanced Technology Co., Ltd., Jinan 250100, China.
Zhuo WangGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.ORCID 0000-0002-1709-7764
Sheng XuShandong Zhongke Advanced Technology Co., Ltd., Jinan 250100, China.ORCID 0000-0002-5086-4152
Weilun GuoShandong Zhongke Advanced Technology Co., Ltd., Jinan 250100, China.
Xinyu WuShandong Zhongke Advanced Technology Co., Ltd., Jinan 250100, China.
Weimin LiShandong Zhongke Advanced Technology Co., Ltd., Jinan 250100, China.

Funding

Key R&D program of Shandong Province, China 2021CXGC011304 and 2023CXGC010701National Key R&D Program of China 2022YFB4703500 and 2022YFC3601700Natural Science Foundation of China 62273325Quancheng 5150 Talent Introduction Plan
6 · The paper itself

Abstract

Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits auxiliary torque and is connected to the upper limb by bypassing the shoulder. Based on the K-nearest neighbors (KNN) algorithm and integrated fuzzy PID control strategy, the ULE identifies the handling posture and provides accurate active auxiliary force automatically. Overall, it has the quality of being light and easy to wear. In unassisted mode, the wearer's upper limbs minimally affect the range of movement. The KNN algorithm uses multi-dimensional motion information collected by the sensor, and the test accuracy is 94.59%. Brachioradialis muscle (BM), triceps brachii (TB), and biceps brachii (BB) electromyogram (EMG) signals were evaluated by 5 kg, 10 kg, and 15 kg weight conditions for five subjects, respectively, during lifting, holding, and squatting. Compared with the ULE without assistance and with assistance, the average peak values of EMG signals of BM, TB, and BB were reduced by 19-30% during the whole handling process, which verified that the developed ULE could provide practical assistance under different load conditions.

Indexed as

exoskeletonupper limb assistancewearable robotics

Identifiers

PMID38534814
PMCPMC10968600

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.