Evidence map›Paper›PMID 42582671›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2026

A Single-Source Dual-Drive Flexible Knee Assistive Exoskeleton for Elderly Daily Locomotion.

Shisheng Zhang, Yang Zhang, Yanzong Xu, Jinke Li, Yuquan Leng, Xinyu Wu

Abstract read
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

6 authors.

Shisheng ZhangGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.ORCID https://orcid.org/0000-0002-2072-9961
Yang ZhangMechanical Industry Key Laboratory of Intelligent Robotics Technology for 3C Product and the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.ORCID https://orcid.org/0009-0006-6523-9153
Yanzong XuMileBot Robotics Company Ltd., Shenzhen 518055, China.
Jinke LiGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Yuquan LengSchool of Biomedical Engineering, State Key Lab of Robotics and Systems, Harbin institute of Technology, Shenzhen 518055, China.
Xinyu WuGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The knees, as important parts in daily locomotion, carry the body weight and provide stability and flexibility. With the degradation of muscle and endurance, the elders get weak knee strength, which heavily affects their life quality. To address this issue, a single-source dual-drive flexible knee assistive exoskeleton is explored to assist the elders in their daily locomotion. Firstly, a single-source dual-drive architecture is designed. The left and right knee are controlled by single electric motor with clutch. It reduces the weight of exoskeleton and has the potential to enhance interaction safety and comfort with cable-driven and elastic elements. Secondly, a cyclic locomotion pattern recognition (LPR) methodology for daily walking situation is provided, adopted with a dual detection strategy fused with finite state machine and fuzzy control. Daily walking situations, e.g., level walking (LW), ramp ascending (RA), ramp descending (RD), stair ascending (SA), and stair descending (SD), could be recognized accurately and precisely. Finally, a time-shared assistive torque control strategy with finite state is conducted to effectively provide suitable auxiliary torque in various walking environments based on locomotion patterns. Three young participants and 3 elder participants participate in outdoor LPR experiments in real-world environment and indoor energy loss experiments. The initial experiment results indicate that the average precision of LPR reaches 98.89%, and the average metabolic cost and surface electromyography signals reduce as much as 28.20% and 67.33%, respectively, with the assistance of exoskeleton.

Identifiers

PMID42582671
PMCPMC13457901

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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.