Evidence map›Paper›PMID 40710277›Full record

ArticleBiomimetics (Basel, Switzerland)2025

An Intuitive and Efficient Teleoperation Human-Robot Interface Based on a Wearable Myoelectric Armband.

Long Wang, Zhangyi Chen, Songyuan Han, Yao Luo, Xiaoling Li, Yang Liu

Abstract read
In one paragraph

Article 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Long WangSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710048, China.
Zhangyi ChenSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710048, China.
Songyuan HanSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710048, China.
Yao LuoSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710048, China.
Xiaoling LiSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710048, China.
Yang LiuSchool of Art and Design, Xi'an University of Technology, Xi'an 710049, China.

Funding

the Basic Research Program of Natural Science in Shaanxi Province 2025JC-YBQN-311the Key R&D project of Shaanxi Province under Grant 2023-YBGY-505
6 · The paper itself

Abstract

Although artificial intelligence technologies have significantly enhanced autonomous robots' capabilities in perception, decision-making, and planning, their autonomy may still fail when faced with complex, dynamic, or unpredictable environments. Therefore, it is critical to enable users to take over robot control in real-time and efficiently through teleoperation. The lightweight, wearable myoelectric armband, due to its portability and environmental robustness, provides a natural human-robot gesture interaction interface. However, current myoelectric teleoperation gesture control faces two major challenges: (1) poor intuitiveness due to visual-motor misalignment; and (2) low efficiency from discrete, single-degree-of-freedom control modes. To address these challenges, this study proposes an integrated myoelectric teleoperation interface. The interface integrates the following: (1) a novel hybrid reference frame aimed at effectively mitigating visual-motor misalignment; and (2) a finite state machine (FSM)-based control logic designed to enhance control efficiency and smoothness. Four experimental tasks were designed using different end-effectors (gripper/dexterous hand) and camera viewpoints (front/side view). Compared to benchmark methods, the proposed interface demonstrates significant advantages in task completion time, movement path efficiency, and subjective workload. This work demonstrates the potential of the proposed interface to significantly advance the practical application of wearable myoelectric sensors in human-robot interaction.

Indexed as

human–robot interactionhybrid reference frameteleoperationwearable myoelectric armband

Identifiers

PMID40710277
PMCPMC12292948

What OpenQuestion holds

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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.