Evidence map›Paper›PMID 40463501›Full record

ArticleResearch (Washington, D.C.)2025

Emotional and Directional Enabled Programmable Flexible Haptic Interface for Enhanced Cognition in Disabled Community.

Yuhan Liu, Liuyang Han, Siqi Lv, Tao Jiang, Mingkai Duan, Hanyu Guo, Yuzhen Li, Qisen Xie, Yanru Chen, Dongkai Wang and 5 more

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

15 authors.

Yuhan LiuTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Liuyang HanTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Siqi LvTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Tao JiangTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Mingkai DuanTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Hanyu GuoTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Yuzhen LiTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Qisen XieTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Yanru ChenTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Dongkai WangDepartment of Electromechanical Engineering, Centre for Artificial Intelligence and Robotics, University of Macau, Macau 999078, China.
Ziheng LiuTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Wenjie ZhangTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Yanting GongDepartment of Electromechanical Engineering, Centre for Artificial Intelligence and Robotics, University of Macau, Macau 999078, China.
Junwen ZhongDepartment of Electromechanical Engineering, Centre for Artificial Intelligence and Robotics, University of Macau, Macau 999078, China.
Xiang QianTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.ORCID https://orcid.org/0000-0003-2487-8785

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advanced haptic feedback interfaces are essential for human-machine interaction, particularly in assistive technologies that offer versatile commands, simplify navigation, and enhance emotional interactions for individuals with visual and hearing impairments. Current systems, primarily reliant on Braille and mechanical announcements, fall short of addressing these needs. Existing haptic interfaces, while providing various haptic feedback modes, still face challenges including rigid, strong current, or high-voltage stimulation, limiting their applicability and long-term safety for widespread use. Here, the work demonstrates a flexible, integrable, and programmable haptic interface based on elastomer actuators that utilize a unique forming process to create customized local stiffness in a multilayer elastomer by varying the cross-linking density of elastomers. Complemented by tailored software, the system delivers a 4-dimensional haptic experience within a safe voltage of less than 50 V and a frequency range of 50 to 450 Hz, enabling high-fidelity emotional and navigational feedback. Demonstrations of this system achieve an average accuracy rate of 64.6% in emotional interactions without prior training, improving to 95.8% with learning mode, along with an average accuracy rate of 94.2% for 9 directional commands in navigation interactions.

Identifiers

PMID40463501
PMCPMC12133101

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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.