Evidence map›Paper›PMID 36288316›Full record

ArticleScience advances2022

An artificial remote tactile device with 3D depth-of-field sensation.

Shanshan Zhu, Yuanheng Li, Huoerhute Yelemulati, Xinping Deng, Yongcheng Li, Jingjing Wang, Xiaojian Li, Guanglin Li, Paschalis Gkoupidenis, Yanlong Tai

Abstract read
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

10 authors.

Shanshan ZhuCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China.ORCID 0000-0001-7148-6659
Yuanheng LiCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China.
Huoerhute YelemulatiCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China.
Xinping DengCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China.
Yongcheng LiCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China.
Jingjing WangCAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute (BCBDI), SIAT, CAS, Shenzhen 518055, China.ORCID 0000-0002-6950-2581
Xiaojian LiCAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute (BCBDI), SIAT, CAS, Shenzhen 518055, China.ORCID 0000-0001-8130-0731
Guanglin LiCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China.ORCID 0000-0001-9016-2617
Paschalis GkoupidenisMolecular Electronics Department, Max Planck Institute for Polymer Research, Ackermannweg 10, Mainz 55128, Germany.ORCID 0000-0002-0139-0851
Yanlong TaiCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China.ORCID 0000-0002-9657-6842

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flexible tactile neuromorphic devices are becoming important as the impetus for the development of human-machine collaboration. However, accomplishing and further transcending human intelligence with artificial intelligence still confront many barriers. Here, we present a self-powered stretchable three-dimensional remote tactile device (3D-RTD) that performs the depth-of-field (DOF) sensation of external mechanical motions through a conductive-dielectric heterogeneous structure. The device can build a logic relationship precisely between DOF motions of an external active object and sensory potential signals of bipolar sign, frequency, amplitude, etc. The sensory mechanism is revealed on the basis of the electrostatic theory and multiphysics modeling, and the performance is verified via an artificial-biological hybrid system with micro/macroscale interaction. The feasibility of the 3D-RTD as an obstacle-avoidance patch for the blind is systematically demonstrated with a rat. This work paves the way for multimodal neuromorphic device that transcends the function of a biological one toward a new modality for brain-like intelligence.

Identifiers

PMID36288316
PMCPMC9604525

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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.