A bioinspired analogous nerve towards artificial intelligence
Open accessAbstract
A bionic artificial device commonly integrates various distributed functional units to mimic the functions of biological sensory neural system, bringing intricate interconnections, complicated structure, and interference in signal transmission. Here we show an all-in-one bionic artificial nerve based on a separate electrical double-layers structure that integrates the functions of perception, recognition, and transmission. The bionic artificial nerve features flexibility, rapid response (<21 ms), high robustness, excellent durability (>10,000 tests), personalized cutability, and no energy consumption when no mechanical stimulation is being applied. The response signals are highly regionally differentiated for the mechanical stimulations, which enables the bionic artificial nerve to mimic the spatiotemporally dynamic logic of a biological neural network. Multifunctional touch interactions demonstrate the enormous potential of the bionic artificial nerve for human-machine hybrid perceptual enhancement. By incorporating the spatiotemporal resolution function and algorithmic analysis, we hope that bionic artificial nerves will promote further development of sophisticated neuroprosthetics and intelligent robotics.
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The APT nerve was employed for playing music, controlling positioning in a two-dimensional plane, and handling rotation.
“The APT nerve was employed for playing music, controlling positioning in a two-dimensional plane, and handling rotation [191].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [191]
The APT nerve can detect mechanical stimulation, discern the location of the stimulation, and transmit mechanosensitive signals.
“The APT nerve can detect mechanical stimulation, discern the location of the stimulation, and transmit mechanosensitive signals.”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [191]
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The emergence of AI-based wearable sensors for digital health technology: a review
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- Authors
- Liao, X., Song, W., Zhang, X., Yan, C., Li, T., Ren, H., Liu, C., Wang, Y., & Zheng, Y.
- Affiliations
- Nanyang Technological University (SG)
- National University of Singapore (SG)
- Beijing Institute of Technology (CN)
- Corresponding author
- Liao, Xinqin
- Zheng, Yuanjin
- Venue
- Nature Communications
- Published
- 2020-01-14
- Volume
- 11
- Issue
- 1
- Pages
- 268-268
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC6959309
- OpenAlex
- W2999029963
- Cited by
- 153
- References
- 41
- Citations by year
- 2026: 12 · 2025: 32 · 2024: 34 · 2023: 33 · 2022: 22 · 2021: 11 · 2020: 9
- FWCI
- 5.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- National University of Singapore (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (No. 61661146002)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Keywords
- mechanoreception, human-machine interaction, neuroprosthetics, intelligent robotics, flexible electronics, energy-efficient sensing
- MeSH terms
- Algorithms, Artificial Intelligence, Bionics, Humans, Nerve Fibers, Robotics, Touch, Biosensing Techniques, Neural Networks, Computer, Biomimetic Materials, Touch Perception
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