Cited by 882Advanced Sensor and Energy Harvesting MaterialsTactile and Sensory InteractionsNeuroscience and Neural Engineering

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index; none of the 13 sources its claims cite is checked for support yet.

A skin-inspired organic digital mechanoreceptor

Open access

Abstract

Sensing the force digitally: Our skin provides us with a flexible waterproof barrier, but it also contains a sensor array that feels the world around us. This array provides feedback and helps us to avoid a hot object or increase the strength of our grip on an object that may be slipping away. Tee et al. describe an approach to simulate the mechanoreceptors of human skin, using pressure-sensitive foils and printed ring oscillators (see the Perspective by Anikeeva and Koppes). The sensor successfully converted pressure into a digital response in a pressure range comparable to that found in a human grip. Science , this issue p. 313 ; see also p. 274

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

The authors present DiTact, a skin-inspired artificial mechanoreceptor built from flexible printed organic circuits that converts pressure directly into digital frequency signals (0–200 Hz) with a sublinear response mimicking slow-adapting skin mechanoreceptors. The sensor output was used to optogenetically and electrically stimulate mouse cortical and hippocampal neurons in vitro, demonstrating a step toward neural-integrated touch feedback for prosthetic limbs.

Key findings

  • The DiTact system transduces pressure into digital frequency signals directly, with an output frequency range of 0 to 200 Hz and a sublinear response to increasing force that mimics slow-adapting skin mechanoreceptors.
  • In the on state (at 100 kPa), power dissipation of the prototype was 18.4 mW at 11 V and 2.0 mW at 6 V, which the authors state compares favorably to analog approaches.
  • The engineered channelrhodopsin bC1C2(s/v) had larger photocurrents and faster off-kinetics than ChR2(HR) and ChETA(EA), and reliably evoked action potentials at frequencies up to 200 Hz for prolonged intervals; spike probability was 100% in bC1C2(s/v)-expressing neurons and decreased in ChETA(EA)-expressing neurons during prolonged stimulation (ChETA(EA), n = 16; bC1C2(s/v), n = 10).
  • The DiTact output stimulated in vitro mouse somatosensory cortical neurons in accordance with applied pressure, with neurons firing in accordance with the stimulation pulse; the system was also coupled to an inorganic oscillator to electrically stimulate hippocampal neurons in a multielectrode array.

Methods

  • The DiTact prototype comprises a three-inverter (three-stage) printed organic ring oscillator on a flexible plastic sheet, a piezoresistive pressure sensor made of a carbon nanotube composite dispersed in a polyurethane elastomer molded into pyramidal microstructures, and a voltage-divider configuration in which the sensor modulates the oscillator's supply voltage and thus its frequency.
  • Optogenetic interfacing: the sensor output was conditioned via an edge detector to a 2-ms pulse triggering an LED (475 nm, 5 mW/mm²) to stimulate PV+ neurons in acute slices of mouse somatosensory cortex; whole-cell patch-clamp recordings compared ChETA(EA) and bC1C2(s/v) constructs, with error bars denoting SEM.
  • Electrical interfacing: an inorganic oscillator was coupled to the pressure sensor and the resulting frequency signal was used to stimulate hippocampal neurons in a multielectrode array.

Limitations

  • The paper states the system currently encodes static pressure stimuli only, and that implementing temporal adaptation to both static and nonstatic stimuli (e.g., increased firing rate for moving stimuli, decreased firing rate for constant stimuli) will be important to fully mimic biological mechanoreceptors.
  • The paper notes that electrical stimulation is more applicable to conventional prosthetics, and that optogenetic stimulation was used as a reliable noncontact method to demonstrate feasibility of interfacing with biological neural circuits.
  • The paper states the 11 V supply voltage was chosen to set the maximum frequency to 200 Hz, and that the supply voltage can be further reduced via reduction of the dielectric thickness (organic oscillators operating at 3 V have been demonstrated).

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1126/science.aaa9306

Cites

32 of 32 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 13 cited sources checked · 0 supported · 0 flagged

Show all 16 claims

  • It may state two separate claims as one. 4
  • Probably not a substantial claim. 11
13 of 13
  • The paper relies on this without support.

    The typical frequency range of biological mechanoreceptors is 0–200 Hz.

    “so as to match the typical frequency range of biological mechanoreceptors.”
    “a range similar to that of slow-adapting mechanoreceptors”
  • The paper relies on this without support.

    Human skin contains an enormously large density of sensors.

    “an enormously large density of sensors as found in human skin”
2 of 2

Claims other papers make about this one

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Citations

Cites

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Show all 32 references

Research works printed but not linked: 2

  1. E. P. Gardner Touch (eLS/Wiley Online Library 2001). 10.1038/npg.els.0000219 · DOI
  2. 10.1038/nmat2896 · DOI · Paper page

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Metadata

Authors
Tee, B. C.-K., Chortos, A., Berndt, A., Nguyen, A. K., Tom, A., McGuire, A., Lin, Z. C., Tien, K., Bae, W.-G., Wang, H., Mei, P., Chou, H.-H., Cui, B., Deisseroth, K., Ng, T. N., & Bao, Z.
Affiliations
  • Stanford University (US)
  • Palo Alto Research Center (US)
Corresponding author
  • Tee, Benjamin C.-K.
  • Chortos, Alex
  • Berndt, Andre
  • Bao, Zhenan
Venue
Science
Published
2015-10-16
Volume
350
Issue
6258
Pages
313-316
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2212410734
Cited by
882
References
32
Citations by year
2026: 53 · 2025: 62 · 2024: 66 · 2023: 70 · 2022: 75 · 2021: 95 · 2020: 91 · 2019: 105 · 2018: 106 · 2017: 88 · 2016: 67 · 2015: 4
FWCI
43.89
Type
journal article
Language
en
Open access
Locations
  • Science (publishedVersion)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • Xerox Foundation
  • gency for Science Technology and Research Singapore (A*STAR)
  • National IT Industry Promotion Agency
  • MSIP (Ministry of Science, ICT and Future Planning), Korea (NIPA-2014-H0201-14-1001)
  • Samsung Electronics
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
Keywords
mechanoreceptors, pressure sensing, optogenetics, somatosensory neurons, neurostimulation, electronic skin, artificial limbs
MeSH terms
Animals, Cerebral Cortex, Transcutaneous Electric Nerve Stimulation, Hand, Humans, Mechanoreceptors, Pressure, Skin, Touch, Transistors, Electronic, Mice, Neural Prostheses, Optogenetics, In Vitro Techniques

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