Evidence map›Paper›PMID 36146344›Full record

ArticleSensors (Basel, Switzerland)2022

Neuromorphic Tactile Edge Orientation Classification in an Unsupervised Spiking Neural Network.

Fraser L A Macdonald, Nathan F Lepora, Jörg Conradt, Benjamin Ward-Cherrier

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

4 authors.

Fraser L A MacdonaldDepartment of Engineering Mathematics, University of Bristol, Bristol BS8 1TW, UK.ORCID 0000-0002-0640-9531
Nathan F LeporaDepartment of Engineering Mathematics, University of Bristol, Bristol BS8 1TW, UK.ORCID 0000-0001-5327-1523
Jörg ConradtSchool of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden.ORCID 0000-0001-5998-9640
Benjamin Ward-CherrierDepartment of Engineering Mathematics, University of Bristol, Bristol BS8 1TW, UK.ORCID 0000-0001-9614-7004

Funding

UK Research and Innovation EP/R513179/1
6 · The paper itself

Abstract

Dexterous manipulation in robotic hands relies on an accurate sense of artificial touch. Here we investigate neuromorphic tactile sensation with an event-based optical tactile sensor combined with spiking neural networks for edge orientation detection. The sensor incorporates an event-based vision system (mini-eDVS) into a low-form factor artificial fingertip (the NeuroTac). The processing of tactile information is performed through a Spiking Neural Network with unsupervised Spike-Timing-Dependent Plasticity (STDP) learning, and the resultant output is classified with a 3-nearest neighbours classifier. Edge orientations were classified in 10-degree increments while tapping vertically downward and sliding horizontally across the edge. In both cases, we demonstrate that the sensor is able to reliably detect edge orientation, and could lead to accurate, bio-inspired, tactile processing in robotics and prosthetics applications.

Indexed as

RoboticsTouch PerceptionNeural Networks, ComputerTouchneuromorphicspiking neural networktactile robotics

Identifiers

PMID36146344
PMCPMC9500632

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.