Evidence map›Paper›PMID 25705703›Full record

ArticleIEEE Haptics Symposium : [proceedings]. IEEE Haptics Symposium2014

Mimicking the End Organ Architecture of Slowly Adapting Type I Afferents May Increase the Durability of Artificial Touch Sensors.

Daine R Lesniak, Gregory J Gerling

Abstract read
In one paragraph

Article in IEEE Haptics Symposium : [proceedings]. IEEE Haptics Symposium, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Daine R LesniakDepartment of Systems and Information Engineering, University of Virginia.
Gregory J GerlingDepartment of Systems and Information Engineering, University of Virginia.

Funding

Peripheral Mechanisms Governing Tactile Encoding During Normal Target RemodelingR01NS073119 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GERLING, GREGORY JOHN, LUMPKIN, ELLEN A · 2010 to 2016
$2.5M
NINDS NIH HHS R01 NS073119
6 · The paper itself

Abstract

In effort to mimic the sensitivity and efficient information transfer of natural tactile afferents, recent work has combined force transducers and computational models of mechanosensitive afferents. Sensor durability, another feature important to sensor design, might similarly capitalize upon biological rules. In particular, gains in sensor durability might leverage insight from the compound end organ of the slowly adapting type I afferent, especially its multiple sites of spike initiation that reset each other. This work develops models of compound spiking sensors using a computational network of transduction functions and leaky integrate and fire models (together a spike encoder, the software element of a compound spiking sensor), informed by the output of an existing force transducer (hardware sensing elements of a compound spiking sensor). Individual force transducer failures are simulated with and without resetting between spike encoders to test the importance of both resetting and configuration on system durability. The results indicate that the resetting of adjacent spike encoders, upon the firing of a spike by any one, is an essential mechanism to maintain a stable overall response in the midst of transducer failure. Furthermore, results suggest that when resetting is enabled, the durability of a compound sensor is maximized when individual transducers are paired with spike encoders and multiple, paired units are employed. To explore these ideas more fully, use cases examine the design of a compound sensor to either reach a target lifetime with a set probability or determine how often to schedule maintenance to control the probability of failure.

Indexed as

biomechanicsbiomimeticmechanoreceptorneurophysiologysensorslowly adapting type I afferentsomatosensory afferentTactiletouch

Identifiers

PMID25705703
PMCPMC4332704

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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.