Literature DB >> 25705703

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

Daine R Lesniak1, Gregory J Gerling1.   

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.

Entities:  

Keywords:  Tactile; biomechanics; biomimetic; mechanoreceptor; neurophysiology; sensor; slowly adapting type I afferent; somatosensory afferent; touch

Year:  2014        PMID: 25705703      PMCID: PMC4332704          DOI: 10.1109/HAPTICS.2014.6775482

Source DB:  PubMed          Journal:  IEEE Haptics Symp        ISSN: 2324-7347


  11 in total

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8.  Validating a population model of tactile mechanotransduction of slowly adapting type I afferents at levels of skin mechanics, single-unit response and psychophysics.

Authors:  Gregory J Gerling; Isabelle I Rivest; Daine R Lesniak; Jacob R Scanlon; Lingtian Wan
Journal:  IEEE Trans Haptics       Date:  2014 Apr-Jun       Impact factor: 2.487

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Authors:  Daine R Lesniak; Kara L Marshall; Scott A Wellnitz; Blair A Jenkins; Yoshichika Baba; Matthew N Rasband; Gregory J Gerling; Ellen A Lumpkin
Journal:  Elife       Date:  2014-01-21       Impact factor: 8.140

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