title: Mimicking the End Organ Architecture of Slowly Adapting Type I Afferents May Increase the Durability of Artificial Touch Sensors.
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.
authors.affiliation: Department of Systems and Information Engineering, University of Virginia.
authors.forename: Daine R
authors.initials: DR
authors.lastname: Lesniak
authors.affiliation: Department of Systems and Information Engineering, University of Virginia.
authors.forename: Gregory J
authors.initials: GJ
authors.lastname: Gerling
keywords: Tactile; biomechanics; biomimetic; mechanoreceptor; neurophysiology; sensor; slowly adapting type I afferent; somatosensory afferent; touch