Neuromorphic capacitive tactile sensors inspired by slowly adaptive mechanoreceptors

Ella Janotte; Simeon Bamford; Ole Richter; Maurizio Valle; Chiara Bartolozzi

doi:10.1109/NEWCAS52662.2022.9841988

Neuromorphic capacitive tactile sensors inspired by slowly adaptive mechanoreceptors

Ella Janotte, Simeon Bamford, Ole Richter, Maurizio Valle, Chiara Bartolozzi

Bio-inspired Circuits & Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

59 Downloads (Pure)

Abstract

The sense of touch is essential in our everyday life as it allows us to interact with our environment. The same applies to robots and users of prostheses but requires sensing solutions that are power efficient and allow edge and embedded computation. In this paper, we present a capacitive, neuromorphic, event-driven, tactile sensor. The mixed-mode subthreshold circuit is implemented in 180nm technology and achieves a sensitivity of ≈ 30Hz/N in simulation with the SPICE simulation platform spectre.

Original language	English
Title of host publication	2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)
Publisher	IEEE
Pages	119-123
Number of pages	5
ISBN (Print)	978-1-6654-0106-7
DOIs	https://doi.org/10.1109/NEWCAS52662.2022.9841988
Publication status	Published - 22-Jun-2022
Event	2022 20th IEEE Interregional NEWCAS Conference (NEWCAS) - Quebec City, QC, Canada Duration: 19-Jun-2022 → 22-Jun-2022

Conference

Conference	2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)
Period	19/06/2022 → 22/06/2022

Keywords

Adaptation models
Sensitivity
Power demand
Neuromorphics
Computational modeling
Force
Neurons

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10.1109/NEWCAS52662.2022.9841988

Neuromorphic capacitive tactile sensors inspired by slowly adaptive mechanoreceptorsFinal publisher's version, 1.86 MBLicence: Taverne

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9841988

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title = "Neuromorphic capacitive tactile sensors inspired by slowly adaptive mechanoreceptors",

abstract = "The sense of touch is essential in our everyday life as it allows us to interact with our environment. The same applies to robots and users of prostheses but requires sensing solutions that are power efficient and allow edge and embedded computation. In this paper, we present a capacitive, neuromorphic, event-driven, tactile sensor. The mixed-mode subthreshold circuit is implemented in 180nm technology and achieves a sensitivity of ≈ 30Hz/N in simulation with the SPICE simulation platform spectre.",

keywords = "Adaptation models, Sensitivity, Power demand, Neuromorphics, Computational modeling, Force, Neurons",

author = "Ella Janotte and Simeon Bamford and Ole Richter and Maurizio Valle and Chiara Bartolozzi",

year = "2022",

month = jun,

day = "22",

doi = "10.1109/NEWCAS52662.2022.9841988",

language = "English",

isbn = "978-1-6654-0106-7",

pages = "119--123",

booktitle = "2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)",

publisher = "IEEE",

note = "2022 20th IEEE Interregional NEWCAS Conference (NEWCAS) ; Conference date: 19-06-2022 Through 22-06-2022",

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T1 - Neuromorphic capacitive tactile sensors inspired by slowly adaptive mechanoreceptors

AU - Janotte, Ella

AU - Bamford, Simeon

AU - Richter, Ole

AU - Valle, Maurizio

AU - Bartolozzi, Chiara

PY - 2022/6/22

Y1 - 2022/6/22

N2 - The sense of touch is essential in our everyday life as it allows us to interact with our environment. The same applies to robots and users of prostheses but requires sensing solutions that are power efficient and allow edge and embedded computation. In this paper, we present a capacitive, neuromorphic, event-driven, tactile sensor. The mixed-mode subthreshold circuit is implemented in 180nm technology and achieves a sensitivity of ≈ 30Hz/N in simulation with the SPICE simulation platform spectre.

AB - The sense of touch is essential in our everyday life as it allows us to interact with our environment. The same applies to robots and users of prostheses but requires sensing solutions that are power efficient and allow edge and embedded computation. In this paper, we present a capacitive, neuromorphic, event-driven, tactile sensor. The mixed-mode subthreshold circuit is implemented in 180nm technology and achieves a sensitivity of ≈ 30Hz/N in simulation with the SPICE simulation platform spectre.

KW - Adaptation models

KW - Sensitivity

KW - Power demand

KW - Neuromorphics

KW - Computational modeling

KW - Force

KW - Neurons

UR - https://ieeexplore.ieee.org/document/9841988/

U2 - 10.1109/NEWCAS52662.2022.9841988

DO - 10.1109/NEWCAS52662.2022.9841988

M3 - Conference contribution

SN - 978-1-6654-0106-7

SP - 119

EP - 123

BT - 2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)

PB - IEEE

T2 - 2022 20th IEEE Interregional NEWCAS Conference (NEWCAS)

Y2 - 19 June 2022 through 22 June 2022

ER -

Neuromorphic capacitive tactile sensors inspired by slowly adaptive mechanoreceptors

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Keywords

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