TY - GEN
T1 - Texture discrimination using a neuromimetic asynchronous flexible tactile sensor array with spatial frequency encoding
AU - Slepyan, Ariel
AU - Sankar, Sriramana
AU - Thakor, Nitish
N1 - Funding Information:
*Research supported by NSF award #1849417 and the Department of Army/USMRAA OR190125 grants. Ariel Slepyan, Sriramana Sankar, and Nitish Thakor are with the department of Biomedical Engineering at Johns Hopkins University,
Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/4
Y1 - 2021/5/4
N2 - State-of-the-art tactile sensing arrays are not scalable to large numbers of sensing units due to their raster-scanned process. This interface process results in a high degree of wiring complexity and a tradeoff between spatial and temporal resolution. In this paper, we present a new neuromimetic tactile sensing scheme that allows for single-wire signal transduction and asynchronous signal transmission - without the incorporation of electronics into each sensing element. A prototype device with spatial frequency encoding was developed using flexible fabric-based e-textile materials, and the ability of this new sensing scheme was demonstrated through a texture discrimination task. Overall, the neuromimetic spatial frequency encoded sensor array had comparable performance to the state-of-the-art tactile sensor array and achieved a classification accuracy of 86.58%. Future tactile sensing systems and electronic skins can emulate the spatial frequency encoding architecture presented here to become dense and numerous while retaining excellent temporal resolution.
AB - State-of-the-art tactile sensing arrays are not scalable to large numbers of sensing units due to their raster-scanned process. This interface process results in a high degree of wiring complexity and a tradeoff between spatial and temporal resolution. In this paper, we present a new neuromimetic tactile sensing scheme that allows for single-wire signal transduction and asynchronous signal transmission - without the incorporation of electronics into each sensing element. A prototype device with spatial frequency encoding was developed using flexible fabric-based e-textile materials, and the ability of this new sensing scheme was demonstrated through a texture discrimination task. Overall, the neuromimetic spatial frequency encoded sensor array had comparable performance to the state-of-the-art tactile sensor array and achieved a classification accuracy of 86.58%. Future tactile sensing systems and electronic skins can emulate the spatial frequency encoding architecture presented here to become dense and numerous while retaining excellent temporal resolution.
UR - http://www.scopus.com/inward/record.url?scp=85107491244&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107491244&partnerID=8YFLogxK
U2 - 10.1109/NER49283.2021.9441136
DO - 10.1109/NER49283.2021.9441136
M3 - Conference contribution
AN - SCOPUS:85107491244
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 191
EP - 194
BT - 2021 10th International IEEE/EMBS Conference on Neural Engineering, NER 2021
PB - IEEE Computer Society
T2 - 10th International IEEE/EMBS Conference on Neural Engineering, NER 2021
Y2 - 4 May 2021 through 6 May 2021
ER -