Footwear discrimination using dynamic tactile information

Alin Drimus, Vedran Mikov

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Abstract:
This paper shows that it is possible to differentiate among various type of footwear solely by using highly dimensional pressure information provided by a sensorised insole. In order to achieve this, a person equipped with two sensorised insoles streaming real-time tactile data to a computer performs normal walking patterns. The sampled data is further transformed and reduced to sets of time series which are used for the classification of footwear. The pressure sensor is formed as a footwear inlay and is based on piezoresistive rubber having 1024 tactile cells providing normal pressure information in the form of a tactile image. The data is transmitted in realtime wirelessly at 30 fps from two such sensors. The online classification is using the dynamic time warping distances for different extracted features to assess the most similar type of footwear based on time series similarities. The paper shows that various footwear types yield distinct tactile patterns which can be assessed by the proposed algorithm.
Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Humanoid Robotics (Humanoids)
PublisherIEEE
Publication date2017
Pages278-282
ISBN (Print)978-1-5386-4679-3
ISBN (Electronic)978-1-5386-4678-6, 978-1-5386-4677-9
DOIs
Publication statusPublished - 2017
Event2017 IEEE-RAS 17th International Conference on Humanoid Robotics - Birmingham, United Kingdom
Duration: 15. Nov 201717. Nov 2017
http://humanoids2017.loria.fr/

Conference

Conference2017 IEEE-RAS 17th International Conference on Humanoid Robotics
CountryUnited Kingdom
CityBirmingham
Period15/11/201717/11/2017
Internet address

Fingerprint

Time series
Pressure sensors
Rubber
Sensors

Keywords

  • tactile sensor
  • piezoresistive rubber
  • dynamic time warping
  • classification

Cite this

Drimus, A., & Mikov, V. (2017). Footwear discrimination using dynamic tactile information. In Proceedings of the 17th International Conference on Humanoid Robotics (Humanoids) (pp. 278-282). IEEE. https://doi.org/10.1109/HUMANOIDS.2017.8246886
Drimus, Alin ; Mikov, Vedran. / Footwear discrimination using dynamic tactile information. Proceedings of the 17th International Conference on Humanoid Robotics (Humanoids). IEEE, 2017. pp. 278-282
@inproceedings{81ac19a2dc23457c82e89c829f2f25d9,
title = "Footwear discrimination using dynamic tactile information",
abstract = "Abstract:This paper shows that it is possible to differentiate among various type of footwear solely by using highly dimensional pressure information provided by a sensorised insole. In order to achieve this, a person equipped with two sensorised insoles streaming real-time tactile data to a computer performs normal walking patterns. The sampled data is further transformed and reduced to sets of time series which are used for the classification of footwear. The pressure sensor is formed as a footwear inlay and is based on piezoresistive rubber having 1024 tactile cells providing normal pressure information in the form of a tactile image. The data is transmitted in realtime wirelessly at 30 fps from two such sensors. The online classification is using the dynamic time warping distances for different extracted features to assess the most similar type of footwear based on time series similarities. The paper shows that various footwear types yield distinct tactile patterns which can be assessed by the proposed algorithm.",
keywords = "tactile sensor, piezoresistive rubber, dynamic time warping, classification",
author = "Alin Drimus and Vedran Mikov",
year = "2017",
doi = "10.1109/HUMANOIDS.2017.8246886",
language = "English",
isbn = "978-1-5386-4679-3",
pages = "278--282",
booktitle = "Proceedings of the 17th International Conference on Humanoid Robotics (Humanoids)",
publisher = "IEEE",
address = "United States",

}

Drimus, A & Mikov, V 2017, Footwear discrimination using dynamic tactile information. in Proceedings of the 17th International Conference on Humanoid Robotics (Humanoids). IEEE, pp. 278-282, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics, Birmingham, United Kingdom, 15/11/2017. https://doi.org/10.1109/HUMANOIDS.2017.8246886

Footwear discrimination using dynamic tactile information. / Drimus, Alin; Mikov, Vedran.

Proceedings of the 17th International Conference on Humanoid Robotics (Humanoids). IEEE, 2017. p. 278-282.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

TY - GEN

T1 - Footwear discrimination using dynamic tactile information

AU - Drimus, Alin

AU - Mikov, Vedran

PY - 2017

Y1 - 2017

N2 - Abstract:This paper shows that it is possible to differentiate among various type of footwear solely by using highly dimensional pressure information provided by a sensorised insole. In order to achieve this, a person equipped with two sensorised insoles streaming real-time tactile data to a computer performs normal walking patterns. The sampled data is further transformed and reduced to sets of time series which are used for the classification of footwear. The pressure sensor is formed as a footwear inlay and is based on piezoresistive rubber having 1024 tactile cells providing normal pressure information in the form of a tactile image. The data is transmitted in realtime wirelessly at 30 fps from two such sensors. The online classification is using the dynamic time warping distances for different extracted features to assess the most similar type of footwear based on time series similarities. The paper shows that various footwear types yield distinct tactile patterns which can be assessed by the proposed algorithm.

AB - Abstract:This paper shows that it is possible to differentiate among various type of footwear solely by using highly dimensional pressure information provided by a sensorised insole. In order to achieve this, a person equipped with two sensorised insoles streaming real-time tactile data to a computer performs normal walking patterns. The sampled data is further transformed and reduced to sets of time series which are used for the classification of footwear. The pressure sensor is formed as a footwear inlay and is based on piezoresistive rubber having 1024 tactile cells providing normal pressure information in the form of a tactile image. The data is transmitted in realtime wirelessly at 30 fps from two such sensors. The online classification is using the dynamic time warping distances for different extracted features to assess the most similar type of footwear based on time series similarities. The paper shows that various footwear types yield distinct tactile patterns which can be assessed by the proposed algorithm.

KW - tactile sensor

KW - piezoresistive rubber

KW - dynamic time warping

KW - classification

U2 - 10.1109/HUMANOIDS.2017.8246886

DO - 10.1109/HUMANOIDS.2017.8246886

M3 - Article in proceedings

SN - 978-1-5386-4679-3

SP - 278

EP - 282

BT - Proceedings of the 17th International Conference on Humanoid Robotics (Humanoids)

PB - IEEE

ER -

Drimus A, Mikov V. Footwear discrimination using dynamic tactile information. In Proceedings of the 17th International Conference on Humanoid Robotics (Humanoids). IEEE. 2017. p. 278-282 https://doi.org/10.1109/HUMANOIDS.2017.8246886