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Modular piezoresistive smart textile for state estimation of cloths

Remko Proesmans (UGent) , Andreas Verleysen (UGent) , Robbe Vleugels, Paula Veske-Lepp (UGent) , Victor-Louis De Gusseme (UGent) and Francis wyffels (UGent)
(2022) SENSORS. 22(1).
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Abstract
Smart textiles have found numerous applications ranging from health monitoring to smart homes. Their main allure is their flexibility, which allows for seamless integration of sensing in everyday objects like clothing. The application domain also includes robotics; smart textiles have been used to improve human-robot interaction, to solve the problem of state estimation of soft robots, and for state estimation to enable learning of robotic manipulation of textiles. The latter application provides an alternative to computationally expensive vision-based pipelines and we believe it is the key to accelerate robotic learning of textile manipulation. Current smart textiles, however, maintain wired connections to external units, which impedes robotic manipulation, and lack modularity to facilitate state estimation of large cloths. In this work, we propose an open-source, fully wireless, highly flexible, light, and modular version of a piezoresistive smart textile. Its output stability was experimentally quantified and determined to be sufficient for classification tasks. Its functionality as a state sensor for larger cloths was also verified in a classification task where two of the smart textiles were sewn onto a piece of clothing of which three states are defined. The modular smart textile system was able to recognize these states with average per-class F1-scores ranging from 85.7 to 94.6% with a basic linear classifier.
Keywords
smart textile, deformable object classification, deformable object manipulation

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MLA
Proesmans, Remko, et al. “Modular Piezoresistive Smart Textile for State Estimation of Cloths.” SENSORS, vol. 22, no. 1, 2022, doi:10.3390/s22010222.
APA
Proesmans, R., Verleysen, A., Vleugels, R., Veske-Lepp, P., De Gusseme, V.-L., & wyffels, F. (2022). Modular piezoresistive smart textile for state estimation of cloths. SENSORS, 22(1). https://doi.org/10.3390/s22010222
Chicago author-date
Proesmans, Remko, Andreas Verleysen, Robbe Vleugels, Paula Veske-Lepp, Victor-Louis De Gusseme, and Francis wyffels. 2022. “Modular Piezoresistive Smart Textile for State Estimation of Cloths.” SENSORS 22 (1). https://doi.org/10.3390/s22010222.
Chicago author-date (all authors)
Proesmans, Remko, Andreas Verleysen, Robbe Vleugels, Paula Veske-Lepp, Victor-Louis De Gusseme, and Francis wyffels. 2022. “Modular Piezoresistive Smart Textile for State Estimation of Cloths.” SENSORS 22 (1). doi:10.3390/s22010222.
Vancouver
1.
Proesmans R, Verleysen A, Vleugels R, Veske-Lepp P, De Gusseme V-L, wyffels F. Modular piezoresistive smart textile for state estimation of cloths. SENSORS. 2022;22(1).
IEEE
[1]
R. Proesmans, A. Verleysen, R. Vleugels, P. Veske-Lepp, V.-L. De Gusseme, and F. wyffels, “Modular piezoresistive smart textile for state estimation of cloths,” SENSORS, vol. 22, no. 1, 2022.
@article{8732517,
  abstract     = {{Smart textiles have found numerous applications ranging from health monitoring to smart homes. Their main allure is their flexibility, which allows for seamless integration of sensing in everyday objects like clothing. The application domain also includes robotics; smart textiles have been used to improve human-robot interaction, to solve the problem of state estimation of soft robots, and for state estimation to enable learning of robotic manipulation of textiles. The latter application provides an alternative to computationally expensive vision-based pipelines and we believe it is the key to accelerate robotic learning of textile manipulation. Current smart textiles, however, maintain wired connections to external units, which impedes robotic manipulation, and lack modularity to facilitate state estimation of large cloths. In this work, we propose an open-source, fully wireless, highly flexible, light, and modular version of a piezoresistive smart textile. Its output stability was experimentally quantified and determined to be sufficient for classification tasks. Its functionality as a state sensor for larger cloths was also verified in a classification task where two of the smart textiles were sewn onto a piece of clothing of which three states are defined. The modular smart textile system was able to recognize these states with average per-class F1-scores ranging from 85.7 to 94.6% with a basic linear classifier.}},
  articleno    = {{222}},
  author       = {{Proesmans, Remko and Verleysen, Andreas and Vleugels, Robbe and Veske-Lepp, Paula and De Gusseme, Victor-Louis and wyffels, Francis}},
  issn         = {{1424-8220}},
  journal      = {{SENSORS}},
  keywords     = {{smart textile,deformable object classification,deformable object manipulation}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{14}},
  title        = {{Modular piezoresistive smart textile for state estimation of cloths}},
  url          = {{http://doi.org/10.3390/s22010222}},
  volume       = {{22}},
  year         = {{2022}},
}
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