Abstract
We present the development of an innovative stretchable tactile sensor based on electrical impedance tomography (EIT) for applications in wearable robotics and rehabilitation. To extract the tactile information we exploit the electrical impedance tomography technique to reconstruct the local conductivity changes of a piezoresistive fabric. The EIT method poses several new challenges in the reconstruction, counterbalanced by the overcoming of many of the drawbacks of the current tactile sensors. Results obtained are preliminary but encouraging and we believe that the combination of the EIT method with advanced machine learning techniques will enable reliable wearable tactile sensing.
The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007–2013/ under REA grant agreement number 608022.
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Russo, S., Carbonaro, N., Tognetti, A. (2019). EIT-Based Tactile Sensing Patches for Rehabilitation and Human Machine Interaction. In: Carrozza, M., Micera, S., Pons, J. (eds) Wearable Robotics: Challenges and Trends. WeRob 2018. Biosystems & Biorobotics, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-01887-0_3
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DOI: https://doi.org/10.1007/978-3-030-01887-0_3
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