We present the development of an innovative stretchable tac- tile sensor based on electrical impedance tomography (EIT) for appli- cations 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 cur- rent 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.

EIT-Based Tactile Sensing Patches for Rehabilitation and Human Machine Interaction

Nicola Carbonaro;Alessandro Tognetti
2018

Abstract

We present the development of an innovative stretchable tac- tile sensor based on electrical impedance tomography (EIT) for appli- cations 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 cur- rent 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.
978-3-030-01886-3
978-3-030-01887-0
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/932330
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