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A quantitative evaluation of drive pattern selection for optimizing EIT-based stretchable sensors

Russo, S; Nefti-Meziani, S; Carbonaro, N; Tognetti, A

Authors

S Russo

S Nefti-Meziani

N Carbonaro

A Tognetti



Abstract

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback in EIT-based sensors however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal to Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of a drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18% respectively.

Citation

Russo, S., Nefti-Meziani, S., Carbonaro, N., & Tognetti, A. (2017). A quantitative evaluation of drive pattern selection for optimizing EIT-based stretchable sensors. Sensors, 17(9), 1999. https://doi.org/10.3390/s17091999

Journal Article Type Article
Acceptance Date Aug 28, 2017
Online Publication Date Aug 31, 2017
Publication Date Aug 31, 2017
Deposit Date Sep 5, 2017
Publicly Available Date Sep 5, 2017
Journal Physical Sensors
Publisher MDPI
Volume 17
Issue 9
Pages 1999
DOI https://doi.org/10.3390/s17091999
Publisher URL http://dx.doi.org/10.3390/s17091999
Related Public URLs http://www.mdpi.com/journal/sensors
Additional Information Projects : Smart-e

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