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Sensors 2017, 17(9), 1999; doi:10.3390/s17091999

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors

1
Autonomous System and Robotics Research Centre, University of Salford, Manchester M5 4WT, UK
2
Research Centre E. Piaggio, University of Pisa, 56122 Pisa, Italy
3
Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
*
Author to whom correspondence should be addressed.
Received: 17 July 2017 / Revised: 19 August 2017 / Accepted: 28 August 2017 / Published: 31 August 2017
(This article belongs to the Section Physical Sensors)
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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 with 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 one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively. View Full-Text
Keywords: stretchable sensor; conductive fabric; inverse problem; performance parameters stretchable sensor; conductive fabric; inverse problem; performance parameters
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MDPI and ACS Style

Russo, S.; Nefti-Meziani, S.; Carbonaro, N.; Tognetti, A. A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors. Sensors 2017, 17, 1999.

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