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

Russo, S, Nefti-Meziani, S, Carbonaro, N and Tognetti, A 2017, 'A quantitative evaluation of drive pattern selection for optimizing EIT-based stretchable sensors' , Physical Sensors, 17 (9) , p. 1999.

PDF - Published Version
Available under License Creative Commons Attribution 4.0.

Download (6MB) | Preview
[img] PDF - Accepted Version
Restricted to Repository staff only

Download (4MB)


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.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: Physical Sensors
Publisher: MDPI
ISSN: 1424-8220
Related URLs:
Funders: People Programme (Marie Curie 355 Actions) of the European Union Seventh Framework Programme FP7/2007-2013/
Depositing User: USIR Admin
Date Deposited: 05 Sep 2017 10:58
Last Modified: 15 Feb 2022 22:24
URI: https://usir.salford.ac.uk/id/eprint/43682

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)


Downloads per month over past year