scholarly journals Complex conductivity reconstruction in multiple frequency electrical impedance tomography for fabric-based pressure sensor

Sensor Review ◽  
2015 ◽  
Vol 35 (1) ◽  
pp. 85-97 ◽  
Author(s):  
C.L. Yang ◽  
A. Mohammed ◽  
Y Mohamadou ◽  
T. I. Oh ◽  
M. Soleimani
Keyword(s):  
Electrical Impedance Tomography ◽  
Pressure Sensor ◽  
Electrical Impedance ◽  
Pressure Sensors ◽  
Complex Impedance ◽  
Electrical Impedance Spectroscopy ◽  
Multiple Frequency ◽  
Impedance Tomography ◽  
Content Type ◽  
Pressure Mapping

Purpose – The aim of this paper is to introduce and to evaluate the performance of a multiple frequency complex impedance reconstruction for fabric-based EIT pressure sensor. Pressure mapping is an important and challenging area of modern sensing technology. It has many applications in areas such as artificial skins in Robotics and pressure monitoring on soft tissue in biomechanics. Fabric-based sensors are being developed in conjunction with electrical impedance tomography (EIT) for pressure mapping imaging. This is potentially a very cost-effective pressure mapping imaging solution in particular for imaging large areas. Fabric-based EIT pressure sensors aim to provide a pressure mapping image using current carrying and voltage sensing electrodes attached on the boundary of the fabric patch. Design/methodology/approach – Recently, promising results are being achieved in conductivity imaging for these sensors. However, the fabric structure presents capacitive behaviour that could also be exploited for pressure mapping imaging. Complex impedance reconstructions with multiple frequencies are implemented to observe both conductivity and permittivity changes due to the pressure applied to the fabric sensor. Findings – Experimental studies on detecting changes of complex impedance on fabric-based sensor are performed. First, electrical impedance spectroscopy on a fabric-based sensor is performed. Secondly, the complex impedance tomography is carried out on fabric and compared with traditional EIT tank phantoms. Quantitative image quality measures are used to evaluate the performance of a fabric-based sensor at various frequencies and against the tank phantom. Originality/value – The paper demonstrates for the first time the useful information on pressure mapping imaging from the permittivity component of fabric EIT. Multiple frequency EIT reconstruction reveals spectral behaviour of the fabric-based EIT, which opens up new opportunities in exploration of these sensors.

Patch-based sparse reconstruction for electrical impedance tomography

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 257-269 ◽  
Author(s):  
Qi Wang ◽  
Pengcheng Zhang ◽  
Jianming Wang ◽  
Qingliang Chen ◽  
Zhijie Lian ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Sparse Representation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Inverse Operator ◽  
Reconstruction Algorithm ◽  
Impedance Tomography ◽  
Content Type ◽  
Ill Posed ◽  
High Level

Purpose Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise. Design/methodology/approach This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity. Findings Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages. Originality/value EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

Low-power electrical impedance tomography spectroscopy

2019 ◽  
Vol 38 (5) ◽  
pp. 1480-1492 ◽  
Author(s):  
Juliana Padilha Leitzke ◽  
Hubert Zangl
Keyword(s):  
Computational Complexity ◽  
Low Power ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Mean Squared Error ◽  
Order Approximation ◽  
Electrode Design ◽  
Electrode Geometry ◽  
Impedance Tomography ◽  
Content Type

Purpose This paper aims to present an approach based on electrical impedance tomography spectroscopy (EITS) for the determination of water and ice fraction in low-power applications such as autarkic wireless sensors, which require a low computational complexity reconstruction approach and a low number of electrodes. This paper also investigates how the electrode design can affect the reconstruction results in tomography. Design/methodology/approach EITS is performed by using a non-iterative method called optimal first order approximation. In addition to that, a planar electrode geometry is used instead of the traditional circular electrode geometry. Such a structure allows the system to identify materials placed on the region above the sensor, which do not need to be confined in a pipe. For the optimization, the mean squared error (MSE) between the reference images and the obtained reconstructed images was calculated. Findings The authors demonstrate that even with a low number of four electrodes and a low complexity reconstruction algorithm, a reasonable reconstruction of water and ice fractions is possible. Furthermore, it is shown that an optimal distribution of the sensor electrodes can help to reduce the MSE without any costs in terms of computational complexity or power consumption. Originality/value This paper shows through simulations that the reconstruction of ice and water mixtures is possible and that the electrode design is a topic of great importance, as they can significantly affect the reconstruction results.

An inspection continuum robot with tactile sensor based on electrical impedance tomography for exploration and navigation in unknown environment

2019 ◽  
Vol 47 (1) ◽  
pp. 121-130 ◽  
Author(s):  
Yaming Wang ◽  
Feng Ju ◽  
Yahui Yun ◽  
Jiafeng Yao ◽  
Yaoyao Wang ◽  
...  
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Aircraft Engine ◽  
Tactile Sensor ◽  
Average Error ◽  
Impedance Tomography ◽  
Content Type ◽  
Inspection Robot ◽  
Continuum Robot ◽  
The Continuum

Purpose This paper aims to introduce an aircraft engine inspection robot (AEIR) which can go in the internal of the aircraft engine without collision and detect damage for engine blades. Design/methodology/approach To obtain the position and pose information of the blades inside the engine, a novel tactile sensor based on electrical impedance tomography (EIT) is developed, which could provide location and direction information when it contacts with an unknown object. In addition, to navigate the continuum robot, a control method is proposed to control the continuum robot, which can control the continuum robot to move along the pre-planned path and reduce the deviation from the planned path. Findings Experiment results show that the average error of contact location measurement of the tactile sensor is 0.8 mm. The average error relative to the size (diameter of 18 mm) of the sensor is 4.4%. The continuum robot can successfully reach the target position through a gap of 30 mm and realize the spatial positioning of blades. The validity of the AEIR for engine internal blade detection is verified. Originality/value The aero-engine inspection robot developed in this paper can replace human to detect engine blades and complete different detection tasks with different kinds of sensors.

Solving the electrical impedance tomography inverse problem for logarithmic conductivity

2018 ◽  
Vol 37 (2) ◽  
pp. 681-690 ◽  
Author(s):  
Sergio P. Pellegrini ◽  
Flavio C. Trigo ◽  
Raul G. Lima
Keyword(s):  
Inverse Problem ◽  
Electrical Impedance Tomography ◽  
Design Methodology ◽  
Electrical Impedance ◽  
Gradient Methods ◽  
Solution Space ◽  
Initial Guess ◽  
Impedance Tomography ◽  
Content Type ◽  
Estimation Problems

PurposeIn the context of electrical impedance tomography (EIT), this paper aims to evaluate limitations of estimating conductivity or resistivity, as well as the improvements achieved with the use of an alternate description of the solution space, the logarithmic conductivity. Design/methodology/approachA quantitative analysis is performed, solving the inverse EIT problem by using the Gauss–Newton and non-linear conjugate gradient methods for a numerical phantom of 15 elements. A property of symmetry is studied for the direct EIT problem for a phantom of 385,601 elements. FindingsSolving the inverse EIT problem in logarithmic conductivity is more robust to the initial guess, as solutions are kept within physical bounds (conductivity positiveness). Also, convergence is faster and less dependent on the final values of the estimates. Research limitations/implicationsLogarithmic conductivity provides an advantageous description of the solution space for the EIT inverse problem. Similar estimation problems might be subject to analogous conclusions. Originality/valueThis study provides a novel analysis, quantitatively comparing the effect of different variables to solve the inverse EIT problem.

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