Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications

Khan, Talha Ahmed; Ling, Sai Ho

doi:10.3390/a12050088

Cited by 101 publications

(65 citation statements)

References 63 publications

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“…In recent years, many researchers have worked on different artificial intelligence and evolutionary algorithms to solve the EIT inverse problem . These nonlinear methods will provide good results if the assumptions of reconstruction problems are simplified.…”

Section: Eit For Artificial Sensitive Skinsmentioning

confidence: 99%

Artificial Sensitive Skin for Robotics Based on Electrical Impedance Tomography

Wang

et al. 2020

Advanced Intelligent Systems

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Electrical impedance tomography (EIT) is a noninvasive measurement technique that estimates the internal resistivity distribution based on the boundary voltage–current data measured from the surface of the conductor. If a thin stretchable soft material with a certain piezoresistive property is used as the electrical conductor, EIT has the ability to reconstruct the position where the resistivity changes due to the inside pressure contact, so that a large‐scale artificial sensitive skin is provided for robotics. First, the different conduction principles and material types of artificial sensitive skins are discussed, which is next followed by the different driving modes and image reconstruction techniques. Then, details on how EIT is used for robotic skin applications are described. Finally, the development trends and future potentials of EIT‐based robotic skins are expounded.

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Section: Eit For Artificial Sensitive Skinsmentioning

confidence: 99%

Artificial Sensitive Skin for Robotics Based on Electrical Impedance Tomography

Wang

et al. 2020

Advanced Intelligent Systems

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“…Starting from linear methods (e.g., Linear Back-Projection) through nonlinear and iterative methods (e.g., Gauss–Newton) [2,3,5], the approach to the inverse problem has evolved into a dozen modern algorithms that utilize so-called artificial intelligence methods. For instance, in [22], the authors reviewed almost 70 papers describing novel methods for image reconstruction. Some of the modern, advanced algorithms, e.g., Sparse Bayesian Learning [23], are thought to offer a better resolution for imaging in comparison to classical methods.…”

Section: Methodsmentioning

confidence: 99%

Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography

Porzuczek

2019

Sensors

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This paper presents a method for the online determination of the spatial distribution of the moisture content in granular material. It might be essential for the monitoring and optimal control of, for example, drying processes. The proposed method utilizes Electrical Impedance Tomography (EIT). As an exemplary material for experimental research, the black chokeberry (Aronia melanocarpa) was used. The relationship between the electrical impedance of the chokeberry and its moisture content was determined for a wide range of frequencies (20 Hz–200 kHz). The EIT research consisted of both simulation and experimental investigation. Experimental studies of the spatial distribution of the moisture content were performed in a cylindrical vessel equipped with 8 electrodes circumferentially arranged. The voltage signal from the electrodes was acquired simultaneously using the data acquisition module. Due to the high impedance of the chokeberries, exceeding 109 Ω for the dried matter, extraordinary instrumentation was necessary to be applied. On the other hand, raw chokeberry was characterized by a several orders of magnitude lower impedance (103–104 Ω), especially for high frequencies. The wide range of the observed impedance was able to be measured owing to its use of the voltage stimulation instead of the current stimulation (which is most common for EIT). The image reconstruction problem was solved using an iterative Gauss–Newton algorithm and the EIDORS (Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software) package. The obtained results showed a satisfactory ability to localize an insufficiently dried part of the material. Prospective ways to improve the imaging quality are also discussed.

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“…These modules must be synchronized with the signal generator so that the magnitude and phase of the signal at the time of being measured is correct. Finally, the conductivity is processed through an EIT image reconstruction algorithm [5], [9], [10].…”

Section: Literature Review 21 Eit Systemsmentioning

confidence: 99%

Electrical Impedance Tomography: Hardware Fundamentals And Medical Applications

Revelo

2020

ing. Solidar

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Introduction: The following article shows a systematic review of publications on hardware topologies used to capture and process electrical signals used in Electrical Impedance Tomography (EIT) in medical applications, as well topicality of the EIT in the field of biomedicine. This work is the product of the research project “Electrical impedance tomography based on mixed signal devices”, which took place at the University of Cauca during the period 2017-2019. Objective: This review describes the operation, topicality and clinical use of Electrical Impedance Tomography systems. Methodology: A systematic review was carried out in the IEEE-Xplore, ScienceDirect and Scopus databases. After the classification, 106 relevant articles were obtained on scientific studies of EIT systems; applications dedicated to the analysis of medical images. Conclusions: Impedance-based methods have a variety of medical applications as they allow for the reconstruction of a body region, by estimating the conductivity distribution inside the human body; this is without exposing the patient to the damaging effects of radiation and contrast elements. Impedance-based methods are therefore a very useful and versatile tool in the treatment of diseases such as: monitoring blood pressure, detection of atherosclerosis, localization of intracranial hemorrhages, determining bone density, among others. Originality: It describes the necessary components to design an EIT system, as well as the design characteristics depending on the pathology to be visualized. Restrictions: The review focuses on aspects of the performance of an EIT system, depending on the pathology analyzed. Considering the hardware advances, it is possible to increase the acquisition speed (temporal resolution), thus improving the spatial resolution and the quality of the reconstructed image. Introduction: The following article shows a systematic review of publications on hardware topologies used to capture and process electrical signals used in Electrical Impedance Tomography (EIT) in medical applications, as well topicality of the EIT in the field of biomedicine. This work is the product of the research project “Electrical impedance tomography based on mixed signal devices”, which took place at the University of Cauca during the period 2017-2019. Objective: This review describes the operation, topicality and clinical use of Electrical Impedance Tomography systems. Methodology: A systematic review was carried out in the IEEE-Xplore, ScienceDirect and Scopus databases. After the classification, 106 relevant articles were obtained on scientific studies of EIT systems; applications dedicated to the analysis of medical images. Conclusions: Impedance-based methods have a variety of medical applications as they allow for the reconstruction of a body region, by estimating the conductivity distribution inside the human body; this is without exposing the patient to the damaging effects of radiation and contrast elements. Impedance-based methods are therefore a very useful and versatile tool in the treatment of diseases such as: monitoring blood pressure, detection of atherosclerosis, localization of intracranial hemorrhages, determining bone density, among others. Originality: It describes the necessary components to design an EIT system, as well as the design characteristics depending on the pathology to be visualized. Restrictions: The review focuses on aspects of the performance of an EIT system, depending on the pathology analyzed. Considering the hardware advances, it is possible to increase the acquisition speed (temporal resolution), thus improving the spatial resolution and the quality of the reconstructed image.

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Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications

Cited by 101 publications

References 63 publications

Artificial Sensitive Skin for Robotics Based on Electrical Impedance Tomography

Artificial Sensitive Skin for Robotics Based on Electrical Impedance Tomography

Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography

Electrical Impedance Tomography: Hardware Fundamentals And Medical Applications

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