This paper presents EIT-based fabric sensors that aim to provide a pressure mapping using the current carrying and voltage sensing electrodes attached to the boundary of the fabric patch. Pressure-induced shape change over the sensor area makes a change in the conductivity distribution which can be conveyed to the change of boundary current-voltage data. This boundary data is obtained through electrode measurements in EIT system. The corresponding inverse problem is to reconstruct the pressure and deformation map from the relationship between the applied current and the measured voltage on the fabric boundary. Taking advantage of EIT in providing dynamical images of conductivity changes due to pressure induced shape change, the pressure map can be estimated. In this paper, the EIT-based fabric sensor was presented for circular and rectangular sensor geometry. A stretch sensitive fabric was used in circular sensor with 16 electrodes and a pressure sensitive fabric was used in a rectangular sensor with 32 electrodes. A preliminary human test was carried out with the rectangular sensor for foot pressure mapping showing promising results.

PurposeElectrical impedance measurement and imaging are techniques that are widely used in a range of applications. Electro‐conductive knitted structure is a major new development in wearable computing. The purpose of this paper is to carry out a preliminary investigation of applying electrical impedance analysis to predict the behavior of electro‐conductive knitted structure. This can potentially pave the way for a low‐cost solution for pressure mapping imaging.Design/methodology/approachElectrical impedance tomography (EIT) has been used as a mapping technique for deformation imaging in conductive knitted fabric. EIT is an imaging system used to generate a map of electrical conductivity. Pressure and deformation mapping scanner is being developed based on electrical conductivity imaging of the conductive area generated in a fabric. The results are presented using these new sensors with various deformations.FindingsExperimental results show the feasibility of qualitative deformation imaging. In particular, it is promising that multiple deformations can be mapped using the proposed technique. The paper also demonstrates preliminary results regarding quantitative pressure and deformation mapping using EIT technique.Research limitations/implicationsThe results presented in the paper are laboratory‐based experiments for proof of principle and will be evaluated in specific application areas in future.Originality/valueThe paper shows, for the first time, detection of multiple pressure points as well as quantifying the pressure map using the new imaging sensor. The sensor proposed here can be used for robotic touch sensing application, as well as some biomechanical observations.

Cone-beam CT (CBCT) is an imaging technique used in conjunction with radiation therapy. For example CBCT is used to verify the position of lung cancer tumours just prior to radiation treatment. The accuracy of the radiation treatment of thoracic and upper abdominal structures is heavily affected by respiratory movement. Such movement typically blurs the CBCT reconstruction and ideally should be removed. Hence motion-compensated CBCT has recently been researched for correcting image artefacts due to breathing motion. This paper presents a new dual-modality approach where CBCT is aided by using electrical impedance tomography (EIT) for motion compensation. EIT can generate images of contrasts in electrical properties. The main advantage of using EIT is its high temporal resolution. In this paper motion information is extracted from EIT images and incorporated directly in the CBCT reconstruction. In this study synthetic moving data are generated using simulated and experimental phantoms. The paper demonstrates that image blur, created as a result of motion, can be reduced through motion compensation with EIT.

This study aimed to develop a physical geometric phantom for the deformable image registration (DIR) credentialing of radiotherapy centers for a clinical trial and tested the feasibility of the proposed phantom at multiple domestic and international institutions. Methods and materials: The phantom reproduced tumor shrinkage, rectum shape change, and body shrinkage using several physical phantoms with custom inserts. We tested the feasibility of the proposed phantom using 5 DIR patterns at 17 domestic and 2 international institutions (21 datasets). Eight institutions used the MIM software (MIM Software Inc, Cleveland, OH); seven used Velocity (Varian Medical Systems, Palo Alto, CA), and six used RayStation (RaySearch Laboratories, Stockholm, Sweden). The DIR accuracy was evaluated using the Dice similarity coefficient (DSC) and Hausdorff distance (HD).Results: The mean and one standard deviation (SD) values (range) of DSC were 0.909 AE 0.088 (0.434-0.984) and 0.909 AE 0.048 (0.726-0.972) for tumor and rectum proxies, respectively. The mean and one SD values (range) of the HD value were 5. ) (mm) for the tumor and rectum proxies, respectively. In three patterns evaluating the DIR accuracy within the entire phantom, 61.9% of the data had more than a DSC of 0.8 in both tumor and rectum proxies. In two patterns evaluating the DIR accuracy by focusing on tumor and rectum proxies, all data had more than a DSC of 0.8 in both tumor and rectum proxies. Conclusions:The wide range of DIR performance highlights the importance of optimizing the DIR process. Thus, the proposed method has considerable potential as an evaluation tool for DIR credentialing and quality assurance.

-Electrical and Electromagnetic imaging are widely used in many application areas. Most works are done in 2D imaging mode. Recently, volumetric (3D) imaging of passive electromagnetic properties using low frequency electrical and electromagnetic imaging is being developed. This paper presents the latest results of 3D electrical and electromagnetic tomography imaging. The results of experimental data will be presented based on most commonly used finite element modelling of the forward model and the standard Tikhonov regularized inverse solution. Challenges and opportunities will be discussed in presentation.