I. Introduction
Dynamic monitoring of lung respiration is of crucial importance in the diagnosis, assessment, treatment guidance, and posttreatment recovery tracking of respiratory diseases which have always been a central point in medical research. It is closely associated with monitoring the respiratory status of patients in the intensive care unit and tracking lung ventilation in patients with chronic obstructive pulmonary disease and acute respiratory distress syndrome. Computed tomography (CT) is a commonly used imaging tool for lung imaging. However, this technology involves radiation and is relatively expensive, limiting its application to radiology departments. It has certain limitations in its application in the medical field. Kim et al. [1] first proposed the concept of using electrical impedance tomography (EIT) to achieve imaging of the impedance distribution in the cross section of the thoracic cavity. The application of EIT in medical imaging involves placing sensor electrodes around the area to be detected, applying a safe electric current through the electrodes to the human body, and then detecting the corresponding voltage values. These voltage values reflect the impedance of internal distribution in the human body, and using these voltage values, an image of the distribution of electrical conductivity within the internal structures of the human body is reconstructed, enabling the detection of internal structures [2], [3]. As lung tissue has a higher impedance compared to other tissues, and there is a significant difference in impedance between the inhalation and exhalation phases [4]. In addition to the noninvasive, radiation-free, and cost-effective advantages of EIT [5], EIT technology demonstrates great utility in respiratory monitoring. In the early 21st century, the practical application of EIT technology for monitoring pulmonary ventilation was realized in medical environments [6]. Today, EIT technology is widely used for dynamic respiratory monitoring in intensive care units, enabling clinical decisions along with static CT images [7]. EIT is also applied in brain imaging [8] and holds potential for cancer detection [9], [10]. However, some limitations hinder the further application of EIT in the medical field. In the medical applications of EIT, the direct/galvanic contact between the electrodes and the skin causes the contact impedance at the interface [11]. Contact impedance is significantly affected by the characteristics of the skin surface, such as skin roughness. In long-term monitoring scenarios, it is challenging to overcome the effects of the unstable contact impedance, which can cause measurement errors. To achieve close contact to reduce the effects of contact impedance, conductive gel is often applied to the skin, or the electrode belt is tightly fastened around the patient’s chest, causing pressure. This leads to discomfort and inconvenience for the user in long-term monitoring scenarios, thus limiting the application of EIT. Ouwerkerk et al. [12] introduced a capacitive sensor (also called contactless sensor) with an insulating layer applied to the electrode surface, which can be fit to EMG/ECG equipment. The sensor is not in galvanic contact with the skin; thus, to avoid the adverse effects of direct electrode-skin contact [12].