# Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications
## 5 EIT Clinical-Based Applications
### Lung Imaging  
[PERSON] et al. [92] have demonstrated the usage of EIT imaging methods in the calculation of the resistivity of the Lungs in examining and detection of edema and apnea. In EIT, the current is injected into the patient by applying several electrodes and calculating border-line voltages to reform a cross-sectional image of internal resistivity distribution. They have presented a fast, simple method for observing and detecting apnea and edema. They demonstrated their method by human experiments and simulations. They have concluded that the EIT imaging method will be more consistent as compared to the current impedance apnea monitoring technique, as they were monitoring the variations in the resistivity of the internal lung. They have suggested that more studies need to be done to validate this technique but that it performs better in the existence of motion artifact as compared to the traditional two-electrode impedance apnea monitoring technique. By taking a series of differential images, [PERSON] al el. have proposed a system to observe human lung ventilation. The result of the experiments highlighted that the Multi Frequency (MF-EIT) system is a practical, reliable, appropriate and consistent technique of imaging human lung ventilation. It is possible to get an accurate reconstructed image in EIT by inserting previous data with reference to size constitution of the object. They used a commercial software tool COMSOL by including the prior information of human thorax to produce a physical model [93]. Alongside the ventilation of the lungs, the authors have presented a developed model too based on the experimental data. By including prior information, the imagery results of the ventilation of the lungs showed that EIT is a reliable procedure for medical analyses and monitoring and has the capabilities to use in the near future [93]. In [94] [PERSON] et al. have proposed a new three-dimensional swift real-time EIT system for imaging and detecting human lung that depends on the node back-projection algorithm with 64 electrodes. The findings indicated that the system contained the potential of reflecting impedance variations of the thorax reconstruction of the images amid a persons' breathing. [PERSON] et al. have [95] proposed a better technique for EIT images for a lung area estimation (LAE). For patients with serious pulmonary diseases, LAE is an appropriate technique. They concluded that in EIT for the lung area estimation the LAE technique provides more reliable results as compared to the other different current techniques. [PERSON] et al. produced an EIT-based wearable lung health-monitoring device. The system has an EIT integrated circuit (IC) that gives programmable current stimulation that is optimally controlled by the results of contact impedance monitoring. The data obtained is forwarded to the handheld mobile device and the lung EIT images of up to 20 frames/s real-time are reconstructed and displayed. The calculated lung air volume- ratio can be used as a pointer of the lung-health, and different other parameters that can be extracted to observe lung status from the lung EIT image obtained [96]. A similar device with less power consumption for lung ventilation monitoring is proposed [97]. The SoC with 32 electrodes on a belt-type EIT system gives dynamic images on the mobile device for lung ventilation. The device can reconstruct the imaginary and the real parts of the images with 97.3% of precision [97].