Torso shape detection to improve lung monitoring

Newborns with lung immaturity often require continuous monitoring and treatment of their lung ventilation in intensive care units, especially if born preterm. Recent studies indicate that Electrical Impedance Tomography (EIT) is feasible in newborn
 infants and children, and can quantitatively identify changes in regional lung aeration and ventilation following alterations to respiratory conditions. Information on the patient-specic shape of the torso and its role in minimizing the artefacts in the
 reconstructed images can improve the accuracy of the clinical parameters obtained from EIT. Currently, only idealized models or those segmented from CT scans are usually adopted. This study presents and compares two methodologies that can
 detect the patient-specic torso shape by means of wearable devices based on: (1) previously reported bend sensor technology and (2) a novel approach based on the use of accelerometers. The reconstruction of different phantoms, taking into account
 anatomical asymmetries and different sizes, are produced for comparison. As a result, the accelerometers are more versatile than bend sensors, which cannot be used on bigger cross-sections. The computational study estimates the optimal number of
 accelerometers required in order to generate an image reconstruction comparable to the use of a CT scan as the forward model. Furthermore, since the patient position is crucial to monitoring lung ventilation, the orientation of the phantoms is automatically
 detected by the accelerometer-based method. [Abstract copyright: © 2018 Institute of Physics and Engineering in Medicine.