Wearable sensors for patient-specific boundary shape estimation to improve the forward model for electrical impedance tomography (EIT) of neonatal lung function

摘要

Electrical impedance tomography (EIT) could be significantly advantageous to continuous monitoring of lung development in newborn and, in particular, preterm infants as it is non-invasive and safe to use within the intensive care unit. It has been demonstrated that accurate boundary form of the forward model is important to minimize artefacts in reconstructed electrical impedance images. This paper presents the outcomes of initial investigations for acquiring patient-specific thorax boundary information using a network of flexible sensors that imposes no restrictions on the patient's normal breathing and movements. The investigations include: (1) description of the basis of the reconstruction algorithms, (2) tests to determine a minimum number of bend sensors, (3) validation of two approaches to reconstruction and (4) an example of a commercially available bend sensor and its performance. Simulation results using ideal sensors show that, in the worst case, a total shape error of less than 6% with respect to its total perimeter can be achieved.