Key points are not available for this paper at this time.
While EIT images can produce clinically useful qualitative information, the extraction of quantitative data is essential in clinical monitoring. In the case of imaging of the thorax the parameters available relate to cardiac activity and pulmonary perfusion. Imaging the relatively small changes in the resistivity of the lungs due to pulmonary perfusion in the presence of noise and the larger ventilation component is difficult. Suggested solutions involve multiple time averaging of cardiac gated data or reconstructed images. The required number of data frames for this type of processing is large (at least 100 cardiac cycles). Because the ventilation and perfusion components of the resistivity signals are well separated in the frequency domain, they can be differentiated by filtering. We report the results of this analysis which requires a data collection period of typically 15 s.
Zadehkoochak et al. (Tue,) studied this question.