高分解能ＥＩＳＴとアルブミン輸送モデルによる早期リンパ浮腫診断法と予測法の確立

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c-EIST system and the prediction model of Lymphedema through the proposal of Albumin Transport Model (ATM) are very important and highly needed. However, the research of c-EIST development for Lymphedema detection was quite tough because of we lack real data from patient. Thus, it is needed more data from the clinical trial. The knowledge on our team about the development this system and prediction model, obviously can be applied on wide research area. On this study, variations of albumin concentration on fluid plasma and saline-agar phantom as a mimic of SAT were conducted because it is not established yet. It shows that the increasing the albumin concentration causes the decreasing of the resistance plasma serum in the case of globulin protein is considered as confounding factor (Baidillah, et a., 2018a). In the case of sensor attached to the object surface, the contact impedance arise and affect to the unknown impedance measurement. This study has proposed a new method to eliminate the unknown contact impedance by employing the cole-cole impedance model (Baidillah, et al., 2019a). It is obvious to conclude that the changing of impedance measurement due to increasing of albumin content level is smaller as compared with one due to the time-varying random noise. Elimination the effect of time-varying random noise is also proposed to improve the performance (Baidillah, et al., 2019b). Moreover, we proposed a method to improve the image reconstruction algorithm method in order to evaluate the changing of SAT on the long-term monitoring (Ryoma, et al., 2020).