Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/27255
ชื่อเรื่อง: Lung Volume Estimation based on Bioimpedance Measurement and Neural Network
ผู้แต่ง: Khumwa N.
Thongkhun K.
Maneerat S.
Ouypornkochagorn T.
Keywords: Electrical Impedance Tomography (EIT)
lung volume
neural network
วันที่เผยแพร่: 2022
สำนักพิมพ์: Institute of Electrical and Electronics Engineers Inc.
บทคัดย่อ: Lung volume is an indicator used for evaluating how healthy of lungs are. Apart from using expensive equipment, lung volume can be determined by bioimpedance obtained by measuring at several regions around the chest. The bioimpedance values are usually used by the Electrical Impedance Tomography (EIT) technique, which transforms the several bioimpedance values into an image of conductivity distribution. EIT is inexpensive and can be used to monitor lungs in real-time. However, EIT is computation expensive and cannot provide the lung volume directly. In this study, the neural network technique was used to estimate the left- and the right-lung volume by using the bioimpedance values as used in EIT. Two network architectures were investigated by simulation. The result shows that neural networks can efficiently estimate lung volumes with the error of less than 0.78 ml and with a correlation of higher than 0.99. Even adding noise to the degree of 40 dB signal-to-noise ratio, the performance was still satisfactory. Two-layer network architecture was also sufficient for this lung application. © 2022 IEEE.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128186732&doi=10.1109%2fiEECON53204.2022.9741619&partnerID=40&md5=fa57d7f53ab9a593ad95593c895db214
https://ir.swu.ac.th/jspui/handle/123456789/27255
Appears in Collections:Scopus 2022

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