Simulation research of respiratory monitoring with magnetic detection electrical impedance tomography_Journal of Biomedical Engineering

Authors：

WANG Huiquan , YIN Jianli , LI Guangxu , FENG Yanbo , WANG Jinhai ,  CHEN Ruijuan

Tianjin Key Laboratory of Photoelectric Detection Technology and System, Tianjin Polytechnic University, Tianjin 300387, P.R.China;

Corresponding author：

CHEN Ruijuan, Email: chenruijuan@tjpu.edu.cn

Keywords：

magnetic detection electrical impedance tomography; forward problem; finite element method; magnetic induction intensity

DOI：

10.7507/1001-5515.201604083

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

In order to explore the feasibility of applying magnetic detection electrical impedance tomography (MDEIT) on respiratory monitoring, aiming at the forward problem of magnetic detection electrical impedance tomography, we calculated the electric potential and current density distribution inside the imaging object by using the finite element method. We then got magnetic induction intensity outside the object at the end of exhaling and inhaling according to Biot-Savart's law. The results showed that the magnetic induction intensity at the end of inhaling was 8.875%, less than that at the end of exhaling. By the simulation results, we could understand the difference of magnetic induction intensity value surrounding the lung at the end of exhaling and inhaling due to the change of lung volume and electrical conductivity distribution better. Our research laid the foundation for the late image reconstruction and clinical disease detection.

Citation： WANGHuiquan, YINJianli, LIGuangxu, FENGYanbo, WANGJinhai, CHENRuijuan. Simulation research of respiratory monitoring with magnetic detection electrical impedance tomography. Journal of Biomedical Engineering, 2017, 34(1): 27-33. doi: 10.7507/1001-5515.201604083 Copy

1.	陈云芝, 徐桂芝, 周茜, 等. 基于脉冲时间依赖可塑性的自适应神经网络抗扰能力研究. 生物医学工程学杂志, 2015, 32(1)): 25-31.
2.	朱险峰, 苏益锦, 余辉. 物理人建模及应用的研究现状与展望. 生物医学工程学杂志, 2014, 31(6): 1384-1388.
3.	周永军, 张辉, 牛中奇. 高频低能电磁环境头颅内电场应力分析. 生物医学工程学杂志, 2015, 32(2): 295-299.
4.	Henderson R P, Webster T G. An impedance camera for spatially specific measurements of the thorax. IEEE Trans Biomed Eng, 1978, 25: 250-254.
5.	Suchomel J, Sobota V. A model of end-expiratory lung impedance-pendency on total extracellular body water//XIV Conference on Electrical Impendance Tomography, 2013: 1-4.
6.	Ferrario D, Grychtol B, Adler A, et al. Toward morphological thoracic EIT: major signal sources correspond to respective organ locations in CT. IEEE Trans Biomed Eng, 2012, 59(11): 3000-3008.
7.	Zhao Z, Fischer R, Frerichs I, et al. Regional ventilation in cystic fibrosis measure by electrical impedance tomography. J.Cyst.Fibro, 2012, 11(5): 412-418.
8.	Pavl D, Anatolij T, Josef P, et al. Assessment of regional ventilation with the electrical impedance tomography in a patient after asphyxia cardiac arrest. Resuscitation, 2014, 85(8): 115-117.
9.	Karsten J, Bohlmann M, Sedemund-Adib B, et al. Electrical impedance tomography May optimize ventilation in a postpartum Woman with respiratory failure. Int J Obstet Anesth, 2013, 22(1): 67-71.
10.	Brunner P, Mayer M, Hinghofer-Szalkay H A, et al. Imaging of local lung ventilation under different gravitational conditions with electrical impedance tomography. Acta Astronaut, 2007, 60(4/7): 281-284.
11.	陈瑞娟. 三维开放式磁共振电阻抗成像的研究. 天津: 天津大学, 2012.
12.	李蔚琛, 史学涛, 夏军营, 等. 用于生物电阻抗成像系统的镜像反馈电流源的研究. 医疗卫生装备, 2015, 36(2): 1-5.
13.	谭春晓. 基于信赖域方法的电阻抗断层成像研究. 天津: 河北工业大学, 2013.
14.	Ahlfors S, IIMONIEMIR. Magnetic imaging of conductivity//14th Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, France: 1992: 1717-1718.
15.	Tozer J C, Ireland R H, Barber D C, et al. Magnetic impedance tomography. Ann N Y Acad Sci, 1999, 873(1): 353-359.
16.	Ireland R H, Tozer J C, Barker A T, et al. Towards magnetic detection electrical impedance tomography: data acquisition and image Reconstruction of current density in phantoms and in vivo. Physiol Meas, 2004, 25(3): 775-796.
17.	Barber D, Brown B. Applied potential tomography. J Br Interplanet Soc, 1989, 42(7): 391-393.
18.	Dehghanih. Barber D C, Basarrab H I. Incorparating a prioriannatomical information into image Reconstruction in electrical impedance tomography. Physiol Meas, 1999, 20: 87-102.
19.	National Cancer Institute. 肺癌图像数据库联盟, (2016-04-23)[2016-04-28].
20.	Faes T, van der Meij H, de Munck J, et al. The electric resistivity of human tissues (100 Hz-10 MHz): a meta-analysis of review studies. Physiol Meas, 1999, 20(4): R1-10.

1. 陈云芝, 徐桂芝, 周茜, 等. 基于脉冲时间依赖可塑性的自适应神经网络抗扰能力研究. 生物医学工程学杂志, 2015, 32(1)): 25-31.
2. 朱险峰, 苏益锦, 余辉. 物理人建模及应用的研究现状与展望. 生物医学工程学杂志, 2014, 31(6): 1384-1388.
3. 周永军, 张辉, 牛中奇. 高频低能电磁环境头颅内电场应力分析. 生物医学工程学杂志, 2015, 32(2): 295-299.
4. Henderson R P, Webster T G. An impedance camera for spatially specific measurements of the thorax. IEEE Trans Biomed Eng, 1978, 25: 250-254.
5. Suchomel J, Sobota V. A model of end-expiratory lung impedance-pendency on total extracellular body water//XIV Conference on Electrical Impendance Tomography, 2013: 1-4.
6. Ferrario D, Grychtol B, Adler A, et al. Toward morphological thoracic EIT: major signal sources correspond to respective organ locations in CT. IEEE Trans Biomed Eng, 2012, 59(11): 3000-3008.
7. Zhao Z, Fischer R, Frerichs I, et al. Regional ventilation in cystic fibrosis measure by electrical impedance tomography. J.Cyst.Fibro, 2012, 11(5): 412-418.
8. Pavl D, Anatolij T, Josef P, et al. Assessment of regional ventilation with the electrical impedance tomography in a patient after asphyxia cardiac arrest. Resuscitation, 2014, 85(8): 115-117.
9. Karsten J, Bohlmann M, Sedemund-Adib B, et al. Electrical impedance tomography May optimize ventilation in a postpartum Woman with respiratory failure. Int J Obstet Anesth, 2013, 22(1): 67-71.
10. Brunner P, Mayer M, Hinghofer-Szalkay H A, et al. Imaging of local lung ventilation under different gravitational conditions with electrical impedance tomography. Acta Astronaut, 2007, 60(4/7): 281-284.
11. 陈瑞娟. 三维开放式磁共振电阻抗成像的研究. 天津: 天津大学, 2012.
12. 李蔚琛, 史学涛, 夏军营, 等. 用于生物电阻抗成像系统的镜像反馈电流源的研究. 医疗卫生装备, 2015, 36(2): 1-5.
13. 谭春晓. 基于信赖域方法的电阻抗断层成像研究. 天津: 河北工业大学, 2013.
14. Ahlfors S, IIMONIEMIR. Magnetic imaging of conductivity//14th Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, France: 1992: 1717-1718.
15. Tozer J C, Ireland R H, Barber D C, et al. Magnetic impedance tomography. Ann N Y Acad Sci, 1999, 873(1): 353-359.
16. Ireland R H, Tozer J C, Barker A T, et al. Towards magnetic detection electrical impedance tomography: data acquisition and image Reconstruction of current density in phantoms and in vivo. Physiol Meas, 2004, 25(3): 775-796.
17. Barber D, Brown B. Applied potential tomography. J Br Interplanet Soc, 1989, 42(7): 391-393.
18. Dehghanih. Barber D C, Basarrab H I. Incorparating a prioriannatomical information into image Reconstruction in electrical impedance tomography. Physiol Meas, 1999, 20: 87-102.
19. National Cancer Institute. 肺癌图像数据库联盟, (2016-04-23)[2016-04-28].
20. Faes T, van der Meij H, de Munck J, et al. The electric resistivity of human tissues (100 Hz-10 MHz): a meta-analysis of review studies. Physiol Meas, 1999, 20(4): R1-10.

Journal of Biomedical Engineering

Simulation research of respiratory monitoring with magnetic detection electrical impedance tomography

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content