Application and Analysis of EIT Image Sequences for Real-time Monitoring of Local Aeration in a Respiratory-like Phantom Device

Document Type : Research Article

Authors

Department of Electrical Engineering and Information Technology, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran

Abstract

The present study demonstrates the applicability of the Electrical Impedance Tomography (EIT) technique for real-time monitoring of inspiration and expiration behavior in a respiratory phantom device. The phantom device, which serves as a mechano-electrical simulator of the human respiratory system, is coupled to a real-time monitoring instrument operating based on the EIT technique. This study reveals that the whole system could act as a helpful apparatus for researchers and physicians in improving their ventilation maneuvers for patients. The phantom specifically helps in designing and examining the results of a larger number of experiments, setting up more qualified test environments, and finally more optimal tuning of ventilator devices. The device's physical appearance and structure resemble the human’s chest cage, making it suitable to be used as a model of the human respiratory system. Experimental results support the applicability of the phantom and EIT system for real-time monitoring of local aerations in different experimental conditions. Additionally, several recorded and analyzed data leads us to better processing and understanding of the EIT technique and its capabilities in respiration studies. The current work could be considered as a proof of concept and a step towards automatically and intelligently suggesting ventilator settings for optimal adoption of treatment strategies and patient management in hospitals in the future.

Keywords

Main Subjects

References

[1] C.J. Roth, Multi-dimensional Coupled Computational Modeling in Respiratory Biomechanics, TECHNISCHE UNIVERSITAT MUNCHEN, 2017.
[2] C.K.G. James M. Harte, Johanna Acosta, Edward F. Nash, Ercihan Kiraci, Mark A. Williams, Theodoros N. Arvanitis, Babu Naidu, Chest wall motion analysis in healthy volunteers and adults with cystic fibrosis using a novel Kinect‑based motion tracking system, Med Biol Eng Comput, 54 (2016).
[3] M.B.P.A. Inéz Frerichs, Anton H van Kaam, David G Tingay,Zhanqi Zhao, Bartłomiej Grychtol, Marc Bodenstein, Hervé Gagnon,Stephan H Böhm, Eckhard Teschner, Ola Stenqvist, Tommaso Mauri,Vinicius Torsani, Luigi Camporota, Andreas Schibler, Gerhard, Chest electrical impedance tomography examination, data analysis, terminology, clinical use and recommendations: consensus statement of the Translational EIT development study group, Thorax, 72 (2017) 83-93.
[4] Y.K. CH Lee, TW Kim, KK Park, Real-time breath monitoring using multi-channel MEMS resonator, Sensors and Actuators A: Physical,  (2023).
[5] Z.H. Shan He, Cristóvão Iglesias, Varun Mehta, Miodrag Bolic, A Real-Time Respiration Monitoring and Classification System Using a Depth Camera and Radars, Frontiers in Physiology,  (2022).
[6] S.U.R. Anuradha Singh, Sira Yongchareon, Peter Han Joo Chong, Modelling of ChestWall Motion for Cardiorespiratory Activity for Radar-Based NCVS Systems, sensors,  (2020).
[7] S.Q. Zhe Li, Chen Chen, Shuya Mei, Yulong Yao, Zhanqi Zhao, Wen Li, Yuxiao Deng, Yuan Gao, Emerging Trends and Hot Spots of Electrical Impedance Tomography Applications in Clinical Lung Monitoring, Frontiers in Medicine,  (2022).
[8] M.I. Eckhard Teschner, Steffen Leonhardt, Electrical Impedance Tomography:The realisation of regional ventilation monitoring, in: www.draeger.com (Ed.), 2015.
[9] B.T. Schranz C, Schädler D, Weiler N2, Möller K, MODEL-BASED VENTILATOR SETTINGS IN PRESSURE CONTROLLED VENTILATION, Biomed Tech,  (2013).
[10] Y.B.D. Tamir Yeshurun, Alon Herman, Stav Bar-Sheshet, Ronen Zilberman, Gil Bachar, Alexander Liberzon, Gideon Segev, A simulation of a medical ventilator with a realistic lungs model, F1000Research,  (2020).
[11] M.N.K. Husam Y. Al-Hetari, Mahmoud A. Al-Rumaima, Noman Q. Al-Naggar, Yasser M. Alginahi, Munirul Hasan, A Mathematical Model of Lung Functionality using Pressure Signal for Volume-Controlled Ventilation, in:  IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS 2020), 2020.
[12] C.B. Sarah Ostadabbas, David N. Ku, Larry J. Anderson, Maysam Ghovanloo, A Passive Quantitative Measurement of Airway Resistance using Depth Data, in:  Annu Int Conf IEEE Eng Med Biol Soc, 2014.
[13] A. Santhanam, Modeling, Simulation, And Visualization Of 3d Lung Dynamics, University of Central Florida, 2006.
[14] R.T. Philippe De Tillieux, Alexandru Foias, Iris Leroux, Imanne El Ma^achi, Hugues Leblond, Nikola Stikov, Julien Cohen-Adad, A Pneumatic Phantom for Mimicking Respiration-Induced Artifacts in Spinal MRI, Magnetic Resonance in Medicine,  (2017).
[15] M.L. F Wetterling, P Schimpf, H Liu, J Haueisen, The localization of focal heart activity via body surface potential measurements: tests in a heterogeneous torso phantom, PHYSICS IN MEDICINE AND BIOLOGY,  (2009) 5395–5409.
[16] J.W. Qi Wang, Xiuyan Li, Xiaojie Duan, Ronghua Zhang, Hong Zhang, Yanhe Ma, Huaxiang Wang, Jiabin Jia, Exploring Respiratory Motion Tracking through Electrical Impedance Tomography (EIT), IEEE Transactions on Instrumentation and Measurement,  (2021).
[17] T.R. Szabała, A Vejar, A robotic respiration phantom with patient data synchronization for medical tomography, Journal of Physics: Conference Series,  (2021).
[18] D.P. Jakob Orschulik, Tobias Menden, Steffen Leonhardt, Marian Walter, Three-dimensional pulmonary monitoring using focused electrical impedance measurements, Journal of Electrical Bioimpedence,  (2018) 84-95.
[19] V.R. Nafisi, Design and fabrication of a device for physiological biofeedback in ventilator equipment, Iran National Science Foundation (INSF), 2023.
[20] A.A.a.W.R.B. Lionheart, EIDORS: Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software, in, 2022.
[21] V.R.N. Maryam Beigzadeh, Introducing a respiratory phantom device with the ability of recording electrical impedance tomography: a step towards the real-time intelligent monitoring of lung aeration, in:  Iranian International Conference of Biomedical Engineering (ICBME), IEEE, Tehran, Iran, 2023.

Files

Share

How to cite

Statistics