A Wireless, Low-Power, and Miniaturized EIT System for Remote and Long-Term Monitoring of Lung Ventilation in the Isolation Ward of ICU

Abstract

Individualized lung-protective ventilation strategy is essential for patients with COVID-19. In this study, a wireless, low-power, and miniaturized electrical impedance tomography (EIT) system was developed for remote and long-term monitoring of lung ventilation for patients with COVID-19 in the isolation ward of ICU. A new strategy of combining filtering and improved voltage-controlled current was employed to design the current source for a simplified system structure, and a new differential receiver circuit consisting of a buffer amplification and a differential amplification was proposed to design the voltage measurement unit for high precision. Moreover, a Bluetooth interface was adopted for wireless data transmission, and components characterized by low power consumption were selected to minimize the system power consumption. The proposed EIT system occupies a total size of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6.5\times 4.5\times0.6$ </tex-math></inline-formula> cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and can work stably within 25 m from the wireless terminal installed with host EIT software. The system has a signal-to-noise of 70 dB at 50 kHz, stability of 0.1% relative change, and power consumption of 114 mW, as tested with a resistor phantom. Furthermore, a comparison between the proposed system and a commercial ICU EIT device was conducted on nine healthy volunteers for ventilation monitoring. The correlation between lung volume and relative impedance changes was higher than 0.9 for both EIT systems ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p &lt; 0.001$ </tex-math></inline-formula> ). The analysis of the corresponding EIT images revealed that both systems delivered comparable images in terms of linearity, repeatability, and regional ventilation distribution. The test and experimental results suggested that the proposed system could conveniently provide reliable data acquisition (DAQ) for remote and long-term lung ventilation monitoring.