Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 71, Issue -, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2022.3144223
Keywords
Signal to noise ratio; Electrical impedance tomography; Colored noise; Matched filters; Integrated circuit modeling; Harmonic analysis; Power harmonic filters; Colored noises; electrical impedance tomography (EIT); matched filter; noise model; signal-to-noise ratio (SNR) improvement
Funding
- National Natural Science Foundation of China [61701550]
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This article presents a comprehensive analysis of the signal-to-noise ratio (SNR) in electrical impedance tomography (EIT) systems. In addition to random noise, the influences of colored noises are considered. A novel noise model for EIT systems is proposed and validated through simulation and experiments. Conventional methods for reducing colored noises are discussed and evaluated in a laboratory-built EIT system.
Sufficient signal-to-noise ratio (SNR) is critical to guarantee the satisfactory performance of an electrical impedance tomography (EIT) system. In this article, a thorough SNR analysis of EIT systems is presented. Besides the well-known random noise, the influences of colored noises, such as switching noise, low-frequency noise, and harmonic noise, are considered. By investigating the colored noises, a novel noise model of electrical impedance tomography systems is first proposed, which is validated by both simulation and experiment conducted in a laboratory-built electrical impedance tomography system. Finally, different conventional methods to reduce the colored noises are discussed and associated circuit-level considerations are evaluated by applying a front-end isolation structure in the laboratory-built EIT system. Overall, this work provides a more practical noise model of electrical impedance tomography systems by including the colored noises. It can serve as a guide to improve the SNR and therefore the performance of an electrical impedance tomography system for high-demanding biomedical applications.
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