Noninvasive Estimation of Plasma Sodium Concentration During Hemodialysis via Capacitively Coupled Electrical Impedance Spectroscopy

Ravagli, Enrico; Crescentini, Marco; Riccio, P.; Severi, Stefano

doi:10.1109/tim.2019.2913612

Cited by 12 publications

(7 citation statements)

References 40 publications

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“…There are several options for the choice of the pseudorandom wideband excitation sequence xn [41]. One possibility consists in randomly generating the elements 𝑥 𝑛 ∈ {0,1}, with n=0,..,N-1, from a uniform binary discrete distribution and creating the cyclic inverse 𝑥 𝑛 (𝑖𝑛𝑣) by implementing (5) in the discrete-time domain, which implies the off-line computation of the DFT and Inverse Discrete Fourier Transform (IDFT). This approach simplifies the signal generation circuit, which can be reduced to a simple 1-bit digital-to-analog converter (DAC) or even a digital output but requires to store in the memory of the embedded system both the sequences xn and 𝑥 𝑛 (𝑖𝑛𝑣) , which could be an issue as long as the memory space is a limited resource.…”

Section: Generation Of the Pseudo-random Excitationmentioning

confidence: 99%

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Energy-Efficient PRBS Impedance Spectroscopy on a Digital Versatile Platform

Luciani

Crescentini

Romani

et al. 2021

IEEE Trans. Instrum. Meas.

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This paper presents the digital design of a versatile and low-power broadband impedance spectroscopy (IS) system based on pseudo-random binary sequence (PRBS) excitation. The PRBS technique allows fast, and low-power estimation of the impedance spectrum over a wide bandwidth with adequate accuracy, proving to be a good candidate for portable medical devices, especially. This paper covers the low-power design of the firmware algorithms and implements them on a versatile and reconfigurable digital platform that can be easily adjusted to the specific application. It will analyze the digital platform with the aim of reducing power consumption while maintaining adequate accuracy of the estimated spectrum. The paper studies two main algorithms (time-domain and frequency-domain) used for PRBSbased IS and implements both of them on the ultra-low-power GAP-8 digital platform. They are compared in terms of accuracy, measurement time, and power budget, while general design tradeoffs are drawn out. The time-domain algorithm demonstrated the best accuracy while the frequency-domain one contributes more to save power and energy. However, analysis of the energy-per-error FOM revealed that the time-domain algorithm outperforms the frequency-domain algorithm offering better accuracy for the same energy consumption. Numerical methods and microprocessor resources are exploited to optimize the implementation of both algorithms achieving 27 ms in processing time, power consumption as low as 1.4 mW and a minimum energy consumption per measurement of 0.5 mJ, for a dense impedance spectrum estimation of 214 points.

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Section: Generation Of the Pseudo-random Excitationmentioning

confidence: 99%

“…It consists of a generic AFE, whose description is out of the scope of this manuscript (e.g. we can use the AFE presented in [5] or [29]), analog/digital interfaces, and a ULP digital platform on which both algorithms are implemented. We chose GAP-8 System-onchip as the energy efficient digital platform.…”

Section: Hardware Architecturementioning

confidence: 99%

Energy-Efficient PRBS Impedance Spectroscopy on a Digital Versatile Platform

Luciani

Crescentini

Romani

et al. 2021

IEEE Trans. Instrum. Meas.

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“…M EASURING frequency response functions (FRF) is a first step towards the (physical) understanding of the dynamic behavior of real-life systems. Practical applications can be found in many disciplines of engineering and (bio-medical) sciences such as, vibration analysis of mechanical and civil engineering structures [1], [2], state-of-health monitoring of lithium-ion batteries [3], hemodialysis measurements [4], characterization of vegetable tissues [5], . .…”

Section: Introductionmentioning

confidence: 99%

Frequency Response Function Measurements via Local Rational Modeling, Revisited

Pintelon

Peumans

Vandersteen

et al. 2021

IEEE Trans. Instrum. Meas.

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A finite measurement time is at the origin of transient (sometimes called leakage) errors in nonparametric frequency response function (FRF) estimation. If the FRF varies significantly over the frequency resolution of the experiment (= reciprocal of the measurement time), then these transients (leakage) errors cause important bias and variance errors in the FRF estimate. To decrease these errors, several local modeling techniques have been proposed in the literature. This paper presents an overview of the existing methods and gives an indepth bias and variance analysis of the FRF and disturbing noise variance estimates. In addition, a new local modeling approach is described that combines the small bias error of the local rational approximation with the low noise sensitivity of the local polynomial approximation. It is based on an automatic local model order selection procedure applied to a specific subclass of rational functions.

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“…The latter system consists in exciting the battery by using a narrowband signal and spanning the center frequency of this excitation. The narrowband measurement system is intrinsically slower but with superior resolution [8], [9], [10]. Most EIS instruments are benchtop devices and cannot be applied directly on the field to characterize batteries while they are operating.…”

Section: Introductionmentioning

confidence: 99%