Very Low Resource Digital Implementation of Bioimpedance Analysis

Type Article
Date 2019-08
Language English
Author(s) Soulier Fabien1, Lamlih Achraf1, Kerzérho Vincent1, Bernard Serge1, Rouyer Tristan2
Affiliation(s) 1 : LIRMM, CNRS, University Montpellier, 34095 Montpellier, France
2 : MARBEC, Ifremer, University Montpellier, 34203 Sète, France
Source Sensors (1424-8220) (MDPI AG), 2019-08 , Vol. 19 , N. 15 , P. 3381 (13p.)
DOI 10.3390/s19153381
WOS© Times Cited 3
Note This article belongs to the Special Issue Selected Papers from the 12th International Conference on Sensing Technology
Keyword(s) bioimpedance spectroscopy, multi-frequency, digital processing

Bioimpedance spectroscopy consists of measuring the complex impedance of biological tissues over a large frequency domain. This method is particularly convenient for physiological studies or health monitoring systems. For a wide range of applications, devices need to be portable, wearable or even implantable. Next generation of bioimpedance sensing systems thus require to be implemented with power and resource savings in mind. Impedance measurement methods are divided into two main categories. Some are based on “single-tone” signals while the others use “multi-tone” signals. The firsts benefit from a very simple analysis that may consist of synchronous demodulation. However, due to necessary frequency sweep, the total measurement may take a long time. On the other hand, generating a multi-frequency signal allows the seconds to cover the whole frequency range simultaneously. This is at the cost of a more complex analysis algorithm. This makes both approaches hardly suitable for embedded applications. In this paper, we propose an intermediate approach that combines the speed of multi-tone systems with a low-resource analysis algorithm. This results in a minimal implementation using only adders and synchronous adc. For optimal performances, this small footprint digital processing can be synthesized and embedded on a mixed-mode integrated circuit together with the analog front-end. Moreover, the proposed implementation is easily scalable to fit an arbitrary frequency range. We also show that the resulting impact on noise sensitivity can be mitigated.

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