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Electrical bioimpedance spectroscopy in time-variant systems: Is undersampling always a problem?
KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.ORCID iD: 0000-0001-7807-8682
KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.ORCID iD: 0000-0002-6995-967X
KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
2014 (English)In: Journal of Electrical Bioimpedance, ISSN 1891-5469, Vol. 5, no 1, 28-33 p.Article in journal (Refereed) Published
Abstract [en]

During the last decades, Electrical Bioimpedance Spectroscopy (EBIS) has been applied mainly by using the frequency-sweep technique, across a range of many different applications. Traditionally, the tissue under study is considered to be time-invariant and dynamic changes of tissue activity are ignored by treating the changes as a noise source. A new trend in EBIS is simultaneous electrical stimulation with several frequencies, through the application of a multi-sine, rectangular or other waveform. This method can provide measurements fast enough to sample dynamic changes of different tissues, such as cardiac muscle. This high sampling rate comes at a price of reduction in SNR and the increase in complexity of devices. Although the frequency-sweep technique is often inadequate for monitoring the dynamic changes in a variant system, it can be used successfully in applications focused on the time-invariant or slowly-variant part of a system. However, in order to successfully use frequency-sweep EBIS for monitoring time-variant systems, it is paramount to consider the effects of aliasing and especially the folding of higher frequencies, on the desired frequency e.g. DC level. This paper discusses sub-Nyquist sampling of thoracic EBIS measurements and its application in the case of monitoring pulmonary oedema. It is concluded that by considering aliasing, and with proper implementation of smoothing filters, as well as by using random sampling, frequency-sweep EBIS can be used for assessing time-invariant or slowly-variant properties of time-variant biological systems, even in the presence of aliasing. In general, undersampling is not always a problem, but does always require proper consideration.

Place, publisher, year, edition, pages
2014. Vol. 5, no 1, 28-33 p.
Keyword [en]
Electrical bioimpedance spectroscopy, Aliasing in thoracic impedance spectroscopy, frequency-sweep EBIS, Thoracic Impedance Measurements, sub-Nyquist sampling
National Category
Medical Equipment Engineering
Research subject
Medical Technology; Electrical Engineering
URN: urn:nbn:se:kth:diva-145304DOI: 10.5617/jeb.801Scopus ID: 2-s2.0-84902521900OAI: diva2:719323

QC 20140604

Available from: 2014-05-23 Created: 2014-05-15 Last updated: 2014-06-04Bibliographically approved
In thesis
1. Aspects of Electrical Bioimpedance Spectrum Estimation
Open this publication in new window or tab >>Aspects of Electrical Bioimpedance Spectrum Estimation
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Electrical bioimpedance spectroscopy (EBIS) has been used to assess the status or composition of various types of tissue, and examples of EBIS include body composition analysis (BCA) and tissue characterisation for skin cancer detection. EBIS is a non-invasive method that has the potential to provide a large amount of information for diagnosis or monitoring purposes, such as the monitoring of pulmonary oedema, i.e., fluid accumulation in the lungs. However, in many cases, systems based on EBIS have not become generally accepted in clinical practice. Possible reasons behind the low acceptance of EBIS could involve inaccurate models; artefacts, such as those from movements; measurement errors; and estimation errors. Previous thoracic EBIS measurements aimed at pulmonary oedema have shown some uncertainties in their results, making it difficult to produce trustworthy monitoring methods. The current research hypothesis was that these uncertainties mostly originate from estimation errors. In particular, time-varying behaviours of the thorax, e.g., respiratory and cardiac activity, can cause estimation errors, which make it tricky to detect the slowly varying behaviour of this system, i.e., pulmonary oedema.

The aim of this thesis is to investigate potential sources of estimation error in transthoracic impedance spectroscopy (TIS) for pulmonary oedema detection and to propose methods to prevent or compensate for these errors.   This work is mainly focused on two aspects of impedance spectrum estimation: first, the problems associated with the delay between estimations of spectrum samples in the frequency-sweep technique and second, the influence of undersampling (a result of impedance estimation times) when estimating an EBIS spectrum. The delay between frequency sweeps can produce huge errors when analysing EBIS spectra, but its effect decreases with averaging or low-pass filtering, which is a common and simple method for monitoring the time-invariant behaviour of a system. The results show the importance of the undersampling effect as the main estimation error that can cause uncertainty in TIS measurements.  The best time for dealing with this error is during the design process, when the system can be designed to avoid this error or with the possibility to compensate for the error during analysis. A case study of monitoring pulmonary oedema is used to assess the effect of these two estimation errors. However, the results can be generalised to any case for identifying the slowly varying behaviour of physiological systems that also display higher frequency variations.  Finally, some suggestions for designing an EBIS measurement system and analysis methods to avoid or compensate for these estimation errors are discussed.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. xi, 36 p.
TRITA-STH : report, ISSN 1653-3836 ; 2014:4
Electrical Bioimpedance Spectroscopy, Thoracic Bioimpedance Spectroscopy, Sub-Nyquist Sampling, Undersampling, Aliasing in Electrical Bioimpedance, Bioimpedance Estimation Error.
National Category
Medical Engineering Signal Processing
Research subject
Medical Technology; Electrical Engineering
urn:nbn:se:kth:diva-145643 (URN)978-91-7595-196-6 (ISBN)
2014-08-21, 221, Alfred Nobels Allé 10, Flemingsberg, 15:37 (English)

QC 20140604

Available from: 2014-06-04 Created: 2014-05-23 Last updated: 2014-06-04Bibliographically approved

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Abtahi, FarhadSeoane, Fernando

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