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Removing respiratory artefacts from transthoracic bioimpedance spectroscopy measurements
KTH, School of Technology and Health (STH). Philips Research Europe, High Tech. Campus 34, 5656AE, Eindhoven, Netherlands; ACTLab., Signal Processing Systems, TU Eindhoven, 5600MB Eindhoven, Netherlands.
Philips Research Europe, High Tech. Campus 34, 5656AE, Eindhoven, Netherlands.ORCID iD: 0000-0001-7807-8682
KTH, School of Technology and Health (STH).
KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Borås, Sweden.
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2013 (English)In: XV International Conference on Electrical Bio-Impedance (ICEBI) & XIV Conference on Electrical Impedance Tomography (EIT), Institute of Physics Publishing (IOPP), 2013, Vol. 434, no 1Conference paper (Refereed)
Abstract [en]

Transthoracic impedance spectroscopy (TIS) measurements from wearable textile electrodes provide a tool to remotely and non-invasively monitor patient health. However, breathing and cardiac processes inevitably affect TIS measurements, since they are sensitive to changes in geometry and air or fluid volumes in the thorax. This study aimed at investigating the effect of respiration on Cole parameters extracted from TIS measurements and developing a method to suppress artifacts. TIS data were collected from 10 participants at 16 frequencies (range: 10 kHz - 1 MHz) using a textile electrode system (Philips Technologie Gmbh). Simultaneously, breathing volumes and frequency were logged using an electronic spirometer augmented with data from a breathing belt. The effect of respiration on TIS measurements was studied at paced (10 and 16 bpm) deep and shallow breathing. These measurements were repeated for each subject in three different postures (lying down, reclining and sitting). Cole parameter estimation was improved by assessing the tidal expiration point thus removing breathing artifacts. This leads to lower intra-subject variability between sessions and a need for less measurements points to accurately assess the spectra. Future work should explore algorithmic artifacts compensation models using breathing and posture or patient contextual information to improve ambulatory transthoracic impedance measurements.

Place, publisher, year, edition, pages
Institute of Physics Publishing (IOPP), 2013. Vol. 434, no 1
, Journal of Physics Conference Series, ISSN 1742-6588 ; 434:1
Keyword [en]
Air, Artificial intelligence, Electric impedance, Electric impedance tomography, Parameter estimation, Patient monitoring, Textiles
National Category
Other Medical Engineering
URN: urn:nbn:se:kth:diva-136737DOI: 10.1088/1742-6596/434/1/012018ISI: 000326512200018ScopusID: 2-s2.0-84877333426OAI: diva2:676939
15th International Conference on Electrical Bio-Impedance, ICEBI 2013 and 14th Conference on Electrical Impedance Tomography, EIT 2013; Heilbad Heiligenstadt; Germany; 22 April 2013 through 25 April 2013

QC 20131209

Available from: 2013-12-08 Created: 2013-12-08 Last updated: 2016-04-18Bibliographically 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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