Decomposing of cardiac and respiratory signals from electrical bio-impedance data using filtering method

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an attempt to decompose cardiac and respiratory signals from an electrical bioimpedance (EBI) dataset. To accomplish this task, the conventional filtering method is used. FIR (low pass filter (LPF) and high pass filter (HPF)) was intended to decompose the impedance respirogram (IRG) and impedance cardiogram (ICG), (the clean ECG was also extracted by filtering method). The decomposed components can be analysed and processed further, each one separately. Investigation was accomplished under the assumption that the total EBI dataset is the summation of cardiac and respiratory components, motion artefacts, stochastic disturbance and noise. The impedances were measured using a Zurich Instruments HF2IS Impedance Spectroscope. A sixteen electrodes configuration belt was used around a human thorax, to measure the EBI. This study showed that it is not possible to decompose cardiac and respiratory signals completely through conventional filtering method.
Original languageEnglish
Title of host publicationThe IFMBE International Conference on Health Informatics (ICHI’13
PublisherSpringer
Pages252-255
ISBN (Electronic)9783319030050
ISBN (Print)9783319030043
DOIs
Publication statusPublished - 7 Nov 2013
Event2013 International Conference on Health Informatics - Vilamoura, Portugal
Duration: 7 Nov 20139 Nov 2013

Conference

Conference2013 International Conference on Health Informatics
Abbreviated titleICHI 2013
Country/TerritoryPortugal
CityVilamoura
Period7/11/139/11/13

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