Adaptive motion-artifact reduction in capacitive ECG measurements by using the power-line interference

L. Xu, C. Rabotti, Y. Zhang, Pieter Harpe, M. Mischi, Mohammed Meftah, Sotir Filipov Ouzounov

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

7 Citations (Scopus)
1 Downloads (Pure)

Abstract

Capacitive electrodes can be employed for noninvasive electrocardiography (ECG) measurements; they are especially suitable for long-term ambulatory monitoring. However, capacitive electrodes are very sensitive to motion artifacts (MAs) due to variable coupling distance. Adaptive filtering has been widely used for optimal MA reduction in biopotential measurements. Unfortunately, the existing adaptive-filtering methods require a reference signal recorded by additional sensors, limiting their applicability in ambulatory settings. In the present study, a novel adaptive MA removal method is proposed where the reference signal is extracted from the power-line interference (PLI). PLI usually appears in ECG measurements due to unbalanced electrode impedance. Movement of the electrodes causes not only MAs but also variations in the PLI. Demodulation of the PLI may, therefore, represent a reference signal reflecting the sensor movement for adaptive MA removal by signal decorrelation. Preliminary validation on both simulation and real data showed effective MA removal by the proposed adaptive filter, possibly leading to improved analysis of capacitive ECG signals in ambulatory settings.
Original languageEnglish
Title of host publication2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)978-1-5386-3392-2
ISBN (Print)9781538633915
DOIs
Publication statusPublished - 16 Aug 2018
Event13th Annual IEEE International Symposium on Medical Measurements & Applications - Rome, Italy
Duration: 11 Jun 201814 Jun 2018

Conference

Conference13th Annual IEEE International Symposium on Medical Measurements & Applications
Abbreviated titleIEEE MeMeA 2018
Country/TerritoryItaly
CityRome
Period11/06/1814/06/18

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