Automatic Signal Quality Index Determination of Radar-Recorded Heart Sound Signals Using Ensemble Classification

Beitrag in einer Fachzeitschrift

Details zur Publikation

Autorinnen und Autoren: Shi K, Schellenberger S, Michler F, Steigleder T, Malessa A, Lurz F, Ostgathe C, Weigel R, Kölpin A
Zeitschrift: IEEE Transactions on Biomedical Engineering
Jahr der Veröffentlichung: 2019
ISSN: 0018-9294


Objective: Radar technology promises to be a
touchless and thereby burden-free method for continuous
heart sound monitoring which can be used to detect cardiovascular
diseases. However, the first and most crucial step
is to differentiate between high- and low-quality segments
in a recording to assess their suitability for a subsequent
automated analysis. This paper gives a comprehensive
study on this task and firstly addresses the specific characteristics
of radar-recorded heart sound signals. Methods:
To gather heart sound signals recorded from radar, a
bistatic radar system was built and installed at the university
hospital. Under medical supervision, heart sound data
were recorded from 30 healthy test subjects. The signals
were segmented and labeled as high- or low-quality by a medical expert. Different state-of-the-art pattern classification
algorithms were evaluated for the task of automated
signal quality determination and the most promising one
was optimized and evaluated using leave-one-subject-out cross-validation. Results: The proposed classifier is able to
achieve an accuracy of up to 96.36% and demonstrates a
superior classification performance compared to the stateof-
the-art classifier with a maximum accuracy of 76.00 %.
Conclusion: This paper introduces an ensemble classifier
that is able to perform automated signal quality determination
of radar-recorded heart sound signals with a
high accuracy. Significance: Besides achieving a higher
performance compared to state-of-the-art classifiers, the
presented study is the first one to deal with the quality
determination of heart sounds that are recorded by radar
systems. The proposed method enables contactless and
continuous heart sound monitoring for the detection of
cardiovascular diseases.

FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Lurz, Fabian
Lehrstuhl für Technische Elektronik
Malessa, Anke Dr.
Abteilung für Palliativmedizin
Michler, Fabian
Lehrstuhl für Technische Elektronik
Ostgathe, Christoph Prof. Dr.
Professur für Palliativmedizin
Schellenberger, Sven
Lehrstuhl für Technische Elektronik
Shi, Kilin
Lehrstuhl für Technische Elektronik
Weigel, Robert Prof. Dr.-Ing.
Lehrstuhl für Technische Elektronik

Einrichtungen weiterer Autorinnen und Autoren

Brandenburgische Technische Universität Cottbus-Senftenberg (BTU)


Shi, K., Schellenberger, S., Michler, F., Steigleder, T., Malessa, A., Lurz, F.,... Kölpin, A. (2019). Automatic Signal Quality Index Determination of Radar-Recorded Heart Sound Signals Using Ensemble Classification. IEEE Transactions on Biomedical Engineering.

Shi, Kilin, et al. "Automatic Signal Quality Index Determination of Radar-Recorded Heart Sound Signals Using Ensemble Classification." IEEE Transactions on Biomedical Engineering (2019).


Zuletzt aktualisiert 2019-12-06 um 08:53