Noise/spike detection in phonocardiogram signal as a cyclic random process with non-stationary period interval

Abstract The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles ar...

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Bibliographic Details
Published in:Computers in biology and medicine 2013-09, Vol.43 (9), p.1205-1213
Main Authors: Naseri, H, Homaeinezhad, M.R, Pourkhajeh, H
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Cluster template
Clustering
Correlation coefficient
Databases, Factual
Energy time series
Ensemble averaging
Female
Filtering
Filtering strategy curve
Frequency time series
Heart
Humans
Internal Medicine
Male
Noise
Orthogonal reconstruction
Other
Phonocardiography - instrumentation
Phonocardiography - methods
Signal Processing, Computer-Assisted
Sound
Studies
Time series
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Summary:Abstract The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles are clustered into a finite number of groups based on appropriate geometrical- and frequency-based time series. Next, the median template of each time series of each cluster is calculated. Afterwards, a correlation-based technique is devised for making a comparison between a test cycle feature and the associated time series of each cluster. Finally, by applying a suitably chosen threshold for the calculated correlation values, a segment is prescribed to be either clean or noisy. As a key merit of this research, the procedure can introduce a decision support for choosing accurately orthogonal-expansion-based filtering or to remove noisy segments. In this paper, the application procedure of the proposed method is comprehensively described by applying it to phonocardiogram (PCG) signals for finding noisy cycles. The database consists of 126 records from several patients of a domestic research station acquired by a 3 M Littmann® 3200, 4 KHz sampling frequency electronic stethoscope. By implementing the noisy segments detection algorithm with this database, a sensitivity of Se=91.41% and a positive predictive value, PPV=92.86% were obtained based on physicians assessments.
ISSN:0010-4825
1879-0534
DOI:10.1016/j.compbiomed.2013.05.020