Proceedings ArticleDOI
Heart Sounds Separation From Lung Sounds Using Independent Component Analysis
Mahsa T. Pourazad,Zahra Moussavi,F. Farahmand,Rabab K. Ward +3 more
- Vol. 2005, pp 2736-2739
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TLDR
To separate the two signals, a novel HS separation method based on independent component analysis (ICA) is developed and analysis of the results as well as subjective inspections indicate the efficiency of the proposed method in terms of HS separation from lung sounds.Abstract:
Heart beat is an unavoidable source of interference during lung sound recording. This disturbance is more significant at low and medium breathing flow rates. Removing heart sounds (HS) from lung sound recordings or vice versa is a challenging task but of great interest for respiratory specialists and cardiologists. In this study, to separate the two signals, a novel HS separation method based on independent component analysis (ICA) is developed. This method applies an ICA algorithm to the spectrograms of two simultaneous lung sound recordings obtained at two different locations on the chest and yields the independent spectrograms of the separated signals. Then, by implementing the inverse short time Fourier transform (ISTFT), the separated signals are reconstructed in the time domain. The method was applied to data of two healthy subjects. Analysis of the results as well as subjective inspections indicate the efficiency of the proposed method in terms of HS separation from lung soundsread more
Citations
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Support Vectors Machine-based identification of heart valve diseases using heart sounds
TL;DR: An automated diagnosis system for the identification of heart valve diseases based on the Support Vector Machines (SVM) classification of heart sounds was applied in a representative global dataset of 198 heart sound signals, which come both from healthy medical cases and from cases suffering from the four most usualheart valve diseases.
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The electronic stethoscope
Shuang Leng,Ru San Tan,Ru San Tan,Kevin T. C. Chai,Chao Wang,Dhanjoo N. Ghista,Liang Zhong,Liang Zhong +7 more
TL;DR: The paper provides the technological and medical basis for the development and commercialization of a real-time integrated heart sound detection, acquisition and quantification system.
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Lung sound classification using cepstral-based statistical features
TL;DR: It is found that the newly investigated features are more robust than existing features and show better recognition accuracy even in low signal-to-noise ratios (SNRs).
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Narrow-Band Interference Mitigation for SAR Using Independent Subspace Analysis
TL;DR: Experimental results of simulated and measured data have demonstrated the effectiveness of the proposed method for NBI mitigation using the independent subspace analysis.
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Precision wearable accelerometer contact microphones for longitudinal monitoring of mechano-acoustic cardiopulmonary signals.
TL;DR: A wearable, hermetically-sealed high-precision vibration sensor that combines the characteristics of an accelerometer and a contact microphone to acquire wideband mechano-acoustic physiological signals, and enable simultaneous monitoring of multiple health factors associated with the cardiopulmonary system.
References
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Book
Independent Component Analysis
TL;DR: Independent component analysis as mentioned in this paper is a statistical generative model based on sparse coding, which is basically a proper probabilistic formulation of the ideas underpinning sparse coding and can be interpreted as providing a Bayesian prior.
Reference EntryDOI
Independent Component Analysis
Hannu Oja,Klaus Nordhausen +1 more
TL;DR: A statistical generative model called independent component analysis is discussed, which shows how sparse coding can be interpreted as providing a Bayesian prior, and answers some questions which were not properly answered in the sparse coding framework.
Journal ArticleDOI
Blind beamforming for non-gaussian signals
TL;DR: In this paper, a computationally efficient technique for blind estimation of directional vectors, based on joint diagonalization of fourth-order cumulant matrices, is presented for beamforming.
Book
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Andrzej Cichocki,Shun-ichi Amari +1 more
TL;DR: This volume unifies and extends the theories of adaptive blind signal and image processing and provides practical and efficient algorithms for blind source separation, Independent, Principal, Minor Component Analysis, and Multichannel Blind Deconvolution (MBD) and Equalization.
Journal ArticleDOI
High-order contrasts for independent component analysis
TL;DR: This article considers high-order measures of independence for the independent component analysis problem and discusses the class of Jacobi algorithms for their optimization and compares the proposed approaches with gradient-based techniques from the algorithmic point of view and also on a set of biomedical data.
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