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Digital Spectrum Analysis of Respiratory Sound
IEEE Transactions on Biomedical Engineering, 1981The applcation of the fast Fourier transform in the digital analysis of various biological signals in the frequency domain is well-known. In this paper a method is described for spectrum analysis of respiratory sound using the technique of fast Fourier transform.
S K, Chowdhury, A K, Majumder
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Classification of Respiratory Conditions using Auscultation Sound
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021Management of respiratory conditions relies on timely diagnosis and institution of appropriate management. Computerized analysis and classification of breath sounds has a potential to enhance reliability and accuracy of diagnostic modality while making it suitable for remote monitoring, personalized uses, and self-management uses.
Quan T, Do +4 more
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Automatic and Unsupervised Snore Sound Extraction From Respiratory Sound Signals
IEEE Transactions on Biomedical Engineering, 2011In this paper, an automatic and unsupervised snore detection algorithm is proposed. The respiratory sound signals of 30 patients with different levels of airway obstruction were recorded by two microphones: one placed over the trachea (the tracheal microphone), and the other was a freestanding microphone (the ambient microphone).
Ali, Azarbarzin, Zahra M K, Moussavi
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Computerized respiratory sound based diagnosis of pneumonia
Medical & Biological Engineering & Computing, 2023Globally, respiratory disorders are a great health burden, affecting as well as destroying human lives; pneumonia is one among them. Pneumonia stages can progress from mild stage to even towards deadly if it is misdiagnosed. Misdiagnosis happens as it exhibits the symptoms identical to other respiratory diseases.
Nishi Shahnaj Haider, Ajoy K. Behera
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Archivos de bronconeumologia, 1995
After having invented the stethoscope, Laennec published his treatise on auscultation in 1819, describing the acoustic events generated by ventilation and linking them with anatomopathological findings. The weak points of his semiology lay in its subjective and interpretative character, expressed by an imprecise and picturesque nomenclature.
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After having invented the stethoscope, Laennec published his treatise on auscultation in 1819, describing the acoustic events generated by ventilation and linking them with anatomopathological findings. The weak points of his semiology lay in its subjective and interpretative character, expressed by an imprecise and picturesque nomenclature.
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Chaotic dynamics of respiratory sounds
Chaos, Solitons & Fractals, 2006There is a growing interest in nonlinear analysis of respiratory sounds (RS), but little has been done to justify the use of nonlinear tools on such data. The aim of this paper is to investigate the stationarity, linearity and chaotic dynamics of recorded RS. Two independent data sets from 8 + 8 healthy subjects were recorded and investigated.
C. Ahlstrom +3 more
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Hierarchical classification of respiratory sounds
Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286), 2002In this study, a novel decision fusion scheme for the classification of respiratory sounds is proposed. Furthermore a regularization scheme is applied to the data to stabilize training and consultation. The method consists of dividing respiratory cycles of patients into phases, and classifying each phase with a separate multilayer perceptron, called ...
Y.P. Kahya +3 more
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Method of classifying respiratory sounds
The Journal of the Acoustical Society of America, 1999The invention provides a method of classifying respiratory sounds. The method provides the steps of selecting a first set of respiratory sounds and manually determining a classification content of the first set of respiratory events. The method further includes extrapolating the classification content of the first set of respiratory events to an at ...
Gil Raviv, Charles A. Weingarten
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Classifying Respiratory Sounds with Different Feature Sets
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006In this study, different feature sets are used in conjunction with (k-nearest neighbors) k-NN and artificial neural network (ANN) classifiers to address the classification problem of respiratory sound signals. A comparison is made between the performances of k-NN and ANN classifiers with different feature sets derived from respiratory sound data ...
Yasemin P, Kahya +2 more
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Normal Versus Adventitious Respiratory Sounds
2018Respiratory sounds are composed by normal and adventitious respiratory sounds which comprise the sounds heard over the trachea/mouth and chest wall. All sounds can be described using frequency, intensity, and timbre. Frequency and intensity are perceived by human beings as pitch and loudness, respectively.
Alda Marques, Ana Oliveira
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