By Zahra Moussavi
Breath sounds have lengthy been vital signs of breathing healthiness and ailment. Acoustical tracking of breathing sounds has been utilized by researchers for varied diagnostic reasons. a number of a long time in the past, physicians depended on their listening to to observe any symptomatic symptoms in breathing sounds in their sufferers. although, by means of laptop know-how and electronic sign processing options lately, breath sound research has drawn a lot realization as a result of its diagnostic functions. automated breathing sound research can now quantify adjustments in lung sounds; make everlasting files of the measurements made and convey graphical representations that support with the prognosis and remedy of sufferers struggling with lung ailments. electronic sign processing recommendations were commonplace to derive features positive aspects of the lung sounds for either diagnostic and overview of remedy reasons. even supposing the analytical ideas of sign processing are principally self sufficient of the appliance, interpretation in their effects on organic facts, i.e. breathing sounds, calls for giant realizing of the concerned physiological approach. This lecture sequence starts off with an summary of the anatomy and body structure regarding human breathing approach, and proceeds to complex study in respiration sound research and modeling, and their program as diagnostic aids. even though many of the used sign processing strategies were defined in brief, the purpose of this e-book isn't to explain the analytical tools of sign processing however the program of them and the way the implications will be interpreted. The publication is written for engineers with collage point wisdom of arithmetic and electronic sign processing.
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Additional info for Fundamentals of Respiratory System and Sounds Analysis
This assumption holds true for the power-line noise and biological signals. , lung sounds. Even if we assume that the heart and lung sounds are uncorrelated in their source of generation, they become correlated when we record them on the surface of the chest wall as they both pass through the same medium. Two groups, who applied adaptive filtering for heart sound reduction, used ECG signals instead of the heart sound as the copy of the noise input [26, 27]. This is highly questionable as the ECG signal is not the noise of the lung sound record and hence even if the filter tries to adapt itself to the ECG signal, the results will not be meaningful.
This technique has been applied for separating speech signals  and for heart sound reduction . The assumption in applying this method is that the source signals are originally statistically independent and at least one of them has the Gaussian distribution. At least two versions of the mixed signals are required although the more the better the performance of separations, which is also at a much higher computational cost. cls 30 November 1, 2006 16:42 FUNDAMENTALS OF RESPIRATORY SOUNDS AND ANALYSIS In  lung sounds were recorded from two sensors on the chest wall to provide two mixed signals, and then ICA was applied on the spectrograms of the signals.
Instead of the spectrogram of the original lung sound signal, the spectrogram of the fifth-level coefficient of the wavelet transform of the original signal is calculated. Also, the threshold in this method does not need any tuning and is simply the mean of the average power of the original lung sound signal. 1: Mean and Standard Deviation Error (%) of Different Heart Sounds Localization Methods at a Low Flow Rate. 2: Mean and Standard Deviation Error (%) of Different Heart Sounds Localization Methods at a Medium Flow Rate.