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      Monitoring and analysis of lung sounds remotely

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          Visual and auditory analysis of respiratory sound signals promises improved detection of certain types of lung diseases. LabVIEW software was used to design a system that monitors the respiratory activity of the patient. The program developed calculates the respiratory rate, displays the time expanded waveform of the lung sound, and computes the fast Fourier transform and short-time Fourier transform to present the power spectrum and spectrogram respectively. These parameters are transmitted synchronously to the remote station using the Internet for online monitoring of the patient.

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          Most cited references 11

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          Method for automatic detection of wheezing in lung sounds.

          The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.
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            A simple computer-based measurement and analysis system of pulmonary auscultation sounds.

            Listening to various lung sounds has proven to be an important diagnostic tool for detecting and monitoring certain types of lung diseases. In this study a computer-based system has been designed for easy measurement and analysis of lung sound using the software package DasyLAB. The designed system presents the following features: it is able to digitally record the lung sounds which are captured with an electronic stethoscope plugged to a sound card on a portable computer, display the lung sound waveform for auscultation sites, record the lung sound into the ASCII format, acoustically reproduce the lung sound, edit and print the sound waveforms, display its time-expanded waveform, compute the Fast Fourier Transform (FFT), and display the power spectrum and spectrogram.
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              • Abstract: not found
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              Basic techniques for respiratory sound analysis


                Author and article information

                Int J Chron Obstruct Pulmon Dis
                International Journal of COPD
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove Medical Press
                20 July 2011
                : 6
                : 407-412
                Department of Instrumentation Technology, RV College of Engineering, Bangalore, Karnataka, India
                Author notes
                Correspondence: Nitin Sahgal, Department of Instrumentation Technology, RV College of Engineering, Bangalore, Karnataka, India, 560059, Tel +91 98 86269310, Email nitin.sahgal@
                © 2011 Sahgal, publisher and licensee Dove Medical Press Ltd.

                This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.

                Short Report

                Respiratory medicine

                labview, monitoring, power spectrum, spectrogram, lung sounds, remote


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