Acoustic Sensors for Biomedical Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Acoustic Sensors for Biomedical Applications write by Nilanjan Dey. This book was released on 2018-07-20. Acoustic Sensors for Biomedical Applications available in PDF, EPUB and Kindle. In this book, application-related studies for acoustic biomedical sensors are covered in depth. The book features an array of different biomedical signals, including acoustic biomedical signals as well as the thermal biomedical signals, magnetic biomedical signals, and optical biomedical signals to support healthcare. It employs signal processing approaches, such as filtering, Fourier transform, spectral estimation, and wavelet transform. The book presents applications of acoustic biomedical sensors and bio-signal processing for prediction, detection, and monitoring of some diseases from the phonocardiogram (PCG) signal analysis. Several challenges and future perspectives related to the acoustic sensors applications are highlighted. This book supports the engineers, researchers, designers, and physicians in several interdisciplinary domains that support healthcare.
Acoustic Sensors for Biomedical Applications
Acoustic Sensors for Biomedical Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Acoustic Sensors for Biomedical Applications write by Nilanjan Dey. This book was released on 2019. Acoustic Sensors for Biomedical Applications available in PDF, EPUB and Kindle. In this book, application-related studies for acoustic biomedical sensors are covered in depth. The book features an array of different biomedical signals, including acoustic biomedical signals as well as the thermal biomedical signals, magnetic biomedical signals, and optical biomedical signals to support healthcare. It employs signal processing approaches, such as filtering, Fourier transform, spectral estimation, and wavelet transform. The book presents applications of acoustic biomedical sensors and bio-signal processing for prediction, detection, and monitoring of some diseases from the phonocardiogram (PCG) signal analysis. Several challenges and future perspectives related to the acoustic sensors applications are highlighted. This book supports the engineers, researchers, designers, and physicians in several interdisciplinary domains that support healthcare.
Sensors in Biomedical Applications
Sensors in Biomedical Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sensors in Biomedical Applications write by Gabor Harsanyi. This book was released on 2000-05-01. Sensors in Biomedical Applications available in PDF, EPUB and Kindle. While most books contain some information on related sensors topics, they are limited in their scope on biomedical sensors. Sensors in Biomedical Applications: Fundamentals, Design, Technology and Applications is the first systematized book to concentrate on all available and potential sensor devices of biomedical applications! Sensors in Bi
Biomedical Sensors
Biomedical Sensors - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Biomedical Sensors write by Deric P. Jones. This book was released on 2010. Biomedical Sensors available in PDF, EPUB and Kindle. Sensors are the eyes, ears, and more, of the modern engineered product or system- including the living human organism. This authoritative reference work, part of Momentum Press's new Sensors Technology series, edited by noted sensors expert, Dr. Joe Watson, will offer a complete review of all sensors and their associated instrumentation systems now commonly used in modern medicine. Readers will find invaluable data and guidance on a wide variety of sensors used in biomedical applications, from fluid flow sensors, to pressure sensors, to chemical analysis sensors. New developments in biomaterials- based sensors that mimic natural bio-systems will be covered as well. Also featured will be ample references throughout, along with a useful Glossary and symbols list, as well as convenient conversion tables.
Acoustic Sensor Array Signal Processing for Biomedical Applications
Acoustic Sensor Array Signal Processing for Biomedical Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Acoustic Sensor Array Signal Processing for Biomedical Applications write by S. M. Akramus Salehin. This book was released on 2011. Acoustic Sensor Array Signal Processing for Biomedical Applications available in PDF, EPUB and Kindle. This thesis develops array signal processing theories for selected biomedical applications involving acoustic waves. Specifically, we consider source localization in the interior of sensor arrays for lung sound localization and efficient algorithms for photoacoustic imaging. Lung sound localization provides quantitative results to the extent and location of lung disorders. Photoacoustic imaging is important for the early detection of cancer and has numerous other biomedical applications. Previous lung sound localization methods cannot deal with multiple sources or have analytical performance measures. We propose two methods utilizing the eigen basis decomposition of the wavefield and the Minimum Variance spectrum for multiple source localization. Analytical performance measures were derived for resolution and spatial aliasing. The performance of our methods for lung sound localization together with the performance measures were proven by simulations. We consider the photoacoustic inversion problem from a frequency invariant source localization perspective. Complete series and fast photoacoustic inversion methods have not been developed for the circular and spherical sensor geometries. A new theory is developed for photoacoustic reconstruction where the source distribution is expanded with a suitable series expansion such that separating the modes in the wavefield expansion at particular frequencies, separates the information in the source expansion. This theory is applied for photoacoustic inversion using a circular acquisition geometry. The source is expanded using a Fourier Bessel series and the coefficients are estimated by processing frequencies corresponding to the Bessel zeros. The proposed method is faster than previous approaches and the derivation is valid even for finite measurement bandwidth. This new theory is flexible enough to be applied for arbitrary sensor geometries and allows the selection of a minimum number of frequency samples for reconstruction. For previous frequency domain methods, there was no way to determine the minimum number of frequency samples required. Further, numerical experiments proved the effectiveness of our approach. The extension of the proposed theory for photoacoustic inversion with a spherical array geometry was proposed. This new method expands the source distribution with a spherical Fourier Bessel series whose coefficients were now obtained by processing frequencies corresponding to the spherical Bessel zeros. Using computational order analysis and numerical experiments, this proposed method was shown to be faster than the backprojection and the Fourier series methods. To enhance the reconstruction of our proposed methods, we introduced a subgradient based Total Variation (TV) minimization and an alternating projections post processing method. Both these methods were designed to handle the large data sets present in photoacoustic tomography. Applications of these two post processing ideas to previously proposed inversion methods are either difficult or impossible. The proposed inversion methods provide projection of the source distribution onto a set of basis functions. Therefore, these two post processing methods were developed to reconstruct a source distribution that preserves these projections and ensures that the source distribution is non-negative. Numerical experiments performed showed that reconstruction quality was improved by applying these two post processing methods. Further, the TV minimization method provided better reconstruction when compared to the alternating projections method.
