Title :
Separating Heart Sounds from Lung Sounds - Accurate Diagnosis of Respiratory Disease Depends on Understanding Noises
Author :
Gnitecki, J. ; Moussavi, Z.M.K.
Author_Institution :
Dept. of Electr. Eng., Manitoba Univ., Winnipeg, Man.
Abstract :
This study reviews the adaptive methods of canceling heart sounds from lung sounds that have been investigated over approximately 20 years. Filtering techniques are categorized as linear adaptive filters and filters employing time-frequency based methods. Several filtering schemes are outlined within these two categories. Methods of heart sound localization are indicated in conjunction with the studies of heart-sound cancellation. Details such as digitization parameters, the location of heart and lung sound recordings, and the number of subjects used in each study. Since a primary objective of respiratory sound research is bring about improvements to monitoring and diagnosis of respiratory disease, the potential usefulness of any method for filtering heart sounds from lung sounds rests on its ability to perform in a clinical setting
Keywords :
adaptive filters; diseases; electrocardiography; least mean squares methods; lung; medical signal processing; patient monitoring; pneumodynamics; time-frequency analysis; digitization parameters; electrocardiogram; filtering technique; heart sound localization; heart-sound cancellation technique; least squares estimation; linear adaptive filtering algorithm; linear adaptive filters; lung sound recordings; respiratory disease diagnosis; respiratory disease monitoring; respiratory sound research; time-frequency based method; Acoustic noise; Adaptive filters; Cardiac disease; Cardiovascular diseases; Filtering; Heart; Lungs; Noise cancellation; Nonlinear filters; Time frequency analysis; Algorithms; Auscultation; Diagnosis, Computer-Assisted; Heart Sounds; Humans; Lung Diseases; Respiratory Sounds; Sound Spectrography;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
DOI :
10.1109/MEMB.2007.289118