Statistical signal processing technique for identification of different infected sites of the diseased lungs.
Accurate Diagnosis of lung disease depends on understanding the sounds emanating from lung and its location. Lung sounds are of significance as they supply precise and important information on the health of the respiratory system. In addition, correct interpretation of breath sounds depends on a systematic approach to auscultation; it also requires the ability to describe the location of abnormal finding in relation to bony structures and anatomic landmark lines. Lungs consist of number of lobes; each lung lobe is further subdivided into smaller segments. These segments are attached to each other. Knowledge of the position of the lung segments is useful and important during the auscultation and diagnosis of the lung diseases. Usually the medical doctors give the location of the infection a segmental position reference. Breath sounds are auscultated over the anterior chest wall surface, the lateral chest wall surfaces, and posterior chest wall surface. Adventitious sounds from different location can be detected. It is common to seek confirmation of the sound detection and its location using invasive and potentially harmful imaging diagnosis techniques like x-rays. To overcome this limitation and for fast, reliable, accurate, and inexpensive diagnose a technique is developed in this research for identifying the location of infection through a computerized auscultation system.
Computer Engineering Department, University of Ottawa, Ottawa, ON, Canada. abbas@mcrlab.uottawa.ca
Ali
A
Abbas
D006801:Humans; D008171:Lung Diseases / Q000175:diagnosis* / Q000503:physiopathology*; D015233:Models, Statistical; D012135:Respiratory Sounds / Q000175:diagnosis*; D012815:Signal Processing, Computer-Assisted; D019023:Stethoscopes