Name
Abstract | ||
|---|---|---|
The stethoscope is widely used for listening to heart sounds (cardiology), lung sounds (chest medicine) and digestive, bowel sounds, etc. An obvious development from this is to seek to automate the process by which a physician listens to and interprets the sounds. In parallel with signal processing developments, medical usage of diagnostic instrumentation is changing. The study described in this paper aimed to prove the feasibility of an automatic stethoscope for particular screening and monitoring algorithms, for which we envisage genuine clinical applicability. The first algorithm is to enable non-specialists to screen for pulmonary fibrosis. The algorithm was found to distinguish effectively between signals representing patients with chronic obstructive pulmonary disease (COPD), those with pulmonary fibrosis and normal individuals. A clear demarcation was observed between signals from patients in different diagnostic categories, with orders of magnitude differences between the groups. The second application is the monitoring of asthmatic patients. The proportion of wheeze within a given time recording is an objective indicator of the patient's condition, which can be used to monitor the person's progress during treatment. The proposed usage of each algorithm is demonstrated through a conceptual device, in which the ability to objectively quantify the patient's condition represents a powerful opportunity to improve clinical outcomes. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.jfranklin.2006.08.003 | Journal of the Franklin Institute |
Keywords | Field | DocType |
Auscultation,Signal processing,Wavelets,Automatic stethoscope,Chest medicine | COPD,Signal processing,Stethoscope,Chest medicine,Control theory,Active listening,Medical physics,Wheeze,Auscultation,Mathematics,Heart sounds | Journal |
Volume | Issue | ISSN |
344 | 3 | 0016-0032 |
Citations | PageRank | References |
14 | 1.34 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Marshall | 1 | 14 | 1.34 |
| S. Boussakta | 2 | 135 | 11.59 |