RALES LUNG SOUNDS FULL

To perform classification and prediction we utilized supervised learning nonparametric classifiers: neural networks and support vector machines. To develop algorithms for testing, the crackle features shown in Table 1 were assessed. A single recording lasted 20 seconds and typically contains a minimum of 3 breaths. The validation of the use of the device as a crackle counter has been reported.

RALES LUNG SOUNDS FULL

The STG software automatically identified crackles in all full breaths.

In this study, we chose the data obtained during the deeper than normal breathing maneuver.Ĭrackles were defined in accordance with accepted criteria. In our usual practice, patients are asked to perform several breathing maneuvers: normal breathing, deeper than normal breathing, coughing, and a vital capacity maneuver. The sounds detected by these microphones are amplified, filtered, and input into a computer for analysis. Each of these chest pieces contains a microphone. In brief, patients are asked to lie on a soft foam pad, which has stethoscope chest pieces embedded in it. The details of this device have been described. All patients were examined using a multichannel lung sound analyzer (STG16). There were 39 patients with IPF, 95 with CHF, and 123 with PN. The IPF patients were outpatients and were all seen by pulmonary specialists. The CHF and PN patients were inpatients in a teaching hospital, and diagnoses were confirmed by board certified specialists. The diagnostic category of each of the patients was that of the clinicians caring for these patients. The studies were not made on consecutive patients this is a convenience sample and we currently have over 1,000 patients for whom we have both the diagnosis and the lung sound analysis. To acquire patients into this study, we identified hospitalized patients and outpatients of a community teaching hospital who were diagnosed as having a specific cardiopulmonary disease or were considered to be normal by their caregivers. Patients were selected for this study from a pool of patients who had undergone lung sound analysis as a part of a broader study of the correlation of disease processes with lung sounds patterns. Our goal was to determine if there are features of the lung sounds in IPF patients that would help to distinguish them from the lung sounds of patients with CHF and PN. Using advanced statistical techniques we compared features of IPF crackles to those in patients with CHF and PN. In an attempt to reduce these complications, we studied the sound patterns of patients with these diseases using a multichannel lung sound analyzer (STG16) to determine if such analysis could help differentiate IPF from CHF and PN. On occasion, this can lead to serious, unwanted side effects such as dehydration due to the inappropriate administration of diuretics or an adverse reaction to an antibiotic that was not indicated in the first place. Unfortunately, they can be misinterpreted as being due to congestive heart failure (CHF) or pneumonia (PN), and as a consequence patients may receive inappropriate therapy. Their presence in a patient is often the first clue that the disease is present. IntroductionĬrackles are a common finding in patients with interstitial pulmonary fibrosis (IPF).

Computer analysis of crackles at the bedside has the potential of aiding clinicians in diagnosing IPF more easily and thus helping to avoid medication errors. Distinctive features are present in the crackles of IPF that help separate them from the crackles of CHF and PN. They were separated from those of CHF patients with a sensitivity of 0.77, a specificity of 0.85 and an accuracy of 0.82. The IPF crackles had distinctive features that allowed them to be separated from those in patients with PN with a sensitivity of 0.82, a specificity of 0.88 and an accuracy of 0.86. Crackle features were analyzed using machine learning methods including neural networks and support vector machines. We studied 39 patients with IPF, 95 with CHF and 123 with PN using a 16-channel lung sound analyzer. The purpose of this study was to determine whether the crackles in patients with IPF differ from those in patients with CHF and PN. Misinterpretation of these crackles can lead to inappropriate therapy. The crackles in patients with interstitial pulmonary fibrosis (IPF) can be difficult to distinguish from those heard in patients with congestive heart failure (CHF) and pneumonia (PN).

Rales lung sounds