Reproducibility of the Vesicular Breath Sounds in Normal Subjects

Abstract

Nonfiltered (NF) lung sounds from the apical area of the heart along with lung volumes and ECG signals were recorded from 5 normal subjects. The signals were digitized and subjected to three methods of heart sound cancelation: 75-Hz high-pass filtering (75 HF), ECG-triggered blanking (BL) and adaptive noise canceling (AF) [IEEE Trans. Biomed. Engng 33:1141–1148,1986]. The sound signals were then subjected to the fast Fourier transform algorithm to obtain power spectra. Five breaths from each subject were analyzed, and their spectra were similar and slightly skewed to the right. The average values of mean, median and mode frequencies of the whole breath of 5 subjects, respectively, were for NF: 64.62 ± 3.74, 44.57 ± 2.06 and 36.75 ± 1.79 Hz; for 75 HF: 150.42 ± 17.49, 114.02 ± 6.43 and 86.16 ± 3.13 Hz; for BL: 81.76 ± 6.02, 52.36 ± 2.79, 41.10 ± 3.15 Hz; for AF: 96.87 ± 11.58, 68.23 ± 10.44 and 52.25 ± 8.97 Hz. These values showed no differences between subjects. The F values obtained by the two-way analysis of variance of all breaths of all subjects (mean, median, mode) were: NF: 0.161, 0.341, 0.089; 75 HF: 0.455, 0.042, 0.085; BL: 0.108, 0.082, 0.057; AF: 0.130, 0.204, 0.113 (all p > 0.1). The data revealed a remarkable lack of variation within and between subjects, suggesting similar sites and mechanisms of production and transmission

Vibration Response Imaging in the Detection of Pleural Effusions: A Feasibility Study

“…Using normal breath sound distribution as a reference, abnormal distributions of sound energy can be used to identify potential pathological states [2,3,4,5,6]. Vibration response imaging (VRI) utilizes such technology.…”

Reduced order Kalman filtering for the enhancement of respiratory sounds

“…( k) as (4) where H = [00 ·-· 1]. Note that i'u the abov'e equations,' even though the dtiving process u( k) 'is a white process, v ~k) is a colored procesS owing to its band-limited behavio~.…”

“…Highpass filtering has traditionally been used as an ad-hoc solution to this separation problem. However, variability inherent to any biological system as well as the variability among subjects limits the effectiveness of the standard filtering schemes owing to the loss of spectral information [3], [4].…”

Interference cancellation in respiratory sounds via a multiresolution joint time-delay and signal-estimation scheme

“…However, the heart sounds are unavoidable and sometimes represent severe disturbing interference; each heartbeat produces two major sounds, known as the first and second heart sounds. In addition, intersubject and intrasubject biological variability and the overlap between frequency contents of the heart and respiratory sounds are important factors that preclude the application of deterministic filtering schemes [2], [3]. Some researchers apply highpass filtering schemes to remove the low-frequency part of the respiratory sound spectrum.…”

“…Some researchers apply highpass filtering schemes to remove the low-frequency part of the respiratory sound spectrum. However, in view of the studies carried out by other researchers [3]- [5], highpass filtering for this application results in loss of important signal information. More recently, various adaptive filtering schemes have been proposed to eliminate this kind of interference [6]- [9].…”