Abstract
Auscultation of lung sounds in vehicles such as an ambulance or aircraft is unachievable because of high noise levels. Also, the bandwidths of lung sounds and vehicle noise typically have significant overlap, limiting the utility of bandpass filtering. In this study, a passively shielded stethoscope coupler with one microphone to measure the (noise‐corrupted) lung sounds and another to measure the ambient noise was constructed. Lung sound measurements were performed on a healthy subject in a simulated USAF C‐130 aircraft environment within an acoustic chamber at noise levels ranging from 80 to 100 dB SPL. Adaptive filtering schemes using a least mean squares (lms) and a normalized least mean squares (nlms) approach were employed to extract lung sounds from the corrupted signal. Up to 25 dB of noise reduction over the 100–600 Hz frequency range was achieved with the lms algorithm, with the more complex nlms algorithm providing faster convergence and up to 5 dB of additional noise reduction. These findings indicate that a combination of active and passive noise reduction can be used to measure clinically useful lung sounds in high noise environments. [Work supported by US Air Force.]
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