ABSTRACT
Auscultation of lung sounds in patient transport vehicles such as an ambulance or aircraft is unachievable because of high ambient noise levels. Aircraft noise levels of 90-100 dB SPL are common, while lung sounds have been measured in the 22-30 dB SPL range in free space and 65-70 dB SPL within a stethoscope coupler. Also, the bandwidth of lung sounds and vehicle noise typically has significant overlap, limiting the utility of traditional band-pass filtering. In this study, a passively shielded stethoscope coupler that contains one microphone to measure the (noise-corrupted) lung sound and another to measure the ambient noise was constructed. Lung sound measurements were made 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 the lung sounds from the noise-corrupted signal. Approximately 15 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 lung sounds in high noise environments.
