Med Biol Eng Comput - Acoustic thoracic image of crackle sounds using linear and nonlinear processing techniques.

Tópicos

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Resumo

In this study, a novel approach is proposed, the imaging of crackle sounds distribution on the thorax based on processing techniques that could contend with the detection and count of crackles; hence, the normalized fractal dimension (NFD), the univariate AR modeling combined with a supervised neural network (UAR-SNN), and the time-variant autoregressive (TVAR) model were assessed. The proposed processing schemes were tested inserting simulated crackles in normal lung sounds acquired by a multichannel system on the posterior thoracic surface. In order to evaluate the robustness of the processing schemes, different scenarios were created by manipulating the number of crackles, the type of crackles, the spatial distribution, and the signal to noise ratio (SNR) at different pulmonary regions. The results indicate that TVAR scheme showed the best performance, compared with NFD and UAR-SNN schemes, for detecting and counting simulated crackles with an average specificity very close to 100%, and average sensitivity of 98 ? 7.5% even with overlapped crackles and with SNR corresponding to a scaling factor as low as 1.5. Finally, the performance of the TVAR scheme was tested against a human expert using simulated and real acoustic information. We conclude that a confident image of crackle sounds distribution by crackles counting using TVAR on the thoracic surface is thoroughly possible. The crackles imaging might represent an aid to the clinical evaluation of pulmonary diseases that produce this sort of adventitious discontinuous lung sounds.

Resumo Limpo

studi novel approach propos imag crackl sound distribut thorax base process techniqu contend detect count crackl henc normal fractal dimens nfd univari ar model combin supervis neural network uarsnn timevari autoregress tvar model assess propos process scheme test insert simul crackl normal lung sound acquir multichannel system posterior thorac surfac order evalu robust process scheme differ scenario creat manipul number crackl type crackl spatial distribut signal nois ratio snr differ pulmonari region result indic tvar scheme show best perform compar nfd uarsnn scheme detect count simul crackl averag specif close averag sensit even overlap crackl snr correspond scale factor low final perform tvar scheme test human expert use simul real acoust inform conclud confid imag crackl sound distribut crackl count use tvar thorac surfac thorough possibl crackl imag might repres aid clinic evalu pulmonari diseas produc sort adventiti discontinu lung sound

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