Optimal wavelet denoising for smart biomonitor systems

Sheila R. Messer; John Agzarian; Derek Abbott

doi:10.1117/12.418781

16 March 2001 Optimal wavelet denoising for smart biomonitor systems

Sheila R. Messer, John Agzarian, Derek Abbott

Proceedings Volume 4236, Smart Electronics and MEMS II; (2001) https://doi.org/10.1117/12.418781
Event: Smart Materials and MEMS, 2000, Melbourne, Australia

Abstract

Future smart-systems promise many benefits for biomedical diagnostics. The ideal is for simple portable systems that display and interpret information from smart integrated probes or MEMS-based devices. In this paper, we will discuss a step towards this vision with a heart bio-monitor case study. An electronic stethoscope is used to record heart sounds and the problem of extracting noise from the signal is addressed via the use of wavelets and averaging. In our example of heartbeat analysis, phonocardiograms (PCGs) have many advantages in that they may be replayed and analysed for spectral and frequency information. Many sources of noise may pollute a PCG including foetal breath sounds if the subject is pregnant, lung and breath sounds, environmental noise and noise from contact between the recording device and the skin. Wavelets can be employed to denoise the PCG. The signal is decomposed by a discrete wavelet transform. Due to the efficient decomposition of heart signals, their wavelet coefficients tend to be much larger than those due to noise. Thus, coefficients below a certain level are regarded as noise and are thresholded out. The signal can then be reconstructed without significant loss of information in the signal. The questions that this study attempts to answer are which wavelet families, levels of decomposition, and thresholding techniques best remove the noise in a PCG. The use of averaging in combination with wavelet denoising is also addressed. Possible applications of the Hilbert Transform to heart sound analysis are discussed.

Citation Download Citation

Sheila R. Messer, John Agzarian, and Derek Abbott "Optimal wavelet denoising for smart biomonitor systems", Proc. SPIE 4236, Smart Electronics and MEMS II, (16 March 2001); https://doi.org/10.1117/12.418781

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