Nonlinear time scaling and cyclostationary signal processing can theoretically and experimentally recover heart sounds in the presence of additive noise and disturbance.
A novel signal processing technique using nonlinear time scaling effectively reduces noise and disturbance in heart sound recordings.
Through an investigation of various clinical cases, heart sounds are found to be quasi-cyclostationary. Nonlinear time scaling from cycle-to-cycle is proposed to enhance cyclic stationarity, where nonlinear time scaling is approximated by a piecewise linear function. The techniques of cyclostationary signal processing are employed in this paper to reduce noise and disturbance in the cycle-frequency domain. Heart sounds can be theoretically recovered in the presence of additive, zero mean noise, and disturbance (perhaps non-Gaussian, nonstationary, or colored). The experimental tests in various conditions confirm the theoretical results.
Tang et al. (Fri,) conducted a other in Heart sounds (noise reduction). Nonlinear time scaling and cyclostationary signal processing was evaluated on Noise and disturbance reduction in heart sounds. Nonlinear time scaling and cyclostationary signal processing can theoretically and experimentally recover heart sounds in the presence of additive noise and disturbance.
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