Empirical mode decomposition-discrete Hilbert transform based solution to detect decompression-induced gas bubble from Doppler ultrasound signal

Abstract

This paper concerns the detection of decompression-induced gas bubble from underwater construction workers Doppler ultrasound signal based on empirical mode decomposition (EMD), discrete Hilbert transform (DHT), and some parameters, which could be useful to detect gas bubble. EMD in combination with DHT is used to generate time-frequency-energy distribution and systolic phase is detected from that distribution. The properly detection of the systolic phase is the most important task to the detection of gas bubble. Time-varying mean frequency (TMF) is determined from instantaneous amplitude and instantaneous frequency. An algorithm is applied to extract some specific segments from TMF. Then the segments are considered as gas bubble on the basis of some parameters such as spreading in frequency, ratio of the gas bubble signal to the background signal, ratio of the gas bubble signal’s total energy to the background signal, and rising rate.