Saavedra Ruiz, Andrés

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    Digital signal analysis for detection of air bubbles on artificial thigh vessels
    (2015) Saavedra Ruiz, Andrés; León Colón, Leyda V.; College of Engineering; Morales, Lizdabel; Cancelos, Silvina; Department of Electrical and Computer Engineering; Sundaram, Paul A.
    Decompression sickness (DCS) occurs when divers rise to the surface exposing the body to sudden changes in pressure, generating nitrogen bubbles in tissues, causing serious bodily injury and even death. To prevent this risk, tables indicating divers’ ascent rates, descent rates, and waiting time in between decompression stops have been developed. Even with the help of such tables, decompression sickness still occurs in individuals who follow the instructions in dive tables. Therefore, prevention of DCS may be viable with a method that detects the presence of bubbles in real time. II In this thesis, we show a new method for bubble detection using a simplified human thigh prototype constructed with a piezoelectric ring (PZT) placed around it. In order to test this new method, we use two high-speed cameras, to record the bubbles produced in a bubble generator system, and pill microphones (PM) to measure disturbances in the prototype when it is in resonance. The electrical signals from the piezoelectric ring (PZT) and microphones (PM) are the inputs to a pattern recognition algorithm. In the classification stage of the pattern recognition, three classifiers are tested; the choice of classifiers are determined by the best accuracy. A neural network based classifier performed the best detection of bubbles for five classes of different diameter ranges. The detection accuracy was 98%.