MACHINE LEARNING METHODS TO CONTROL MICROBUBBLE DYNAMICS

Abstract

Systems and methods for predicting and controlling bubble dynamics. The controller may comprise one or more processors. The controller may also comprise a machine learning model trained based on bubble acoustic emission data. The controller may also comprise at least one memory in communication with the controller and the machine learning model and storing computer program code. The computer program code may cause the controller to monitor acoustic emission levels of one or more bubbles in a body of a subject. The computer program code may further cause the controller to predict at least one acoustic emission level indicative of a collapse of the one or more bubbles. The computer program code may also cause the controller to cause an acoustic transducer to emit acoustic energy based at least in part on the at least one predicted acoustic emission level indicative of the collapse of the one or more bubbles.

CPC Classifications