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Vibroacoustic signals generated by the interaction of moving clinical devices, e.g. an aspiration or biopsy needle, with different tissues creates a distinct signal. These signals can be received via a dedicated audio sensor and subsequently analysed with the potential to provide information about location, tissue characterisation, and event classification. With that it could also be used as an additional and complementary guidance tool particularly for future robotic assisted procedures. In our laboratory research we used different phantoms with animal and artificial tissues, audio pre-processing, and subsequent training and optimisation of a ResNet model with a tissue event detection F1 score of 95.3% when compared to video based annotation tool. This result is very encouraging, as several possible improvements have been identified that will be implemented in the next research steps together with a robot assisted insertion and an automatic video annotation algorithm.