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Surgical audio information as base for haptic feedback in robotic-assisted procedures

Alfredo Illanes, Anna Schaufler, Thomas Sühn, Axel Boese, Roland S. Croner, Michael Friebe

Year
2020
Citations
11
Access
Open access

Abstract

Abstract This work aims to demonstrate the feasibility that haptic information can be acquired from a da Vinci robotic tool using audio sensing according to sensor placement requirements in a real clinical scenario. For that, two potential audio sensor locations were studied using an experimental setup for performing, in a repeatable way, interactions of a da Vinci forceps with three different tissues. The obtained audio signals were assessed in terms of their resulting signal-to-noise-ratio (SNR) and their capability to distinguish between different tissues. A spectral energy distribution analysis using Discrete Wavelet Transformation was performed to extract signal signatures from the tested tissues. Results show that a high SNR was obtained in most of the audio recordings acquired from both studied positions. Additionally, evident spectral energy-related patterns could be extracted from the audio signals allowing us to distinguish between different palpated tissues.

Keywords

Computer scienceHaptic technologyArtificial intelligenceAudio signalSIGNAL (programming language)Energy (signal processing)RobotNoise (video)WaveletComputer vision

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