Bone Cement Removal with Audio-Monitoring and Erosion Depth

This dataset comprises extensive multi-modal data related to the experimental study of ultrasonically excited pulsating fluid jets used for bone cement removal. Conducted at the Institute of Geonics, Ostrava, Czech Republic, the study explores the effect of varying standoff distances on erosion profiles, under controlled parameters including a fixed nozzle diameter, sonotrode frequency, supply pressure, and robot arm velocity. The dataset includes numerical data representing ablation profiles, captured as a large CSV file, and audio recordings captured using a high-resolution microphone. Ablation profiles are measured at standoff distances that span several discrete lengths, ensuring diverse sample conditions. The audio data derives from high-fidelity recordings at a 38.4 kHz sampling rate in .wav format, capturing the fluid jet's impact sounds as it interacts initially with a metal plate and subsequently with the bone cement. This audio information was processed into Mel Spectrograms, which efficiently capture the frequency distribution crucial for predictive analysis. The dataset is organized into training and testing subsets, with the initial portions used to train predictive models leveraging Mel Spectrogram inputs to predict erosion profiles. This dataset offers insights into the dynamic interactions between a pulsating fluid jet and target materials, providing a foundation for predictive modeling in non-invasive surgical procedures.

本数据集涵盖了与超声波激发脉动流体射流在骨水泥去除实验研究中广泛的多模态数据。该研究由捷克共和国奥斯特拉瓦的地球物理研究所开展，旨在探究不同 standoff 距离对侵蚀轮廓的影响，研究过程中控制了包括固定喷嘴直径、声换能器频率、供应压力和机器人臂速度在内的参数。数据集包括代表消融轮廓的数值数据，以大型 CSV 文件形式捕获，以及使用高分辨率麦克风录制的音频记录。消融轮廓在跨越数个离散长度的 standoff 距离处进行测量，以确保多样化的样本条件。音频数据来源于 38.4 kHz 采样率的高保真录音，以 .wav 格式捕捉流体射流与金属板及骨水泥相互作用时的冲击声音。该音频信息被处理成梅尔频谱图，有效地捕捉了预测分析中至关重要的频率分布。数据集被组织为训练集和测试集，其中初始部分用于训练预测模型，利用梅尔频谱图输入来预测侵蚀轮廓。本数据集揭示了脉动流体射流与目标材料之间的动态相互作用，为非侵入性手术中的预测建模奠定了基础。