Multimodal Porcine Electrosurgical Impact Sensing. Sus scrofa domesticus

This dataset contains sensor measurements acquired during electrosurgical operation on a cohort of in vivo porcine specimens. Raw data is available on the Illinois Data Bank, accessible with DOI link https://doi.org/10.13012/B2IDB-7506134_V1 . The main purpose of this dataset is to allow for modeling of electrosurgical processes on live tissues, with the primary goal of modeling the underlying mechanisms governing of electrosurgery. The dataset contains both manual (surgeon-operated) cuts, as well as cuts effectuated by a robotic arm with pose records. Several different electrosurgical modes are included, including pure cutting, blend, and coagulation modes. Potential applications of this dataset include: - Assessment and modeling of tissue damage due to electrosurgical action; - Modeling of thermal propagation due to electrosurgical action; - Tissue segmentation based on discoloration during electrosurgical action. A number of sensing modalities have been used (note that not all sensing modalities are available for each porcine specimen): - Visual imaging using an Intel RealSense D405 sensor; - Depth imaging using an Intel RealSense L515 LIDAR sensor, or stereoscopic depth measurements using an Intel RealSense D405 sensor; - Thermography using Optris Xi 400 thermographers, and FLIR Lepton 3.5 sensors; - Voltage and current sensing. Porcine trials have been performed on a cohort of juvenile Landrace pigs, in accordance with the Animal Care Policies and Procedures of the University of Illinois at Chicago.