主催: The Japan Society of Mechanical Engineers
会議名: ロボティクス・メカトロニクス 講演会2020
開催日: 2020/05/27 - 2020/05/30
Quantitative wound data is essential to support objective wound assessment, and it can contribute to the improvement of wound management. This study developed a system that estimates the depth and classifies the different tissue types simultaneously and continuously using impedance data from the skin. The system uses 50 frequency spectroscopy and 8 direction tomography to obtain two-dimensional area data. To confirm the validity of the estimation and classification we used meat phantoms with a hole or different tissues or both, and the accuracy was calculated for small 200 regions in the skin area surrounded by the sensor system. The system showed 76.0% accuracy for the depth estimation and 87.0% accuracy for the tissue classification. The study confirmed the possibility of simultaneous depth estimation and tissue classification, and further study is required to validate the wound assessment.