TY - GEN
T1 - Blood vessel detection using skin impedance tomography and spectroscopy
AU - Kang, Sooin
AU - Mori, Taketoshi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Blood vessel detection is an essential method in a non-invasive circulatory monitoring system. However, only using camera-based image processing for finding a vein has many limitations due to the complexity of underneath tissue. Impedance tomography and spectroscopy can collect electrical characteristics map of the biological tissue precisely. The study developed instrumentation to measure the impedance with eight small electrodes, which can observe near vein area and show the conductivity map with small patches using tomographic reconstruction. The study examined the cephalic vein of a healthy human arm to confirm the feasibility of vein location recognition. The system could perform 86.8% pixel accuracy and achieve a mIoU score of 63.7% for vessel location segmentation in 5cm2 area observation. The system could identify a human blood vessel's electrical characteristic and visualize the passage.Clinical Relevance-This approach will support intravascular therapy by identifying the vessel location automatically and providing information to the vessel monitoring system in backend. In addition, the system would allow efficient data entry into the electronic medical record for management of hospitalized patients.
AB - Blood vessel detection is an essential method in a non-invasive circulatory monitoring system. However, only using camera-based image processing for finding a vein has many limitations due to the complexity of underneath tissue. Impedance tomography and spectroscopy can collect electrical characteristics map of the biological tissue precisely. The study developed instrumentation to measure the impedance with eight small electrodes, which can observe near vein area and show the conductivity map with small patches using tomographic reconstruction. The study examined the cephalic vein of a healthy human arm to confirm the feasibility of vein location recognition. The system could perform 86.8% pixel accuracy and achieve a mIoU score of 63.7% for vessel location segmentation in 5cm2 area observation. The system could identify a human blood vessel's electrical characteristic and visualize the passage.Clinical Relevance-This approach will support intravascular therapy by identifying the vessel location automatically and providing information to the vessel monitoring system in backend. In addition, the system would allow efficient data entry into the electronic medical record for management of hospitalized patients.
UR - http://www.scopus.com/inward/record.url?scp=85179637815&partnerID=8YFLogxK
U2 - 10.1109/EMBC40787.2023.10340703
DO - 10.1109/EMBC40787.2023.10340703
M3 - Conference contribution
C2 - 38082762
AN - SCOPUS:85179637815
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
BT - 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023
Y2 - 24 July 2023 through 27 July 2023
ER -