Real-time separation of perfusion and oxygenation signals for an implantable sensor using adaptive filtering.
In this paper, an adaptive filtering algorithm to separate signals due to perfusion and oxygenation has been developed using an 810-nm source, in addition to 660-nm and 940-nm sources, as an internal reference due to its limited oxygen sensitivity. The newly developed algorithm was tested using Monte Carlo simulated data to prove the effectiveness of the 810-nm reference and adaptive algorithm. Following the simulation, an in vitro model was developed to test the algorithm that used a blood flow through system wrapped with tissue. The system had the ability to isolate the effects of perfusion and oxygenation and the algorithm accurately captured the changes in these signals with reliable consistency. Using the serosal surface of the swine jejunum, in vivo data was also taken to analyze the algorithms response to fluctuating perfusion levels like that seen in hemorrhaging or failing transplants. The algorithm was able to extract the perfusion information from the oxygenation information in this in vivo study. Overall, it was shown that an adaptive filtering algorithm using an 810-nm reference has provided a means to separate oxygenation and perfusion.
Subramanian
Hariharan
H
Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843-3120, USA. hariharan@tamu.edu
Ibey
Bennett L
BL
Xu
Weijian
W
Wilson
Mark A
MA
Ericson
M Nance
MN
Coté
Gerard L
GL
D000465:Algorithms; D000818:Animals; D001783:Blood Flow Velocity / Q000502:physiology*; D003199:Computer Systems; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D007583:Jejunum / Q000098:blood supply* / Q000502:physiology*; D010092:Oximetry / Q000379:methods*; D010100:Oxygen / Q000097:blood; D019736:Prostheses and Implants; D012815:Signal Processing, Computer-Assisted; D013552:Swine
D010100:Oxygen