Title :
Prediction of Intradialytic Hypotension Using Photoplethysmography
Author :
Solem, Kristian ; Olde, Bo ; Sörnmo, Leif
Author_Institution :
Dept. of Electr. & Inf. Technol., Lund Univ., Lund, Sweden
fDate :
7/1/2010 12:00:00 AM
Abstract :
Intradialytic hypotension is the most common acute complication during conventional hemodialysis treatment. Prediction of such events is highly desirable in clinical routine for prevention. This paper presents a novel prediction method of acute symptomatic hypotension in which the photoplethysmographic signal is analyzed with respect to changes in amplitude, reflecting vasoconstriction, and cardiac output. The method is based on a statistical model in which the noise is assumed to have Laplacian amplitude distribution. The performance is evaluated on 11 hypotension-prone patients who underwent hemodialysis treatment, resulting in seven events with acute symptomatic hypotension and 17 without. The photoplethysmographic signal was continuously acquired during treatment as was information on blood pressure and oxygen saturation. Using leave-one-out cross validation, the proposed method predicted six out of seven hypotensive events, while producing 1 false prediction out of 17 possible. The performance was achieved when the prediction threshold was chosen to be in the range 57%-65% of the photoplethysmographic envelope at treatment onset.
Keywords :
biomedical optical imaging; haemodynamics; medical disorders; medical signal processing; patient treatment; plethysmography; Laplacian amplitude distribution; acute symptomatic hypotension; blood pressure; cardiac output; conventional hemodialysis treatment; intradialytic hypotension; leave-one-out cross validation; oxygen saturation; photoplethysmography; vasoconstriction; Hemodialysis; intradialytic hypotension; pulse oximetry; signal processing; vasoconstriction; Aged; Aged, 80 and over; Algorithms; Female; Humans; Hypotension; Male; Middle Aged; Models, Statistical; Photoplethysmography; Predictive Value of Tests; Renal Dialysis; Reproducibility of Results; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2010.2042170