title: Predicting acute hypotensive episodes based on HR baroreflex model estimation.
abstract: A new method to predict acute hypotensive episodes (AHE) is proposed in this paper. The AHE is defined as any period of 30 min or more during which at least 90% of mean arterial pressure (MAP) measurements are below 60 mmHg. Since arterial pressure has a direct correlation with heart rate through heart rate (HR) baroreflex and cardiovascular systems, any changes in MAP, directly affect HR and vice versa. Predicting HR using our developed model, the periods in which HR drops to the values less than 40 beat/min are detected. The demonstrated AHE data for twenty patients are picked to validate the proposed algorithm. Results show that the proposed method could truly predict occurrence of the AHE in 17 out of 20 cases analyzed. Results show reliable accuracy in predicting AHE in these patients.
authors.affiliation: Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran.
authors.forename: A
authors.initials: A
authors.lastname: Ghaffari
authors.forename: A
authors.initials: A
authors.lastname: Jalali
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D017704:Baroreflex; D001794:Blood Pressure; D001795:Blood Pressure Determination / Q000379:methods; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006339:Heart Rate; D006801:Humans; D007022:Hypotension / Q000175:diagnosis* / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity