title: A comparison of real-time performance of signal processing algorithms for minimum latency detection of hypovolemic States.
abstract: Algorithms for real-time ambulatory monitoring of physiological signals often run on platforms which have very limited processing power and memory. Therefore, in addition to functionality, it is necessary to carefully consider real-time performance requirements. This is particularly important for physiological monitoring of life threatening conditions such as hemorrhage. In this paper we present a comparison of several algorithms as candidates for implementation on a prehospital ambulatory monitor of hypovolemic states. The algorithms were tested on data from lower body negative pressure (LBNP) experiments that were used to simulate hypovolemic states. We also present a promising real-time wavelet algorithm for heart rate variability (HRV) processing in prehospital ambulatory monitoring applications.
authors.affiliation: Dept. of Electr. & Comput. Eng., Alabama Univ., Huntsville, AL, USA.
authors.forename: Emil
authors.initials: E
authors.lastname: Jovanov
authors.forename: Paul
authors.initials: P
authors.lastname: Cox
authors.forename: J Philip
authors.initials: JP
authors.lastname: Saul
authors.forename: Jose
authors.initials: J
authors.lastname: Salinas
authors.forename: Kathy L
authors.initials: KL
authors.lastname: Ryan
authors.forename: Victor A
authors.initials: VA
authors.lastname: Convertino
mesh_terms: D000465:Algorithms; D003199:Computer Systems; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D006339:Heart Rate; D006801:Humans; D020896:Hypovolemia / Q000175:diagnosis* / Q000503:physiopathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors