A Comparison of Real-Time Performance of Signal Processing Algorithms for Minimum Latency Detection of Hypovolemic States

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