The performances of eight currently available computerized pulse-detection algorithms were compared on signal-free noise and physiological luteinizing hormone (LH) time series. Signal-free noise was made to vary from 4 to 36% for Gaussian and empirical distributions. Physiological LH data were obtained by immunoassay of blood samples withdrawn every 5 min for 24 h in 8 healthy men, so that the data sets could be emended to simulate varying sampling intensities. Whenever possible, programs were tested at a presumptive 1% false-positive rate. In relation to signal-free noise, the Santen and Bardin program and its modification manifested elevated false-positive rates when the intraseries coefficients of variation increased. The Regional Dual-Threshold program yielded a 1% false-positive rate except on simulated series with high variance. The Cluster and Detect programs both approximated a 1% false-positive rate and the Ultra program approximated a 2.3% false-positive rate throughout the entire range of variance tested. In regard to physiological LH data, all algorithsm disclosed a significant impact of sampling intensity on estimates of LH pulse frequency. Sampling-intensity dependent estimates of LH peak frequency by three of the eight programs (Ultra, Cluster, and Detect) were statistically indistinguishable from each other but distinct from the five other programs tested. Furthermore, when judged in relation to their ability to identify individual peaks, the three congruent programs were minimally distinguishable (McNemar's test). Rather, these programs identified the same particular peaks (as defined by concordance of peak maxima) at least 72% of the time.
|Original language||English (US)|
|Journal||American Journal of Physiology - Endocrinology and Metabolism|
|State||Published - Jan 1 1988|
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Physiology (medical)