Objective To develop a computerised system that will assist the early diagnosis of fetal hypoxia and to investigate the relationship between the fetal heart rate variability and the fetal pulse oximetry recordings. Design Retrospective off-line analysis of cardiotocogram and FSpO 2 recordings.Setting The Maternity Unit of the 2nd Department of Obstetrics and Gynaecology, Aretaieion Hospital, University of Athens. Population Sixty-one women of more than 37 weeks of gestation were monitored throughout labour.Methods Multiresolution wavelet analysis was applied in each 10-minute period of second stage of labour focussing on long term variability changes in different frequency ranges and statistical analysis was performed in the associated 10-minute FSpO 2 recordings. Self-organising map neural network was used to categorise the different 10-minute fetal heart rate patterns and the associated 10-minute FSpO 2 recordings. Main outcome measures Umbilical artery pH of 7.20 and Apgar score at 5 minutes of 7 formed the inclusion criteria of the risk group. Results After using k-means clustering algorithm, the two-dimensional output layer of the self-organising map neural network was divided into three distinct clusters. All the cases that mapped in cluster 3 belonged in the risk group except one. The sensitivity of the system was 83.3% and the specificity 97.9% for the detection of risk group cases. Conclusions A relationship between the fetal heart rate variability in different frequency ranges and the time in which FSpO 2 is less than 30% was noticed. Fetal pulse oximetry seems to be an important additional source of information. Computerised analysis of the fetal heart rate monitoring and pulse oximetry recordings is a promising technique in objective intrapartum diagnosis of fetal hypoxia. Further evaluation of this technique is mandatory to evaluate its efficacy and reliability in interpreting fetal heart rate recordings.

ABSTRACT:The data on trends in semen quality are conflicting and sensitive to geographical variations. Although previous British surveys on semen quality indicate a decline, the northeast of Scotland has never been included in these surveys. This is an area with low out migration rates where andrology services for a population of 500 000 are centralized within a single laboratory, thus providing a unique opportunity to study population-based trends in semen quality over time. We investigated trends in semen parameters between 1994-2005, in a cohort of 4832 men attending for routine semen analysis at the Aberdeen Fertility Centre who had a sperm density of greater than 20 million per mL. The main outcome measures were trends in sperm density, sperm motility and motile density in the first semen sample. Linear regression and time series analysis were used to examine trends over time in the semen parameters. The mean and standard deviation (SD) age of all men (n 5 5204) in the study was 34 (6) years. The median (inter quartile range) for sperm density and motile density for the study population were 61 (40-91) million/mL and 99 (47-181) millon. The mean (SD) sperm motility was 49 (19)%. Among 4832 men (with sperm count .20 million per mL), data adjusted for age and period of abstinence showed a decreasing trend for sperm density over time, R 2 5 0.45 (P 5 .017). There was no such trend in sperm motility and motile density. However, this trend has to be interpreted with caution due to fluctuations in semen parameters, population bias and the retrospective nature of the analysis.

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Computerized FHR and FSPO2 monitoring shows an excellent efficacy and reliability in interpreting non-reassuring FHR recordings.