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Automatic hardware for time-specified sampling is here combined with a set of software modules for signal processing by periodic regression in order to assess the extent of blood pressure variability within a day in ordinary conditions. The predictable variability thus identified can be used in screening and prevention as well as for diagnosis and cure.1
Predictable changes with several frequencies and trends are here quantified by least-squares fitting in blood pressure and heart rate automatically monitored throughout two consecutive pregnancies of a clinically healthy woman. This complex time-structure of blood pressure offers new endpoints as reference standards for an early identification of gestational hypertension or even pre-eclampsia.1
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