Machine learning techniques and algorithms originally developed for use in the field of robotics can be applied to continuous, noninvasive physiological waveform data to discover hidden, hemodynamic relationships. Newly developed algorithms can, in real-time: 1) predict cardiovascular collapse well ahead of any clinically significant changes in standard vital signs, 2) monitor and estimate fluid resuscitation needs, 3) estimate acute blood loss volume, and 4) estimate intracranial pressure. The investigators hypothesize that these same methods can be used to predict functional hypovolemia during regional anesthesia for labor or fetal intervention.
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effective intravascular volume loss during maternal regional anesthesia
Timeframe: during epidural, 1-4 hours