Home > Articles > Non-linear analysis of heart rate variability and its application to predict hypotension during spinal anesthesia for cesarean delivery
Resumen: A non-linear analysis of heart rate variability is carried out through two complexity measures (Correlation Dimension and Pointwise Correlation Dimension) and two regularity measures (Approximate Entropy and Sample Entropy) in order to predict hypotension episodes occurred during spinal anesthesia in cesarean delivery. These methods are applied to RR-interval series, during which woman adopts two alternative positions, one physiologically relaxed (PR) and one physiologically stressed (PS). Results show that women who developed hypotension have significantly higher (p-value = 0.05) complexity measures at PR position, (and significantly lower values for the PS position), than those who did not developed the disease. Regarding the regularity measures, women who developed hypotension have lower values, but not arriving to significance, during PS position than those who did not developed it, whereas those values remain almost constant for PR position. Idioma: Inglés Año: 2012 Publicado en: Computing in Cardiology 39 (2012), 413-416 ISSN: 2325-8861 Originalmente disponible en: Texto completo de la revista