Heart Rate Variability (HRV) Signal Analysis : Clinical Applications

Open a Window into the Autonomic Nervous System Quantifying the amount of autonomic nervous system activity in an individual patient can be extremely important, because it provides a gauge of disease severity in a large number of diseases. Heart rate variability (HRV) calculated from both short-term and longer-term electrocardiograms is an ideal window into such autonomic activity for two reasons: one, heart rate is sensitive to autonomic activity in the entire body, and two, recording electrocardiograms is inexpensive and non-invasive unlike other techniques currently available for autonomic assessment, such as microneurography and metaiodobenzylguanidine (MIBG) scanning. Heart Rate Variability (HRV) Signal Analysis: Clinical Applications provides a comprehensive review of three major aspects of HRV: mechanism, technique, and clinical applications. Learn Techniques for HRV Signal Analysis Edited by an engineer, a cardiologist, and a neurologist, and featuring contributions by widely published international researchers, this interdisciplinary book begins by reviewing the many signal processing techniques developed to extract autonomic activity information embedded in heart-rate records. The classical time and frequency domain measures, baroreceptor sensitivity, and newer non-linear measures of HRV are described with a fair amount of mathematical detail with the biomedical engineer and mathematically oriented physician in mind. The book also covers two recent HRV methods, heart-rate turbulence and phase-rectified signal averaging. Use of HRV in Clinical Care The large clinical section is a must-read for clinicians and engineers wishing to get an insight into how HRV is applied in medicine. Nineteen chapters altogether are devoted to uses of HRV in: Monitoring—for example to predict potential complications in pregnancies, fetal distress, and in neonatal critical care Acute care—for gauging the depth of anesthesia during surgery and predicting change in patient status