Heart Rate Variability Analysis with the R package RHRV [electronic resource] / by Constantino Antonio García Martínez, Abraham Otero Quintana, Xosé A. Vila, María José Lado Touriño, Leandro Rodríguez-Liñares, Jesús María Rodríguez Presedo, Arturo José Méndez Penín.
Вид матеріалу:
Текст Серія: Use R!Публікація: Cham : Springer International Publishing : Imprint: Springer, 2017Видання: 1st ed. 2017Опис: XVI, 157 p. 50 illus., 29 illus. in color. online resourceТип вмісту: - text
- computer
- online resource
- 9783319653556
- Statistics
- Signal processing
- Image processing
- Speech processing systems
- Biostatistics
- Biomedical engineering
- Cardiology
- Cardiac imaging
- Statistics for Life Sciences, Medicine, Health Sciences
- Signal, Image and Speech Processing
- Biostatistics
- Biomedical Engineering and Bioengineering
- Cardiology
- Cardiac Imaging
- 519.5 23
- QA276-280
ЕКнига
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Springer Ebooks (2017 Network Access))
Foreword -- Preface -- 1 Introduction to Heart Rate Variability -- 2 Loading, Plotting and Filtering RR Intervals -- 3 Time Domain Analysis -- 4 Frequency Domain Analysis -- 5 Nonlinear and Fractal Analysis -- 6 Comparing HRV Variability across Different Segments of a Recording -- 7 Putting it All Together, a Practical Example -- A Installing RHRV -- B How do I Get a Series of RR Intervals from a Clinical/Biological Experiment?
This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques. Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in various disciplines such as biomedical engineering, human and veterinary medicine, biology, and pharmacy, as well as researchers conducting heart rate variability analyses on both human and animal data.
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