Aplicación de la variabilidad de la frecuencia cardiaca al control del entrenamiento deportivo: Análisis en modo frecuencia
Year: 2013
Type: article
Abstract: Biological signals are often used as a tool for the control and evaluation of the training loads or for the evaluation of the acute and chronic effects in the organism of athletes. The Heart Rate is still considered nowadays as the most popular of load indicators among athletes and coaches. Every single individual, in rest conditions, has a natural rhythm but unlike we might think, is far from stable. This is an exceptional circumstance for the application in the athletic training. These variations are known as Heart Rate Variability. The Heart Rate depends directly on autonomic or vegetative nervous system. In turn, it influences on several functions of the organism, training loads evaluation and in the acute and chronic effects produced in the organism of the athlete. The control of this parameter depends on a high number of factors, internals and externals, which vary significantly throughout the exercise time or in situations where the body alters normal operating situation. Thus, we can observe that during exercise the sympathetic -vagal balance is dependent of the intensity and duration of the exercise. Some authors suggest that up 50% VO 2max approximately, HRV changes are mainly due to the decreased parasympathetic discharge accompanied by a progressive increase of the sympathetic influence. Above this intensity, HR and its oscillations are primarily influenced by sympathetic activity. In these situations, HR oscillations are also dependents of two oscillatory processes which work as feedback mechanism: breathing (Respiratory sinus arrhythmia) and blood pressure (baroreflex influence). These mechanisms, assessment, methodology and control tools are the issues we will discuss in this review.
Authors: García Manso, Juan Manuel
Language: Spanish
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W11317291
