This study confirmed that heavy training shifted the cardiac autonomic balance toward a predominance of the sympathetic over the parasympathetic drive. When recorded during the night, heart rate variability appeared to be a better tool than resting heart rate to evaluate cumulated physical fatigue, as it magnified the induced changes in autonomic nervous system activity. These results could be of interest for optimizing individual training profiles.

Background-Enhanced nocturnal heart rate variability (HRV) has been evoked in sleep-related breathing disorders. However, its capacity to detect obstructive sleep apnea syndrome (OSAS) has not been systematically determined. Thus, we evaluated the discriminant power of HRV parameters in a first group of patients (G1) and validated their discriminant capacity in a second group (G2

Heart rate variability is a recognized parameter for assessing autonomous nervous system activity. Fourier transform, the most commonly used method to analyze variability, does not offer an easy assessment of its dynamics because of limitations inherent in its stationary hypothesis. Conversely, wavelet transform allows analysis of nonstationary signals. We compared the respective yields of Fourier and wavelet transforms in analyzing heart rate variability during dynamic changes in autonomous nervous system balance induced by atropine and propranolol. Fourier and wavelet transforms were applied to sequences of heart rate intervals in six subjects receiving increasing doses of atropine and propranolol. At the lowest doses of atropine administered, heart rate variability increased, followed by a progressive decrease with higher doses. With the first dose of propranolol, there was a significant increase in heart rate variability, which progressively disappeared after the last dose. Wavelet transform gave significantly better quantitative analysis of heart rate variability than did Fourier transform during autonomous nervous system adaptations induced by both agents and provided novel temporally localized information.

Autonomic nervous system status depends on cumulated physical fatigue due to increased training loads. Therefore, heart rate variability analysis appears to be an appropriate tool to monitor the effects of physical training loads on performance and fitness, and could eventually be used to prevent overtraining states.

Since the pioneering studies of the 1960s, heart rate variability (HRV) has become an increasingly used non-invasive tool for examining cardiac autonomic functions and dysfunctions in various populations and conditions. Many calculation methods have been developed to address these issues, each with their strengths and weaknesses. Although, its interpretation may remain difficult, this technique provides, from a non-invasive approach, reliable physiological information that was previously inaccessible, in many fields including death and health prediction, training and overtraining, cardiac and respiratory rehabilitation, sleep-disordered breathing, large cohort follow-ups, children's autonomic status, anesthesia, or neurophysiological studies. In this context, we developed HRVanalysis, a software to analyse HRV, used and improved for over 20 years and, thus, designed to meet laboratory requirements. The main strength of HRVanalysis is its wide application scope. In addition to standard analysis over short and long periods of RR intervals, the software allows time-frequency analysis using wavelet transform as well as analysis of autonomic nervous system status on surrounding scored events and on preselected labeled areas. Moreover, the interface is designed for easy study of large cohorts, including batch mode signal processing to avoid running repetitive operations. Results are displayed as figures or saved in TXT files directly employable in statistical softwares. Recordings can arise from RR or EKG files of different types such as cardiofrequencemeters, holters EKG, polygraphs, and data acquisition systems. HRVanalysis can be downloaded freely from the Web page at: https://anslabtools.univ-st-etienne.fr HRVanalysis is meticulously maintained and developed for in-house laboratory use. In this article, after a brief description of the context, we present an overall view of HRV analysis and we describe the methodological approach of the different techniques provided by the software.

Intensive endurance training in elderly men enhanced parasympathetic parameters of HRV and, interestingly, of SBR. Physiological mechanisms and long-term clinical effects on health status should be further investigated.

The impact of undiagnosed SRBD on cognitive function appeared quite limited in a generally older healthy population, and only slightly affected severe cases. The implication of undiagnosed SRBD on the cognitive impairment in elderly subjects remains hypothetical and needs to be prospectively studied.

Performance is correlated with nocturnal ANS activity at an individual level. The decrease in ANS activity during intensive training is correlated with the loss in performance, and the rebound in ANS activity during tapering tracks with the gain in performance. Interestingly, the speed of the rebound during the tapering period was quite different between swimmers. ANS activity measurement may be useful to design and control individual training periods and to optimize the duration of tapering.