Effects of increased training load on vagal-related indexes of heart rate variability: a novel sleep approach

2004 ◽  
Vol 287 (6) ◽  
pp. H2813-H2818 ◽  
Author(s):  
M. Buchheit ◽  
C. Simon ◽  
F. Piquard ◽  
J. Ehrhart ◽  
G. Brandenberger
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Slow Wave Sleep ◽  
Training Load ◽  
Vagal Activity ◽  
Lower Heart Rate ◽  
Sleep Parameters ◽  
Recording Conditions ◽  
Young Subjects ◽  
Better Than

There is little doubt that moderate training improves cardiac vagal activity and thus has a cardioprotective effect against lethal arrhythmias. Our purpose was to learn whether a higher training load would further increase this beneficial effect. Cardiac autonomic control was inferred from heart rate variability (HRV) and analyzed in three groups of young subjects (24.5 ± 3.0 yr) with different training states in a period free of stressful stimuli or overload. HRV was analyzed in 5-min segments during slow-wave sleep (SWS, a parasympathetic state that offers high electrocardiographic stationarity) and compared with data collected during quiet waking periods in the morning. Sleep parameters, fatigue, and stress levels checked by questionnaire were identical for all three groups with no signs of overtraining in the highly trained (HT) participants. During SWS, a significant ( P < 0.05) increase in absolute and normalized vagal-related HRV indexes was observed in moderately trained (MT) individuals compared with sedentary (Sed) subjects; this increase did not persist in HT athletes. During waking periods, most of the absolute HRV indexes indistinctly increased in MT individuals compared with controls ( P < 0.05) but did not increase in HT athletes. Normalized spectral HRV indexes did not change significantly among the three groups. Heart rate was similar for MT and Sed subjects but was significantly ( P < 0.05) lower in HT athletes under both recording conditions. These results indicate that SWS discriminates the state of sympathovagal balance better than waking periods. A moderate training load is sufficient to increase vagal-related HRV indexes. However, in HT individuals, despite lower heart rate, vagal-related HRV indexes return to Sed values even in the absence of competition, fatigue, or overload.

scholarly journals On the Variability of Heart Rate Variability—Evidence from Prospective Study of Healthy Young College Students

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1302
Author(s):  
Xingran Cui ◽  
Leirong Tian ◽  
Zhengwen Li ◽  
Zikai Ren ◽  
Keyang Zha ◽  
...  
Keyword(s):  
College Students ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Daily Activities ◽  
Recording Time ◽  
Detection Algorithms ◽  
Multi Scale ◽  
Gender Influence ◽  
Recording Conditions ◽  
Young Subjects

Heart rate variability (HRV) has been widely used as indices for autonomic regulation, including linear analyses, entropy and multi-scale entropy based nonlinear analyses, and however, it is strongly influenced by the conditions under which the signal is being recorded. To investigate the variability of healthy HRV under different settings, we recorded electrocardiograph (ECG) signals from 56 healthy young college students (20 h for each participant) at campus using wearable single-lead ECG device. Accurate R peak to R peak (RR) intervals were extracted by combing the advantages of five commonly used R-peak detection algorithms to eliminate data quality influence. Thorough and detailed linear and nonlinear HRV analyses were performed. Variability of HRV metrics were evaluated from five categories: (1) different states of daily activities; (2) different recording time period in the same day during free-running daily activities; (3) body postures of sitting and lying; (4) lying on the left, right and back; and (5) gender influence. For most of the analyzed HRV metrics, significant differences (p < 0.05) were found among different recording conditions within the five categories except lying on different positions. Results suggested that the standardization of ECG data collection and HRV analysis should be implemented in HRV related studies, especially for entropy and multi-scale entropy based analyses. Furthermore, this preliminary study provides reference values of HRV indices under various recording conditions of healthy young subjects that could be useful information for different applications (e.g., health monitoring and management).

scholarly journals How to Use Heart Rate Variability: Quantification of Vagal Activity in Toddlers and Adults in Long-Term ECG

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5959
Author(s):  
Helmut Karl Lackner ◽  
Marina Tanja Waltraud Eglmaier ◽  
Sigrid Hackl-Wimmer ◽  
Manuela Paechter ◽  
Christian Rominger ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Time Domain ◽  
Wearable Sensors ◽  
Vagal Activity ◽  
Activity Levels ◽  
Frequency Bands ◽  
Recording Conditions

Recent developments in noninvasive electrocardiogram (ECG) monitoring with small, wearable sensors open the opportunity to record high-quality ECG over many hours in an easy and non-burdening way. However, while their recording has been tremendously simplified, the interpretation of heart rate variability (HRV) data is a more delicate matter. The aim of this paper is to supply detailed methodological discussion and new data material in order to provide a helpful notice of HRV monitoring issues depending on recording conditions and study populations. Special consideration is given to the monitoring over long periods, across periods with different levels of activity, and in adults versus children. Specifically, the paper aims at making users aware of neglected methodological limitations and at providing substantiated recommendations for the selection of appropriate HRV variables and their interpretation. To this end, 30-h HRV data of 48 healthy adults (18–40 years) and 47 healthy toddlers (16–37 months) were analyzed in detail. Time-domain, frequency-domain, and nonlinear HRV variables were calculated after strict signal preprocessing, using six different high-frequency band definitions including frequency bands dynamically adjusted for the individual respiration rate. The major conclusion of the in-depth analyses is that for most applications that implicate long-term monitoring across varying circumstances and activity levels in healthy individuals, the time-domain variables are adequate to gain an impression of an individual’s HRV and, thus, the dynamic adaptation of an organism’s behavior in response to the ever-changing demands of daily life. The sound selection and interpretation of frequency-domain variables requires considerably more consideration of physiological and mathematical principles. For those who prefer using frequency-domain variables, the paper provides detailed guidance and recommendations for the definition of appropriate frequency bands in compliance with their specific recording conditions and study populations.

scholarly journals Increase in perceived stress is correlated to lower heart rate variability in healthy young subjects

2015 ◽  
Vol 37 (1) ◽  
pp. 7 ◽  
Author(s):  
Ana Gabriela Câmara Batista da Silva ◽  
Diego Neves Araujo ◽  
Amanda Caroline Muñoz Costa ◽  
Bruna Alice Lima Dias ◽  
Guilherme Augusto de Freitas Fregonezi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Perceived Stress ◽  
Lower Heart Rate ◽  
Young Subjects

scholarly journals Direct measurement of vagal tone in rats does not show correlation to HRV

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joseph T. Marmerstein ◽  
Grant A. McCallum ◽  
Dominique M. Durand
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Neural Activity ◽  
Vagal Tone ◽  
Neural Recording ◽  
The Body ◽  
Autonomic Nerve ◽  
Vagal Activity ◽  
Recording Technology

AbstractThe vagus nerve is the largest autonomic nerve, innervating nearly every organ in the body. “Vagal tone” is a clinical measure believed to indicate overall levels of vagal activity, but is measured indirectly through the heart rate variability (HRV). Abnormal HRV has been associated with many severe conditions such as diabetes, heart failure, and hypertension. However, vagal tone has never been directly measured, leading to disagreements in its interpretation and influencing the effectiveness of vagal therapies. Using custom carbon nanotube yarn electrodes, we were able to chronically record neural activity from the left cervical vagus in both anesthetized and non-anesthetized rats. Here we show that tonic vagal activity does not correlate with common HRV metrics with or without anesthesia. Although we found that average vagal activity is increased during inspiration compared to expiration, this respiratory-linked signal was not correlated with HRV either. These results represent a clear advance in neural recording technology but also point to the need for a re-interpretation of the link between HRV and “vagal tone”.

scholarly journals Heart Rate Variability, Time Estimation and Internet-Dependent Behaviour in 16–17-Year-Old Adolescents: A Study in Russian Arctic

Life ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 497
Author(s):  
Olga Krivonogova ◽  
Elena Krivonogova ◽  
Liliya Poskotinova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Internet Addiction ◽  
Internet Use ◽  
Time Estimation ◽  
Vagal Activity ◽  
Russian Arctic ◽  
Severe Withdrawal ◽  
Dependent Behaviour ◽  
Nenets Autonomous

Internet-dependent behaviour in adolescents can contribute to a change in the function of the nervous system, which is reflected in the violation of time perception and autonomic regulation of the heart rate. The aim of the study was to determine groups of individuals with different risks of Internet addiction (IA) in relation to heart rate variability (HRV) parameters and the efficiency of time estimation in adolescents aged 16–17 years living in the Russian Arctic. Adolescents aged 16–17 years (n = 49–32 females, 17 males) living in Yamalo-Nenets Autonomous Okrug (Russia) were observed. Chen Scale Internet Addiction (CIAS) was used. The duration of an individual 1 min was determined. HRV parameters were determined using the "Varicard" equipment (Russia). In 16–17-year-old adolescents with different levels of risk of developing IA, including signs of IA, we revealed a high severity of symptoms of withdrawal from Internet use, difficulty in time estimation against the background of sympathicotonia and a decrease in vagal regulation of heart rate. In individuals with minimal symptoms of withdrawal from Internet use, the total HRV and vagal activity remain higher than in those with severe withdrawal symptoms, and their time estimation remains effective.

Effects of mobile phone radiation on heart rate variability of healthy young subjects

2015 ◽  
Vol 2 (1) ◽  
pp. 23
Author(s):  
AnupM Vegad ◽  
YogeshK Kacha ◽  
HemantB Mehta ◽  
ChinmayJ Shah ◽  
MaulikS Varu
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Mobile Phone ◽  
Young Subjects ◽  
Mobile Phone Radiation

scholarly journals Heart Rate Variability Responses to a Training Cycle in Female Youth Rowers

2020 ◽  
Vol 17 (22) ◽  
pp. 8391
Author(s):  
Rohan Edmonds ◽  
Julian Egan-Shuttler ◽  
Stephen J. Ives
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Cardiac Autonomic Function ◽  
Female Youth ◽  
Training Cycle ◽  
And Training

Heart rate variability (HRV) is a reputable estimate of cardiac autonomic function used across multiple athletic populations to document the cardiac autonomic responses to sport demands. However, there is a knowledge gap of HRV responses in female youth rowers. Thus, the purpose of this study was to measure HRV weekly, over a 15-week training period, covering pre-season and up to competition in youth female rowers, in order to understand the physiological response to long-term training and discern how fluctuations in HRV may relate to performance in this population. Measures of heart rate and heart rate variability were recorded before training each Friday over the monitoring period in seven athletes. Analysis of heart rate variability focused on time domain indices, the standard deviation of all normal to normal R–R wave intervals, and the root mean square of successive differences as markers of cardiac parasympathetic modulation. Training load was quantified by multiplying the rating of perceived exertion of the weeks training and training duration. A decrease was identified in cardiac parasympathetic modulation as the season progressed (Effect Size (Cohen’s d) = −0.34 to −0.8, weeks 6 and 11–15), despite no significant relationship between training load and heart rate variability. Factors outside of training may further compound the reduction in heart rate variability, with further monitoring of external stressors (e.g., school) in adolescent athletes.

scholarly journals Heart Rate Variability and Direct Current Measurement Characteristics in Professional Mixed Martial Arts Athletes

Sports ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 109
Author(s):  
Joseph O. C. Coyne ◽  
Aaron J. Coutts ◽  
Roman Fomin ◽  
Duncan N. French ◽  
Robert U. Newton ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Direct Current ◽  
Martial Arts ◽  
Signal To Noise Ratio ◽  
Training Load ◽  
Mixed Martial Arts ◽  
Daily Training ◽  
Training Signal ◽  
Direct Current Measurement

This study’s purpose was to examine heart rate variability (HRV) and direct current potential (DC) measures’ sensitivity and correlations between changes in the acute recovery and stress scale (ARSS) and the previous day’s training load. Training load, HRV, DC and ARSS data were collected from fourteen professional mixed martial arts athletes (32.6 ± 5.3 years, 174.8 ± 8.8 cm, 79.2 ± 17.5 kg) the following morning after hard, easy and rest days. Sensitivity was expressed as a signal-to-noise ratio (SNR, inter-day typical error (TE) or coefficient of variation (%CV) divided by intra-day TE or %CV). Correlations between HRV, DC and ARSS with training load were also examined. The SNRs for the various HRV and DC measures were acceptable to good (1.02–2.85). There was a 23.1% CV average increase between measures taken between different locations versus the same location. Training load changes were not correlated with HRV/DC but were correlated with ARSS stress variables. Practitioners should be aware of HRV/DC variability; however the daily training signal was greater than the test-retest error in this investigation. Upon awakening, HRV/DC measures appear superior for standardization and planning. HRV and DC measures were less sensitive to the previous day’s training load than ARSS measures.

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