Study of Heart Rate Variability Characteristics and Mood States of Gigong Trainers by Training Period

2012 ◽  
Vol 12 ◽  
pp. 173-216
Author(s):  
Jun-Young Shim ◽  
Young-Ja Im
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Mood States ◽  
Training Period

scholarly journals HIIT Models in Addition to Training Load and Heart Rate Variability Are Related With Physiological and Performance Adaptations After 10-Weeks of Training in Young Futsal Players

2021 ◽  
Vol 12 ◽  
Author(s):  
Fernando de Souza Campos ◽  
Fernando Klitzke Borszcz ◽  
Lucinar Jupir Forner Flores ◽  
Lilian Keila Barazetti ◽  
Anderson Santiago Teixeira ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Vertical Jump ◽  
Young Male ◽  
Interval Training ◽  
Training Load ◽  
Training Period ◽  
Incremental Test ◽  
Peak Speed ◽  
Shuttle Run

IntroductionThe present study aimed to investigate the effects of two high-intensity interval training (HIIT) shuttle-run-based models, over 10 weeks on aerobic, anaerobic, and neuromuscular parameters, and the association of the training load and heart rate variability (HRV) with the change in the measures in young futsal players.MethodsEleven young male futsal players (age: 18.5 ± 1.1 years; body mass: 70.5 ± 5.7 kg) participated in this study. This pre-post study design was performed during a typical 10 weeks training period. HIIT sessions were conducted at 86% (HIIT86; n = 6) and 100% (HIIT100; n = 5) of peak speed of the FIET. Additionally, friendly and official matches, technical-tactical and strength-power training sessions were performed. Before and after the training period, all players performed the FIET, treadmill incremental, repeated sprint ability (RSA), sprint 15-m, and vertical jump tests (CMJ and SJ), and the HRV was measured. Training load (TL) was monitored using the session rating of perceived effort. Data analysis was carried out using Bayesian inference methods.ResultsThe HIIT86 model showed clear improvements for the peak oxygen uptake (VO2peak), peak speed in the treadmill incremental test, first and second ventilatory thresholds, RSA best and mean times, CMJ, and SJ. The HIIT100 model presented distinct advances in VO2peak, peak speed in the treadmill incremental test, RSA mean time, and CMJ. Between HIIT models comparisons showed more favorable probabilities of improvement for HIIT86 than HIIT100 model in all parameters. TL data and HIIT models strongly explained the changes in the RSA mean and best times (R2 = 0.71 and 0.87, respectively), as well as HRV changes, and HIIT models explained positively VO2peak changes (R2 = 0.72). All other changes in the parameters were low to moderately explained.ConclusionThe HIIT86 proved to be more effective for improving aerobic, RSA, and neuromuscular parameters than HIIT100 during a typical 10-week futsal training period. So, strength and conditioning specialists prescribing shuttle-run intermittent exercises at submaximal intensities can manage the individual acceleration load imposed on athlete increasing or decreasing either the set duration or the frequency of change of direction during HIIT programming.

The Effects of an Intensive 2-wk Resistance Training Period on Strength Performance and Nocturnal Heart Rate Variability

2020 ◽  
Vol 15 (10) ◽  
pp. 1448-1454
Author(s):  
Piia Kaikkonen ◽  
Esa Hynynen ◽  
Arto Hautala ◽  
Juha P. Ahtiainen
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Resistance Training ◽  
Effect Size ◽  
Training Load ◽  
Training Period ◽  
Short Term ◽  
Strength Performance ◽  
Repetition Maximum ◽  
Leg Press

Purpose: It is known that modifying the endurance-type training load of athletes may result in altered cardiac autonomic modulation that may be estimated with heart rate variability (HRV). However, the specific effects of intensive resistance-type training remain unclear. The main aim of this study was to find out whether an intensive 2-wk resistance training period affects the nocturnal HRV and strength performance of healthy participants. Methods: Young healthy men (N = 13, age 24 [2] y) performed 2-wk baseline training, 2-wk intensive training, and a 9-d tapering periods, with 2, 5, and 2 hypertrophic whole-body resistance exercise sessions per week, respectively. Maximal isometric and dynamic strength were tested at the end of these training periods. Nocturnal HRV was also analyzed at the end of these training periods. Results: As a main finding, the nocturnal root mean square of differences of successive R-R intervals decreased (P = .004; from 49 [18] to 43 [15] ms; 95% CI, 2.4–10.4; effect size = 0.97) during the 2-wk intensive resistance training period. In addition, maximal isometric strength improved slightly (P = .045; from 3933 [1362] to 4138 [1540] N; 95% CI, 5.4–404; effect size = 0.60). No changes were found in 1-repetition-maximum leg press or leg press repetitions at 80% 1-repetition maximum. Conclusions: The present data suggest that increased training load due to a short-term intensive resistance training period can be detected by nocturnal HRV. However, despite short-term accumulated physiological stress, a tendency of improvement in strength performance was detected.

scholarly journals Heart rate variability and soccer training: a case study

2013 ◽  
Vol 19 (1) ◽  
pp. 171-177
Author(s):  
Maurício Gattás Bara-Filho ◽  
Daniel Schimitz Freitas ◽  
Débora Moreira ◽  
Marcelo de Oliveira Matta ◽  
Jorge Roberto Perrout de Lima ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Supine Position ◽  
Individual Characteristics ◽  
Training Period ◽  
Rr Intervals ◽  
Soccer Training ◽  
Soccer Team ◽  
Periods Of Stress

The aim of this study was to monitor changes in HRV indices of two players of the same soccer team during a training period. Training loads of each session of the 3-week period were monitored by means of the training impulses (TRIMP) method. Resting RR intervals at supine position were obtained at five moments over 3-week period. The HRV indices (SD1, SDNN, RMSSD and HF) followed similar inter-subject patterns. They had similar values at M1 and, from M2, these variables were greater in athlete 1 than in athlete 2. At M2 and M4, athlete 1 presented a parasympathetic rebound, especially in SD1, SDNN and RMSSD, whereas athlete 2 presented reduction of these indices. We can advance that indices of HRV can be useful to monitor the effects of soccer training/competitive loads on parasympathetic modulation, being sensitive to both individual characteristics and to periods of stress and recovery.

scholarly journals Heart Rate Variability as a Marker of Changes in Mood State in Daily Life by Photoplethysmography Technique

2018 ◽  
Vol 1 (2) ◽  
pp. 100-103
Author(s):  
Santosh Kumar Deo ◽  
Kopila Agrawal ◽  
Prem Bhattarai
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
High Frequency ◽  
Mood State ◽  
Negative Mood ◽  
Low Frequency ◽  
Positive Mood ◽  
Mood States ◽  
State Condition ◽  
Negative Mood State

Introduction: The different mood states in our daily life can affect our mental and emotional health. The aim of our study was to explore photoplethysmography to record heart rate variability as a marker of changes in mood states in our daily life.Materials and Methods: Two groups of affective pictures categorized into positive and negative sets were shown to thirty subjects on two different consecutive days with simultaneously recording of heart rate variability for 5 minutes by photoplethysmography technique. Immediately after recording on each day, 0-9 self-assessment scale was used to assess the mood state of the subject after viewing the set of pictures.Results: Sympathetic domains of heart rate variability like low frequency (200.3 ±4.1 vs. 166.7 ±2.8, p<0.05), low- and high frequency ratio (1.45 ± 0.21 vs. 0.55 ± 0.07, p<0.05) and low frequency (55.8 ± 2.9 vs. 38.6 ± 2.8, p<0.05) significantly increased in negative mood state condition as compared to positive mood state condition. High frequency (157.9 ± 3.9 vs. 264.3 ± 5.3, p<0.05) and high frequency (44 ± 2.9 vs. 61.2 ±4.2, p< 0.05) significantly increased in positive mood state condition as compared to negative mood state condition. There was significant increase in heart rate (78 ± 2.99 vs. 73 ± 3.11, p<0.05) in negative mood state as compared to positive mood state.Conclusions: Increase in sympathetic activity during negative mood state and increase in parasympathetic activity during positive mood state measured by photoplethysmography technique validates this easy and noninvasive mental assessment tool to determine different mood states.

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