Effect of resistance training volume on heart rate variability in young adults

2019 ◽  
Vol 27 (1) ◽  
pp. 69-77
Author(s):  
Leonardo S. Fortes ◽  
Maria E.C. Ferreira ◽  
Santiago T. Paes ◽  
Manoel C. Costa ◽  
Dalton R.A.A. Lima-Júnior ◽  
...  
Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 18-OR
Author(s):  
AMY S. SHAH ◽  
LAURE EL GHORMLI ◽  
SAMUEL GIDDING ◽  
KARA S. HUGHAN ◽  
LORRAINE E. KATZ ◽  
...  

2020 ◽  
Vol 30 (11) ◽  
pp. 113116
Author(s):  
David Aguillard ◽  
Vanessa Zarubin ◽  
Caroline Wilson ◽  
Katherine R. Mickley Steinmetz ◽  
Carolyn Martsberger

SLEEP ◽  
2019 ◽  
Vol 42 (Supplement_1) ◽  
pp. A362-A363
Author(s):  
Lei Gao ◽  
Peng Li ◽  
Chelsea Hu ◽  
Patricia Wong ◽  
Chen Lin ◽  
...  

2019 ◽  
Vol 03 (02) ◽  
pp. E48-E57 ◽  
Author(s):  
Brett A. Dolezal ◽  
David M. Boland ◽  
Eric V. Neufeld ◽  
Jennifer L. Martin ◽  
Christopher B. Cooper

AbstractBehavioral modification (BM) is a strategy designed to sustain or restore well-being through effects such as enhanced relaxation, reduced stress, and improved sleep. Few studies have explored the role of BM delivered in the context of fitness programs for healthy adults. Thus, the purpose of this investigation was to examine whether BM combined with aerobic and resistance training programs would improve health and fitness measures more than the exercise training alone. Thirty-two healthy fitness club members (19 men) were randomized to receive a BM program (n=15) or an equal-attention (EA) control (n=17). BM consisted of twelve, 10-min education sessions between a trained fitness professional and the participant, coupled with weekly, individualized relaxation, stress reduction, and sleep improvement assignments. All participants engaged in 1 h of coached resistance training and remotely guided aerobic exercise thrice weekly for 12 weeks. Fitness measures (aerobic performance, body composition, muscle strength and endurance, lower-body power), sleep characteristics, and heart rate variability (HRV) were obtained at baseline and after the 12-week program. BM resulted in greater improvements in aerobic performance (increased maximum oxygen uptake, metabolic (lactate) threshold, and percent of maximum oxygen uptake at which metabolic threshold occurred), peak and average lower-body power, and body composition (decreased body fat percentage and fat mass) compared to EA. BM also positively influenced parasympathetic tone through increased High-frequency HRV. BM resulted in greater improvements in fitness measures, body composition, and heart rate variability compared with EA. These findings have intriguing implications regarding the role of BM in augmenting health and physical performance.


2009 ◽  
Vol 26 (4) ◽  
pp. 354-361 ◽  
Author(s):  
T. Koskinen ◽  
M. Kähönen ◽  
A. Jula ◽  
N. Mattsson ◽  
T. Laitinen ◽  
...  

Author(s):  
Martina Bernaciková ◽  
Jakub Mazúr ◽  
Martin Sebera ◽  
Petr Hedbávný

Purpose: Many high performance and especially top athletes are still at risk or suffer from total fatigue. Therefore, sports science seeks to develop an objective, sensitive and reliable method of early diagnosis of this fatigue (e.g. heart rate variability – HRV as a modern ob-jective method). The aim of the study was to evaluate whether the HRV monitoring could be a complementary diagnostic tool for overreaching / overtraining in young athletes. Already introduced “classical” indicators of HRV, such as spectral performance and its density in the established frequency ranges, are a part of athlete monitoring in the scope of overreaching prevention We were monitoring the heart rate variability parameters at three different phases of the year-long training cycle and to find out whether in one of these phases we could find athletes showing symptoms of overreaching. Methods: 48 young athletes (33 boys 14.8 ± 1.5 years, 15 girls 14.9 ± 1.7 years) were involved in the study, consisting of 38 boys and 10 girls. There were 15 swimmers (with training volume 9x 1.5‒2 hours a week), 12 artistic gymnasts (with training volume 9x 2‒2.5 hours a week) and 21 badminton players (with training volume 4x weekly 1.5‒2 hours a week). Monitoring was carried out in athletes in three training periods: at the end of the transition period, at the end of the prepared period, at the end of the competition period. Measurements were carried out in the morning. The DiANS PF8 system was used to measure the heart rate variability, the measurements were performed at five-minute intervals: lying-standing-lying. Time and spectral parameters of HRV were monitored. Results: Results of HRV in three periods (HR + rMSSD in lying). Boys: HR (61 ± 8, 64 ± 7, 64 ± 8), rMSSD (85 ± 64; 80 ± 54; 88 ± 59), TS (-0.56 ± 1.53; -0.87 ± 1.4; -0.42 ± 1.44). Girls: HR (65 ± 8; 64 ± 7; 65 ± 8), rMSSD (74 ± 37; 79 ± 35; 83 ± 43), TS (-0.58 ± 1.57; -0.72 ± 1.35); -0.18 ± 0.18). Statistically significant differences (at the significance level = 0.05) among sports were found in Kruskal-Walls ANOVAby Ranks: boys in LF-standing, HF standing, FV, SVB and TS; girls in HF-lying, HF-standing, rMSSD, TP-lying, TP-standing, FV, VA and TS. Conclusion: Monitoring of heart rate variability seems to be a practical tool for prevention of overtraining even in young age. To monitor heart rate variability, we recommend monitoring these parameters: RR, rMSSD, VA, SVB, TS.


2019 ◽  
Vol 7 (1) ◽  
pp. 19
Author(s):  
S D. Mamatha ◽  
R Rajalakshmi ◽  
T Rajesh Kumar ◽  
M C Smitha

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