Heart Rate Variability as Biomarker of Training Load in Professional Soccer Players

Vilamitjana, Javier J.; Lentini, Néstor A.; Perez, Mario F.; Verde, Pablo Emilio

doi:10.1249/01.mss.0000496026.80272.dd

Cited by 7 publications

(11 citation statements)

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“…Additionally, increased sympathetic activity has been associated with muscle fatigue or contractures (Vilamitjana, 2014), which may also justify the topological proximity of SNS t to 'Injury'.…”

Section: Resultsmentioning

confidence: 99%

Decision Support System for Mitigating Athletic Injuries

Peterson

Evans

2019

International Journal of Computer Science in Sport

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The purpose of the present study was to demonstrate an inductive approach for dynamically modelling sport-related injuries with a probabilistic graphical model. Dynamic Bayesian Network (DBN), a well-known machine learning method, was employed to illustrate how sport practitioners could utilize a simulatory environment to augment the training management process. 23 University of Iowa female student-athletes (from 3 undisclosed teams) were regularly monitored with common athlete monitoring technologies, throughout the 2016 competitive season, as a part of their routine health and well-being surveillance. The presented work investigated the ability of these technologies to model injury occurrences in a dynamic, temporal dimension. To verify validity, DBN model accuracy was compared with the performance of its static counterpart. After 3 rounds of 5-fold cross-validation, resultant DBN mean accuracy surpassed naïve baseline threshold whereas static Bayesian network did not achieve baseline accuracy. Conclusive DBN suggested subjectively-reported stress two days prior, subjective internal perceived exertions one day prior, direct current potential and sympathetic tone the day of, as the most impactful towards injury manifestation.

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Section: Resultsmentioning

confidence: 99%

Decision Support System for Mitigating Athletic Injuries

Peterson

Evans

2019

International Journal of Computer Science in Sport

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“…Although studies have indicated that resistance training performed with an intensity greater than 60% of 1RM causes autonomic nervous system disturbance, representing on the reduction of HRV (12,13), the scientific literature pointed out that exposure to repeated stimuli (aerobic exercise), as long as there is balance between stress and recovery, can lead to an increase in HRV (3,7). According to Peçanha et al (1), the increase in HRV can be explained by the optimization of the activation of the parasympathetic band and reduction of the sympathetic tone, which is explained by the reduction in plasma concentration of norepinephrine.…”

Section: Discussionmentioning

confidence: 99%

“…Studies have shown that HRV can be modulated by physical exercise (5)(6)(7). Chronic exposure to moderate to high physical exercise intensity leads to an increase in HRV in healthy subjects (1).…”

Section: Introductionmentioning

confidence: 99%

Clustering vs Multi-Sets Method in Resistance Training: Effect on Heart Rate Variability

Fortes

Paes

et al. 2017

Asian J Sports Med

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The aim of this study was to analyze the effect of two different methods (clustering and multi-sets) on resistance training on heart rate variability (HRV) in young adults. A total of 31 volunteers were randomly divided into three groups: clustering (GCL), multi-sets (GMS) and control group (CG). Group and time interaction was identified (F(3, 28) = 36.71, P < 0.01), with reduction in CG (P = 0.01) and increase in GCL (P = 0.01) and GMS (P = 0.01). It was concluded that both clustering and multi-sets enhanced HRV after 8 weeks of resistance training in trained young adult males.

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“…The participants warmed-up for five minutes in a swimming pool. Next, in consideration of the post-activation potential phenomenon identified by Wilson et al. (2013), we gave participants another five minute warm-up interval before beginning the simulated race (50, 100, or 200-m freestyle).…”

Section: Methodsmentioning

confidence: 99%

Smartphone Use Among High Level Swimmers Is Associated With Mental Fatigue and Slower 100- and 200- but Not 50-Meter Freestyle Racing

et al. 2020

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Discovering any performance degradation effect of racing swimmers’ use of social media smartphone apps might lead to new training and race preparation protocols, including pre-meet smartphone avoidance. This study’s objective was to analyze the performance effects of using smartphone social media apps on the 50, 100, and 200-m freestyle among 25 high-level swimmers. Each participant performed the three race distances in two conditions: with smartphone app exposure (50-MF, 100-MF, and 200-MF) and without (50-CON, 100-CON, and 200-CON). We randomized the order of these two conditions across participants. While smartphone app use was not associated with statistically significant performance differences on the shortest race (50CON versus 50MF), a repeated measures ANOVA showed a significant condition × time interaction for the swimmers’100-m freestyle performance ( p = 0.01), with a significantly slower performance following smartphone app use evident in the last half of this race ( p = 0.02) but not in the first half ( p = 0.41). We also found a condition × time interaction in the same direction (slower for swimmers who used the smartphone app) for the 200-m freestyle performance ( p = 0.01), with the slower performance occurring in the second ( p = 0.01) but not the first ( p = 0.91), third ( p = 0.07) or fourth ( p = 0.06 ) quarters of this race. Thus, prolonged smartphone social media app use was associated with reduced performance from elite swimmers on the 100- and 200- but not the 50-m freestyle.

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Heart Rate Variability as Biomarker of Training Load in Professional Soccer Players

Cited by 7 publications

References 0 publications

Decision Support System for Mitigating Athletic Injuries

Decision Support System for Mitigating Athletic Injuries

Clustering vs Multi-Sets Method in Resistance Training: Effect on Heart Rate Variability

Smartphone Use Among High Level Swimmers Is Associated With Mental Fatigue and Slower 100- and 200- but Not 50-Meter Freestyle Racing

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