Literature DB >> 33383719

Inter- and Intra-Day Comparisons of Smartphone-Derived Heart Rate Variability across Resistance Training Overload and Taper Microcycles.

Tyler D Williams1,2, Michael R Esco2, Michael V Fedewa2, Phillip A Bishop2.   

Abstract

The purposes of this study were: (1) to determine if smartphone-derived heart rate variability (HRV) could detect changes in training load during an overload microcycle and taper, and (2) to determine the reliability of HRV measured in the morning and measured immediately prior to the testing session. Twelve powerlifters (male = 10, female = 2) completed a 3-week resistance training program consisting of an introduction microcycle, overload microcycle, and taper. Using a validated smartphone application, daily measures of resting, ultra-short natural logarithm of root mean square of successive differences were recorded in the morning (LnRMSSDM) and immediately before the test session (LnRMSSDT) following baseline, post-overload, and post-taper testing. LnRMSSDM decreased from baseline (82.9 ± 13.0) to post-overload (75.0 ± 9.9, p = 0.019), while post-taper LnRMSSDM (81.9 ± 7.1) was not different from post-overload (p = 0.056) or baseline (p = 0.998). No differences in LnRMSSDT (p < 0.05) were observed between baseline (78.3 ± 9.0), post-overload (74.4 ± 10.2), and post-taper (78.3 ± 8.0). LnRMSSDM and LnRMSSDT were strongly correlated at baseline (ICC = 0.71, p < 0.001) and post-overload (ICC = 0.65, p = 0.010), whereas there was no relationship at post-taper (ICC = 0.44, p = 0.054). Bland-Altman analyses suggest extremely wide limits of agreement (Bias ± 1.96 SD) between LnRMSSDM and LnRMSSDT at baseline (4.7 ± 15.2), post-overload (0.5 ± 16.9), and post-taper (3.7 ± 15.3). Smartphone-derived HRV, recorded upon waking, was sensitive to resistance training loads across an overload and taper microcycles in competitive strength athletes, whereas the HRV was taken immediately prior to the testing session was not.

Entities:  

Keywords:  athlete monitoring; bench press; powerlifting; strength

Mesh:

Year:  2020        PMID: 33383719      PMCID: PMC7795557          DOI: 10.3390/ijerph18010177

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  25 in total

1.  Parasympathetic nervous activity mirrors recovery status in weightlifting performance after training.

Authors:  Jui-Lien Chen; Ding-Peng Yeh; Jo-Ping Lee; Chung-Yu Chen; Chih-Yang Huang; Shin-Da Lee; Chiu-Chou Chen; Terry B J Kuo; Chung-Lan Kao; Chia-Hua Kuo
Journal:  J Strength Cond Res       Date:  2011-06       Impact factor: 3.775

Review 2.  Heart rate monitoring: applications and limitations.

Authors:  Juul Achten; Asker E Jeukendrup
Journal:  Sports Med       Date:  2003       Impact factor: 11.136

Review 3.  Training Monitoring for Resistance Exercise: Theory and Applications.

Authors:  Brendan R Scott; Grant M Duthie; Heidi R Thornton; Ben J Dascombe
Journal:  Sports Med       Date:  2016-05       Impact factor: 11.136

Review 4.  Progressive statistics for studies in sports medicine and exercise science.

Authors:  William G Hopkins; Stephen W Marshall; Alan M Batterham; Juri Hanin
Journal:  Med Sci Sports Exerc       Date:  2009-01       Impact factor: 5.411

5.  Monitoring training with heart rate-variability: how much compliance is needed for valid assessment?

Authors:  Daniel J Plews; Paul B Laursen; Yann Le Meur; Christophe Hausswirth; Andrew E Kilding; Martin Buchheit
Journal:  Int J Sports Physiol Perform       Date:  2013-12-11       Impact factor: 4.010

6.  Smartphone-enabled pulse rate variability: an alternative methodology for the collection of heart rate variability in psychophysiological research.

Authors:  James A J Heathers
Journal:  Int J Psychophysiol       Date:  2013-06-08       Impact factor: 2.997

7.  Novel Resistance Training-Specific Rating of Perceived Exertion Scale Measuring Repetitions in Reserve.

Authors:  Michael C Zourdos; Alex Klemp; Chad Dolan; Justin M Quiles; Kyle A Schau; Edward Jo; Eric Helms; Ben Esgro; Scott Duncan; Sonia Garcia Merino; Rocky Blanco
Journal:  J Strength Cond Res       Date:  2016-01       Impact factor: 3.775

8.  Heart rate variability and psychometric responses to overload and tapering in collegiate sprint-swimmers.

Authors:  Andrew A Flatt; Bjoern Hornikel; Michael R Esco
Journal:  J Sci Med Sport       Date:  2016-11-17       Impact factor: 4.319

9.  Intraday and Interday Reliability of Ultra-Short-Term Heart Rate Variability in Rugby Union Players.

Authors:  Fábio Y Nakamura; Lucas A Pereira; Michael R Esco; Andrew A Flatt; José E Moraes; Cesar C Cal Abad; Irineu Loturco
Journal:  J Strength Cond Res       Date:  2017-02       Impact factor: 3.775

Review 10.  Monitoring training load to understand fatigue in athletes.

Authors:  Shona L Halson
Journal:  Sports Med       Date:  2014-11       Impact factor: 11.136

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