1
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Engel FA, Zehnter F, Yona T, Mai P, Willwacher S, Düking P, Sperlich B. Acute physiological, biomechanical, and perceptual responses of runners wearing downward-curved carbon fiber insoles. Front Sports Act Living 2024; 6:1340154. [PMID: 38645727 PMCID: PMC11026664 DOI: 10.3389/fspor.2024.1340154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/18/2024] [Indexed: 04/23/2024] Open
Abstract
In a randomized controlled cross-over study ten male runners (26.7 ± 4.9 years; recent 5-km time: 18:37 ± 1:07 min:s) performed an incremental treadmill test (ITT) and a 3-km time trial (3-km TT) on a treadmill while wearing either carbon fiber insoles with downwards curvature or insoles made of butyl rubber (control condition) in light road racing shoes (Saucony Fastwitch 9). Oxygen uptake, respiratory exchange ratio, heart rate, blood lactate concentration, stride frequency, stride length and time to exhaustion were assessed during ITT. After ITT, all runners rated their perceived exertion, perceived shoe comfort and perceived shoe performance. Running time, heart rate, blood lactate levels, stride frequency and stride length were recorded during, and shoe comfort and shoe performance after, the 3-km TT. All parameters obtained during or after the ITT did not differ between the two conditions [range: p = 0.188 to 0.948 (alpha value: 0.05); Cohen's d = 0.021 to 0.479] despite the rating of shoe comfort showing better scores for the control insoles (p = 0.001; d = -1.646). All parameters during and after the 3-km TT showed no differences (p = 0.200 to 1.000; d = 0.000 to 0.501) between both conditions except for shoe comfort showing better scores for control insoles (p = 0.017; d = -0.919). Running with carbon fiber insoles with downwards curvature did not change running performance or any submaximal or maximal physiological or biomechanical parameter and perceived exertion compared to control condition. Shoe comfort is impaired while running with carbon fiber insoles. Wearing carbon fiber insoles with downwards curvature during treadmill running is not beneficial when compared to running with control insoles.
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Affiliation(s)
- Florian A. Engel
- Integrative and Experimental Exercise Science and Training, University of Würzburg, Würzburg, Germany
| | - Frank Zehnter
- Integrative and Experimental Exercise Science and Training, University of Würzburg, Würzburg, Germany
| | - Tomer Yona
- Department of Biomedical Engineering, Technion Israel Institute of Technology, Haifa, Israel
| | - Patrick Mai
- Department of Mechanical and Process Engineering, Offenburg University of Applied Sciences, Offenburg, Germany
| | - Steffen Willwacher
- Department of Mechanical and Process Engineering, Offenburg University of Applied Sciences, Offenburg, Germany
| | - Peter Düking
- Department of Sports Science and Movement Pedagogy, Technische Universität Braunschweig, Braunschweig, Germany
| | - Billy Sperlich
- Integrative and Experimental Exercise Science and Training, University of Würzburg, Würzburg, Germany
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2
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Düking P, Sperlich B, Voigt L, Van Hooren B, Zanini M, Zinner C. ChatGPT Generated Training Plans for Runners are not Rated Optimal by Coaching Experts, but Increase in Quality with Additional Input Information. J Sports Sci Med 2024; 23:56-72. [PMID: 38455449 PMCID: PMC10915606 DOI: 10.52082/jssm.2024.56] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/19/2023] [Indexed: 03/09/2024]
Abstract
ChatGPT may be used by runners to generate training plans to enhance performance or health aspects. However, the quality of ChatGPT generated training plans based on different input information is unknown. The objective of the study was to evaluate ChatGPT-generated six-week training plans for runners based on different input information granularity. Three training plans were generated by ChatGPT using different input information granularity. 22 quality criteria for training plans were drawn from the literature and used to evaluate training plans by coaching experts on a 1-5 Likert Scale. A Friedmann test assessed significant differences in quality between training plans. For training plans 1, 2 and 3, a median rating of <3 was given 19, 11, and 1 times, a median rating of 3 was given 3, 5, and 8 times and a median rating of >3 was given 0, 6, 13 times, respectively. Training plan 1 received significantly lower ratings compared to training plan 2 for 3 criteria, and 15 times significantly lower ratings compared to training plan 3 (p < 0.05). Training plan 2 received significantly lower ratings (p < 0.05) compared to plan 3 for 9 criteria. ChatGPT generated plans are ranked sub-optimally by coaching experts, although the quality increases when more input information are provided. An understanding of aspects relevant to programming distance running training is important, and we advise avoiding the use of ChatGPT generated training plans without an expert coach's feedback.
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Affiliation(s)
- Peter Düking
- Department of Sports Science and Movement Pedagogy, Technische Universität Braunschweig, Braunschweig, Germany
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Laura Voigt
- Institute of Psychology, German Sport University Cologne, Cologne, Germany
| | - Bas Van Hooren
- Department of Nutrition and Movement Sciences, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Michele Zanini
- School of Sport, Exercise, and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - Christoph Zinner
- Department of Sport, University of Applied Sciences for Police and Administration of Hesse, Wiesbaden, Germany
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3
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Thron M, Düking P, Ruf L, Härtel S, Woll A, Altmann S. Assessing anaerobic speed reserve: A systematic review on the validity and reliability of methods to determine maximal aerobic speed and maximal sprinting speed in running-based sports. PLoS One 2024; 19:e0296866. [PMID: 38252665 PMCID: PMC10802961 DOI: 10.1371/journal.pone.0296866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/23/2023] [Indexed: 01/24/2024] Open
Abstract
PURPOSE Locomotor profiling using anaerobic speed reserve (ASR) enables insights into athletes' physiological and neuromuscular contributing factors and prescription of high-intensity training beyond maximal aerobic speed (MAS). This systematic review aimed to determine the validity and reliability of different methods to assess the characteristics of ASR, i.e., MAS and maximal sprinting speed (MSS). METHODS A comprehensive search of the PubMed and Web of Science databases was conducted according to the PRISMA guidelines. Studies were included if they reported data on validity and/or reliability for methods to assess MAS or MSS. RESULTS 58 studies were included with 28 studies referring to MAS and 30 studies to MSS. Regarding MAS, different methods for cardiopulmonary exercise testing yielded different values (four out of seven studies) of MAS (Cohen's d (ES) = 0.83-2.8; Pearson's r/intraclass correlation coefficient (r/ICC) = 0.46-0.85). Criterion validity of different field tests showed heterogeneous results (ES = 0-3.57; r/ICC = 0.40-0.96). Intraday and interday reliability was mostly acceptable for the investigated methods (ICC/r>0.76; CV<16.9%). Regarding MSS, radar and laser measurements (one out of one studies), timing gates (two out of two studies), and video analysis showed mostly good criterion validity (two out of two studies) (ES = 0.02-0.53; r/ICC = 0.93-0.98) and reliability (r/ICC>0.83; CV<2.43%). Criterion validity (ES = 0.02-7.11) and reliability (r/ICC = 0.14-0.97; CV = 0.7-9.77%) for global or local positioning systems (seven out of nine studies) and treadmill sprinting (one out of one studies) was not acceptable in most studies. CONCLUSION The criterion validity of incremental field tests or shuttle runs to examine MAS cannot be confirmed. Results on time trials indicate that distances adapted to the participants' sporting background, fitness, or sex might be suitable to estimate MAS. Regarding MSS, only sprints with radar or laser measures, timing gates, or video analysis provide valid and reliable results for linear sprints of 20 to 70 m.
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Affiliation(s)
- Maximiliane Thron
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Baden-Wuerttemberg, Germany
| | - Peter Düking
- Department of Sports Science and Movement Pedagogy, Technical University of Braunschweig, Braunschweig, Lower Saxony, Germany
| | - Ludwig Ruf
- TSG 1899 Hoffenheim, Zuzenhausen, Baden-Wuerttemberg, Germany
- TSG ResearchLab gGmbH, Zuzenhausen, Baden-Württemberg, Germany
| | - Sascha Härtel
- TSG 1899 Hoffenheim, Zuzenhausen, Baden-Wuerttemberg, Germany
| | - Alexander Woll
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Baden-Wuerttemberg, Germany
| | - Stefan Altmann
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Baden-Wuerttemberg, Germany
- TSG ResearchLab gGmbH, Zuzenhausen, Baden-Württemberg, Germany
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Sperlich B, Düking P, Leppich R, Holmberg HC. Strengths, weaknesses, opportunities, and threats associated with the application of artificial intelligence in connection with sport research, coaching, and optimization of athletic performance: a brief SWOT analysis. Front Sports Act Living 2023; 5:1258562. [PMID: 37920303 PMCID: PMC10618674 DOI: 10.3389/fspor.2023.1258562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 09/29/2023] [Indexed: 11/04/2023] Open
Abstract
Here, we performed a non-systematic analysis of the strength, weaknesses, opportunities, and threats (SWOT) associated with the application of artificial intelligence to sports research, coaching and optimization of athletic performance. The strength of AI with regards to applied sports research, coaching and athletic performance involve the automation of time-consuming tasks, processing and analysis of large amounts of data, and recognition of complex patterns and relationships. However, it is also essential to be aware of the weaknesses associated with the integration of AI into this field. For instance, it is imperative that the data employed to train the AI system be both diverse and complete, in addition to as unbiased as possible with respect to factors such as the gender, level of performance, and experience of an athlete. Other challenges include e.g., limited adaptability to novel situations and the cost and other resources required. Opportunities include the possibility to monitor athletes both long-term and in real-time, the potential discovery of novel indicators of performance, and prediction of risk for future injury. Leveraging these opportunities can transform athletic development and the practice of sports science in general. Threats include over-dependence on technology, less involvement of human expertise, risks with respect to data privacy, breaching of the integrity and manipulation of data, and resistance to adopting such new technology. Understanding and addressing these SWOT factors is essential for maximizing the benefits of AI while mitigating its risks, thereby paving the way for its successful integration into sport science research, coaching, and optimization of athletic performance.
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Affiliation(s)
- Billy Sperlich
- Integrative and Experimental Training Science, Institute of Sport Sciences, University of Würzburg, Würzburg, Germany
| | - Peter Düking
- Department of Sports Science and Movement Pedagogy, Technische Universität Braunschweig, Braunschweig, Germany
| | - Robert Leppich
- Software Engineering Group, Department of Computer Science, University of Würzburg, Würzburg, Germany
| | - Hans-Christer Holmberg
- Department of Health Sciences, Luleå University of Technology, Luleå, Sweden
- Department of Physiology and Pharmacology, Biomedicum C5, Karolinska Institutet, Stockholm, Sweden
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5
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Zinner C, Gerspitzer A, Düking P, Boone J, Schiffer T, Holmberg HC, Sperlich B. The magnitude and time-course of physiological responses to 9 weeks of incremental ramp testing. Scand J Med Sci Sports 2023. [PMID: 36866970 DOI: 10.1111/sms.14347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/16/2023] [Accepted: 02/19/2023] [Indexed: 03/04/2023]
Abstract
PURPOSE The aims of this study were to assess (1) the day-to-day variability in, and (2) the magnitude and time-course of adaptation of physiological parameters (i.e., maximal oxygen uptake [VO2 max], heart rate [HR], blood lactate concentration, respiratory exchange ratio [RER], ratings of perceived exertion [RPE], and time-to-exhaustion [TTE]) in response to an intervention involving three incremental ramp tests per week for 9 weeks. METHODS Twelve participants (25 ± 4 yrs, VO2 max, 47.8 ± 5.2 mL∙min-1 ∙kg-1 (means ± SD)) completed the entire experimental procedure. The tests comprised a 5-min constant workload to obtain submaximal parameters followed by an incremental protocol until exhaustion. RESULTS The mean day-to-day variability for the maximal value of VO2 was 2.8%, 1.1% for HR, 18.1% for blood lactate concentration, 2.1% for RER, 1.1% for RPE, and 5.0% for TTE. The values for the corresponding submaximal variables were 3.8% for VO2 , 2.1% for HR, 15.6% for blood lactate concentration, 2.6% for RER and 6.0% for RPE. VO2 max (+4.7% ± 3.5%), TTE (+17.9% ± 8.6%), and submaximal HR (-3.2 ± 3.5%) improved significantly. Except for RPE (p < 0.01), there were no alterations in the coefficient of variation for any parameter. On the group level, the first changes greater than the day-to-day variability in VO2 max, TTE, and submaximal HR were observed after 21, 12, and 9 training sessions, respectively. CONCLUSION Based on our findings, we recommend that training studies include assessment of the reliability of the measurements, for example, the CVs in the specific laboratory to be able to judge if the changes detected are actually physiological.
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Affiliation(s)
- Christoph Zinner
- Department of Sport, University of Applied Sciences for Police and Administration of Hesse, Wiesbaden, Germany
| | - Annika Gerspitzer
- Integrative & Experimental Exercise Science & Training, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Peter Düking
- Integrative & Experimental Exercise Science & Training, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Jan Boone
- Department of Movement and Sport Sciences, Ghent University, Ghent, Belgium
| | - Thorsten Schiffer
- Outpatient Clinic for Sports Traumatology and Public Health Consultation|, German Sport University Cologne, Cologne, Germany
| | - Hans-Christer Holmberg
- Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden
- Department of Health Sciences, Luleå University of Technology, Luleå, Sweden
| | - Billy Sperlich
- Integrative & Experimental Exercise Science & Training, Department of Sport Science, University of Würzburg, Würzburg, Germany
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6
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Düking P, Picerno P, Camomilla V, Gastaldi L, Sperlich B. Editorial: Highlights in sports science, technology and engineering 2021/22. Front Sports Act Living 2023; 4:1117803. [PMID: 36819731 PMCID: PMC9929562 DOI: 10.3389/fspor.2022.1117803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 12/13/2022] [Indexed: 02/05/2023] Open
Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Pietro Picerno
- SMART Engineering Solutions & Technologies (SMARTEST) Research Center, Università Telematica “e-Campus”, Novedrate, CO, Italy
| | - Valentina Camomilla
- Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Rome, Italy
| | - Laura Gastaldi
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino. Italy
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany,Correspondence: Billy Sperlich
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7
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Seshadri DR, Harlow ER, Thom ML, Emery MS, Phelan DM, Hsu JJ, Düking P, De Mey K, Sheehan J, Geletka B, Flannery R, Calcei JG, Karns M, Salata MJ, Gabbett TJ, Voos JE. Wearable technology in the sports medicine clinic to guide the return-to-play and performance protocols of athletes following a COVID-19 diagnosis. Digit Health 2023; 9:20552076231177498. [PMID: 37434736 PMCID: PMC10331194 DOI: 10.1177/20552076231177498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 05/06/2023] [Indexed: 07/13/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has enabled the adoption of digital health platforms for self-monitoring and diagnosis. Notably, the pandemic has had profound effects on athletes and their ability to train and compete. Sporting organizations worldwide have reported a significant increase in injuries manifesting from changes in training regimens and match schedules resulting from extended quarantines. While current literature focuses on the use of wearable technology to monitor athlete workloads to guide training, there is a lack of literature suggesting how such technology can mediate the return to sport processes of athletes infected with COVID-19. This paper bridges this gap by providing recommendations to guide team physicians and athletic trainers on the utility of wearable technology for improving the well-being of athletes who may be asymptomatic, symptomatic, or tested negative but have had to quarantine due to a close exposure. We start by describing the physiologic changes that occur in athletes infected with COVID-19 with extended deconditioning from a musculoskeletal, psychological, cardiopulmonary, and thermoregulatory standpoint and review the evidence on how these athletes may safely return to play. We highlight opportunities for wearable technology to aid in the return-to-play process by offering a list of key parameters pertinent to the athlete affected by COVID-19. This paper provides the athletic community with a greater understanding of how wearable technology can be implemented in the rehabilitation process of these athletes and spurs opportunities for further innovations in wearables, digital health, and sports medicine to reduce injury burden in athletes of all ages.
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Affiliation(s)
- Dhruv R Seshadri
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
| | - Ethan R Harlow
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Mitchell L Thom
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Michael S Emery
- Sports Cardiology Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Dermot M Phelan
- Sanger Heart and Vascular Institute, Atrium Health, Charlotte, NC, USA
| | - Jeffrey J Hsu
- David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | | | | | - Benjamin Geletka
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
- University Hospitals Rehabilitation Services and Sports Medicine, Cleveland, OH, USA
| | - Robert Flannery
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Jacob G Calcei
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Michael Karns
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Michael J Salata
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Tim J Gabbett
- Gabbett Performance Solutions, Brisbane, Australia
- Centre for Health Research, University of Southern Queensland, Ipswich, Australia
- School of Science, Psychology and Sport, Federation University, Ballarat, Australia
| | - James E Voos
- University Hospitals Sports Medicine Institute, Cleveland, OH, USA
- Department of Orthopaedic Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
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8
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Thron M, Düking P, Härtel S, Woll A, Altmann S. Differences in Physical Match Performance and Injury Occurrence Before and After the COVID-19 Break in Professional European Soccer Leagues: A Systematic Review. Sports Med - Open 2022; 8:121. [PMID: 36178557 PMCID: PMC9523642 DOI: 10.1186/s40798-022-00505-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/06/2022] [Indexed: 11/10/2022]
Abstract
Background Due to the COVID-19 pandemic, matches and soccer-specific training were suspended for several weeks, matches after resumption were congested, and substitutions per team and game increased from three to five. Objective The aim of this review was to examine possible differences in physical match performance and injuries between before and after the COVID-19 induced break of matches and training in professional male European soccer leagues during the 2019/2020 season. Methods A systematic search identified all scientifically peer-reviewed publications involving elite male soccer players competing in the European leagues which reported physical match performance variables such as total running distance and running distance at different speed zones and/or injury parameters pre- and post-COVID-19 induced break. Results In total, 11 articles were included, which were coming from German Bundesliga, Polish Ekstraklasa, Croatian HNL, Spanish La Liga, and Italian Serie A. In all studies investigating the German Bundesliga, most parameters of physical match performance remained unaffected (0.08 ≤ p ≤ 0.82; − 0.15 ≤ ES 0.15), while studies investigating the Polish Ekstraklasa (p ≤ 0.03; − 0.27 ≤ ES − 0.18), Croatian HNL (p ≤ 0.04; − 1.42 ≤ ES ≤ 1.44), Spanish La Liga (p ≤ 0.017; − 0.32 ≤ ES ≤ 5.5), and Italian Serie A (p ≤ 0.014; − 1.01 ≤ ES 0.24) showed a decrease in most parameters of physical match performance after the COVID-19 break. Injury rates were only investigated by studies targeting the German Bundesliga and Italian Serie A. In the majority of studies (3 out of 4 studies), there occurred no difference in injuries between pre- and post-COVID-19 break (p > 0.05; ES = N/A). Conclusion Results indicate that Bundesliga teams maintained physical match performance during the 9-weeks break in matches and 3-weeks break in group training, whereas a longer match and group training interruption up to 15 weeks and 8 weeks, respectively, in the other leagues appeared to lead to a decreased physical match performance. Regarding injuries, we speculate that the increase in substitutions from 3 to 5 substitutions per game might prevent an increase in injury occurrence during matches. The underlying studies’ results provide hints for possible upcoming unexpected interruptions with respect to optimal physical preparations for the resumption of matches and a congested schedule to maintain physical match performance, or for possible rule changes such as 5 instead of 3 substitutions to avoid physical overload during congested match schedules. Supplementary Information The online version contains supplementary material available at 10.1186/s40798-022-00505-z.
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9
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Wallmann-Sperlich B, Düking P, Müller M, Froböse I, Sperlich B. Type and intensity distribution of structured and incidental lifestyle physical activity of students and office workers: a retrospective content analysis. BMC Public Health 2022; 22:634. [PMID: 35365097 PMCID: PMC8976323 DOI: 10.1186/s12889-022-12999-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 03/16/2022] [Indexed: 11/16/2022] Open
Abstract
Background Physical activity (PA) guidelines acknowledge the health benefits of regular moderate-to-vigorous physical activity (MVPA) regardless of bout duration. However, little knowledge exists concerning the type and intensity distribution of structured and incidental lifestyle PA of students and office workers. The present study aimed to i) assess the duration and distribution of intensity of MVPAs during waking hours ≥50% of heart rate reserve (HRR), ii) to identify the type of PA through diary assessment, iii) to assign these activities into structured and lifestyle incidental PA, and iv) to compare this information between students and office workers. Methods Twenty-three healthy participants (11 students, 12 office workers) recorded heart rate (HR) with a wrist-worn HR monitor (Polar M600) and filled out a PA diary throughout seven consecutive days (i.e. ≥ 8 waking h/day). Relative HR zones were calculated, and PA diary information was coded using the Compendium of PA. We matched HR data with the reported PA and identified PA bouts during waking time ≥ 50% HRR concerning duration, HRR zone, type of PA, and assigned each activity to incidental and structured PA. Descriptive measures for time spend in different HRR zones and differences between students and office workers were calculated. Results In total, we analyzed 276.894 s (76 h 54 min 54 s) of waking time in HRR zones ≥50% and identified 169 different types of PA. The participants spend 31.9 ± 27.1 min/day or 3.9 ± 3.2% of their waking time in zones of ≥50% HRR with no difference between students and office workers (p > 0.01). The proportion of assigned incidental lifestyle PA was 76.9 ± 22.5%. Conclusions The present study provides initial insights regarding the type, amount, and distribution of intensity of structured and incidental lifestyle PA ≥ 50% HRR. Findings show a substantial amount of incidental lifestyle PA during waking hours and display the importance of promoting a physically active lifestyle. Future research could employ ambulatory assessments with integrated electronic diaries to detect information on the type and context of MVPA during the day. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-12999-z.
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Affiliation(s)
- Birgit Wallmann-Sperlich
- Institute of Sports Science, Julius-Maximilian University Würzburg, Judenbühlweg 11, 97082, Würzburg, Germany.
| | - Peter Düking
- Integrative and Experimental Exercise Science and Training, Institute of Sport Science, University of Würzburg, Judenbühlweg 11, 97082, Würzburg, Germany
| | - Miriam Müller
- Institute of Sports Science, Julius-Maximilian University Würzburg, Judenbühlweg 11, 97082, Würzburg, Germany
| | - Ingo Froböse
- Institute of Movement-Therapy and movement-oriented Prevention and Rehabilitation, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933, Köln, Germany
| | - Billy Sperlich
- Integrative and Experimental Exercise Science and Training, Institute of Sport Science, University of Würzburg, Judenbühlweg 11, 97082, Würzburg, Germany
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10
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Düking P, Van Hooren B, Sperlich B. Assessment of Peak Oxygen Uptake with a Smartwatch and its Usefulness
for Training of Runners. Int J Sports Med 2022; 43:642-647. [PMID: 35094376 PMCID: PMC9286863 DOI: 10.1055/a-1686-9068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Peak oxygen uptake (˙VO
2peak
) is an important factor
contributing to running performance. Wearable technology may allow the
assessment of ˙VO
2peak
more frequently and on a larger scale.
We aim to i) validate the ˙VO
2peak
assessed by a smartwatch
(Garmin Forerunner 245), and ii) discuss how this parameter may assist to
evaluate and guide training procedures. A total of 23 runners (12 female, 11
male; ˙VO
2peak
:
48.6±6.8 ml∙min
−1
∙kg
−1
)
visited the laboratory twice to determine their ˙VO
2peak
during a treadmill ramp test. Between laboratory visits, participants wore a
smartwatch and performed three outdoor runs to obtain
˙VO
2peak
values provided by the smartwatch. The
˙VO
2peak
obtained by the criterion measure ranged from 38
to
61 ml∙min
−1
∙kg
−1
.
The mean absolute percentage error (MAPE) between the smartwatch and the
criterion ˙VO
2peak
was 5.7%. The criterion measure
revealed a coefficient of variation of 4.0% over the VO2peak range from
38–61 ml∙min
−1
∙kg
−1
.
MAPE between the smartwatch and criterion measure was 7.1, 4.1 and
−6.2% when analyzing ˙VO
2peak
ranging from
39–45 ml∙min
−1
∙kg
−1
,
45–55 ml∙min
−1
∙kg
−1
or
55–61 ml∙min
−1
∙kg
−1
,
respectively.
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Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport
Science, University of Würzburg, Würzburg, Germany
| | - Bas Van Hooren
- Department of Nutrition and Movement Sciences, NUTRIM School of
Nutrition and Translational Research in Metabolism, Maastricht University
Medical Centre+, Maastricht, Netherlands
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport
Science, University of Würzburg, Würzburg, Germany
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11
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Düking P, Zinner C, Trabelsi K, Reed JL, Holmberg HC, Kunz P, Sperlich B. Monitoring and adapting endurance training on the basis of heart rate variability monitored by wearable technologies: A systematic review with meta-analysis. J Sci Med Sport 2021; 24:1180-1192. [PMID: 34489178 DOI: 10.1016/j.jsams.2021.04.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 04/19/2021] [Accepted: 04/20/2021] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To systematically perform a meta-analysis of the scientific literature to determine whether the outcomes of endurance training based on heart rate variability (HRV) are more favorable than those of predefined training. DESIGN Systematic review and meta-analysis. METHODS PubMed and Web of Science were searched systematically in March of 2020 using keywords related to endurance, the ANS, and training. To compare the outcomes of HRV-guided and predefined training, Hedges' g effect size and associated 95% confidence intervals were calculated. RESULTS A total of 8 studies (198 participants) were identified comprising 9 interventions involving a variety of approaches. Compared to predefined training, most HRV-guided interventions included fewer moderate- and/or high-intensity training sessions. Fixed effects meta-analysis revealed a significant medium-sized positive effect of HRV-guided training on submaximal physiological parameters (g = 0.296, 95% CI 0.031 to 0.562, p = 0.028), but its effects on performance (g = 0.079, 95% CI -0.050 to 0.393, p = 0.597) and V̇O2peak (g = 0.171, 95% CI -0.213 to 0.371, p = 0.130) were small and not statistically significant. Moreover, with regards to performance, HRV-guided training was associated with fewer non-responders and more positive responders. CONCLUSIONS In comparison to predefined training, HRV-guided endurance training had a medium-sized effect on submaximal physiological parameters, but only a small and non-significant influence on performance and V̇O2peak. There were fewer non-responders regarding performance with HRV-based training.
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Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Germany.
| | - Christoph Zinner
- University of Applied Sciences for Police and Administration of Hesse, Germany
| | - Khaled Trabelsi
- Education, Motricité, Sport et Santé, EM2S, LR19JS01, High Institute of Sport and Physical Education of Sfax, University of Sfax, Tunisia
| | - Jennifer L Reed
- Exercise Physiology and Cardiovascular Health Laboratory, Division of Cardiac Prevention and Rehabilitation, University of Ottawa Heart Institute, Canada; School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Canada; School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Canada
| | - Hans-Christer Holmberg
- Department of Physiology and Pharmacology, Biomedicum C5, Karolinska Institutet, Sweden; Department of Health Sciences, Luleå University of Technology, Luleå, Sweden
| | - Philipp Kunz
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Germany
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Germany
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12
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Düking P, Tafler M, Wallmann-Sperlich B, Sperlich B, Kleih S. Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis. JMIR Mhealth Uhealth 2020; 8:e20820. [PMID: 33211023 PMCID: PMC7714647 DOI: 10.2196/20820] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/13/2020] [Accepted: 09/02/2020] [Indexed: 12/21/2022] Open
Abstract
Background Decreasing levels of physical activity (PA) increase the incidences of noncommunicable diseases, obesity, and mortality. To counteract these developments, interventions aiming to increase PA are urgently needed. Mobile health (mHealth) solutions such as wearable sensors (wearables) may assist with an improvement in PA. Objective The aim of this study is to examine which behavior change techniques (BCTs) are incorporated in currently available commercial high-end wearables that target users’ PA behavior. Methods The BCTs incorporated in 5 different high-end wearables (Apple Watch Series 3, Garmin Vívoactive 3, Fitbit Versa, Xiaomi Amazfit Stratos 2, and Polar M600) were assessed by 2 researchers using the BCT Taxonomy version 1 (BCTTv1). Effectiveness of the incorporated BCTs in promoting PA behavior was assessed by a content analysis of the existing literature. Results The most common BCTs were goal setting (behavior), action planning, review behavior goal(s), discrepancy between current behavior and goal, feedback on behavior, self-monitoring of behavior, and biofeedback. Fitbit Versa, Garmin Vívoactive 3, Apple Watch Series 3, Polar M600, and Xiaomi Amazfit Stratos 2 incorporated 17, 16, 12, 11, and 11 BCTs, respectively, which are proven to effectively promote PA. Conclusions Wearables employ different numbers and combinations of BCTs, which might impact their effectiveness in improving PA. To promote PA by employing wearables, we encourage researchers to develop a taxonomy specifically designed to assess BCTs incorporated in wearables. We also encourage manufacturers to customize BCTs based on the targeted populations.
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Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport Science, Würzburg, Germany
| | - Marie Tafler
- Department of Psychology I, University of Würzburg, Würzburg, Germany
| | | | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport Science, Würzburg, Germany
| | - Sonja Kleih
- Department of Psychology I, University of Würzburg, Würzburg, Germany
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13
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Düking P, Zinner C, Reed JL, Holmberg HC, Sperlich B. Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review. Scand J Med Sci Sports 2020; 30:2291-2304. [PMID: 32785959 DOI: 10.1111/sms.13802] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 07/03/2020] [Accepted: 07/22/2020] [Indexed: 12/18/2022]
Abstract
Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre- and post-intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV-based interventions reduced the amount of moderate- and/or high-intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV-based training. Peak oxygen uptake ( V ˙ O 2 peak ) and submaximal running parameters (eg, LT1, LT2) improved following both HRV-based and predefined training, with no clear difference in the extent of improvement in V ˙ O 2 peak . Submaximal running parameters tended to improve more following HRV-based training. Research findings to date have been limited and inconsistent. Both HRV-based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater.
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Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Christoph Zinner
- University of Applied Sciences for Police and Administration of Hesse, Wiesbaden, Germany
| | - Jennifer L Reed
- Exercise Physiology and Cardiovascular Health Lab, Division of Cardiac Prevention and Rehabilitation, University of Ottawa Heart Institute, Ottawa, Canada.,School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Canada.,School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada
| | - Hans-Christer Holmberg
- Department of Health Sciences, Mid Sweden University, Sundsvall, Sweden.,Department of Physiology and Pharmacology, Biomedicum C5, Karolinska Institutet, Stockholm, Sweden
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
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14
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Düking P, Holmberg HC, Kunz P, Leppich R, Sperlich B. Intra-individual physiological response of recreational runners to different training mesocycles: a randomized cross-over study. Eur J Appl Physiol 2020; 120:2705-2713. [PMID: 32918588 PMCID: PMC7674349 DOI: 10.1007/s00421-020-04477-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 08/14/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE Pronounced differences in individual physiological adaptation may occur following various training mesocycles in runners. Here we aimed to assess the individual changes in performance and physiological adaptation of recreational runners performing mesocycles with different intensity, duration and frequency. METHODS Employing a randomized cross-over design, the intra-individual physiological responses [i.e., peak ([Formula: see text]) and submaximal ([Formula: see text]) oxygen uptake, velocity at lactate thresholds (V2, V4)] and performance (time-to-exhaustion (TTE)) of 13 recreational runners who performed three 3-week sessions of high-intensity interval training (HIIT), high-volume low-intensity training (HVLIT) or more but shorter sessions of HVLIT (high-frequency training; HFT) were assessed. RESULTS [Formula: see text], V2, V4 and TTE were not altered by HIIT, HVLIT or HFT (p > 0.05). [Formula: see text] improved to the same extent following HVLIT (p = 0.045) and HFT (p = 0.02). The number of moderately negative responders was higher following HIIT (15.4%); and HFT (15.4%) than HVLIT (7.6%). The number of very positive responders was higher following HVLIT (38.5%) than HFT (23%) or HIIT (7.7%). 46% of the runners responded positively to two mesocycles, while 23% did not respond to any. CONCLUSION On a group level, none of the interventions altered [Formula: see text], V2, V4 or TTE, while HVLIT and HFT improved [Formula: see text]. The mean adaptation index indicated similar numbers of positive, negative and non-responders to HIIT, HVLIT and HFT, but more very positive responders to HVLIT than HFT or HIIT. 46% responded positively to two mesocycles, while 23% did not respond to any. These findings indicate that the magnitude of responses to HIIT, HVLIT and HFT is highly individual and no pattern was apparent.
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Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science and Training, Department of Sport Science, University of Würzburg, Würzburg, Germany.
| | - Hans-Christer Holmberg
- Swedish Winter Sports Research Centre, Department of Health Sciences, Mid Sweden University, Östersund, Sweden.,Department of Physiology and Pharmacology, Biomedicum C5, Karolinska Institutet, Stockholm, Sweden
| | - Philipp Kunz
- Integrative and Experimental Exercise Science and Training, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Robert Leppich
- Chair of Software Engineering, Department of Computer Science, University of Würzburg, Würzburg, Germany
| | - Billy Sperlich
- Integrative and Experimental Exercise Science and Training, Department of Sport Science, University of Würzburg, Würzburg, Germany
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15
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Düking P, Giessing L, Frenkel MO, Koehler K, Holmberg HC, Sperlich B. Wrist-Worn Wearables for Monitoring Heart Rate and Energy Expenditure While Sitting or Performing Light-to-Vigorous Physical Activity: Validation Study. JMIR Mhealth Uhealth 2020; 8:e16716. [PMID: 32374274 PMCID: PMC7240439 DOI: 10.2196/16716] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/12/2019] [Accepted: 01/24/2020] [Indexed: 01/07/2023] Open
Abstract
Background Physical activity reduces the incidences of noncommunicable diseases, obesity, and mortality, but an inactive lifestyle is becoming increasingly common. Innovative approaches to monitor and promote physical activity are warranted. While individual monitoring of physical activity aids in the design of effective interventions to enhance physical activity, a basic prerequisite is that the monitoring devices exhibit high validity. Objective Our goal was to assess the validity of monitoring heart rate (HR) and energy expenditure (EE) while sitting or performing light-to-vigorous physical activity with 4 popular wrist-worn wearables (Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa). Methods While wearing the 4 different wearables, 25 individuals performed 5 minutes each of sitting, walking, and running at different velocities (ie, 1.1 m/s, 1.9 m/s, 2.7 m/s, 3.6 m/s, and 4.1 m/s), as well as intermittent sprints. HR and EE were compared to common criterion measures: Polar-H7 chest belt for HR and indirect calorimetry for EE. Results While monitoring HR at different exercise intensities, the standardized typical errors of the estimates were 0.09-0.62, 0.13-0.88, 0.62-1.24, and 0.47-1.94 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 0.9%-4.3%, 2.2%-6.7%, 2.9%-9.2%, and 4.1%-19.1%, respectively, for the 4 wearables. While monitoring EE at different exercise intensities, the standardized typical errors of the estimates were 0.34-1.84, 0.32-1.33, 0.46-4.86, and 0.41-1.65 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 13.5%-27.1%, 16.3%-28.0%, 15.9%-34.5%, and 8.0%-32.3%, respectively. Conclusions The Apple Watch Series 4 provides the highest validity (ie, smallest error rates) when measuring HR while sitting or performing light-to-vigorous physical activity, followed by the Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, in that order. The Apple Watch Series 4 and Polar Vantage V are suitable for valid HR measurements at the intensities tested, but HR data provided by the Garmin Fenix 5 and Fitbit Versa should be interpreted with caution due to higher error rates at certain intensities. None of the 4 wrist-worn wearables should be employed to monitor EE at the intensities and durations tested.
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Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Laura Giessing
- Department of Sport Psychology, Institute for Sport and Sport Sciences, Heidelberg University, Heidelberg, Germany
| | - Marie Ottilie Frenkel
- Department of Sport Psychology, Institute for Sport and Sport Sciences, Heidelberg University, Heidelberg, Germany
| | - Karsten Koehler
- Department of Sport and Health Science, Technical University of Munich, Munich, Germany
| | - Hans-Christer Holmberg
- Department of Health Sciences, Mid Sweden University, Östersund, Sweden.,Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
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16
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Davidson P, Düking P, Zinner C, Sperlich B, Hotho A. Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study. Sensors (Basel) 2020; 20:s20092637. [PMID: 32380738 PMCID: PMC7248997 DOI: 10.3390/s20092637] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 04/27/2020] [Accepted: 04/29/2020] [Indexed: 11/16/2022]
Abstract
The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE ( ≤ 15 "Somewhat hard to hard" on Borg's 6-20 scale vs. RPE > 15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84 . 8 for the whole dataset, 81 . 82 for the trained runners, and 86 . 08 for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions.
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Affiliation(s)
- Padraig Davidson
- Data Science, Institute for Computer Sciences, University of Würzburg, 97074 Würzburg, Germany;
- Correspondence: (P.D.); (P.D.)
| | - Peter Düking
- Integrative and Experimental Exercise Science & Training, Institute for Sport Sciences, University of Würzburg, 97082 Würzburg, Germany;
- Correspondence: (P.D.); (P.D.)
| | - Christoph Zinner
- Department of Sport, University of Applied Sciences for Police and Administration of Hesse, 65199 Wiesbaden, Germany;
| | - Billy Sperlich
- Integrative and Experimental Exercise Science & Training, Institute for Sport Sciences, University of Würzburg, 97082 Würzburg, Germany;
| | - Andreas Hotho
- Data Science, Institute for Computer Sciences, University of Würzburg, 97074 Würzburg, Germany;
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17
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Sperlich B, Aminian K, Düking P, Holmberg HC. Editorial: Wearable Sensor Technology for Monitoring Training Load and Health in the Athletic Population. Front Physiol 2020; 10:1520. [PMID: 31969826 PMCID: PMC6960165 DOI: 10.3389/fphys.2019.01520] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 12/03/2019] [Indexed: 11/13/2022] Open
Affiliation(s)
- Billy Sperlich
- Integrative and Experimental Exercise Science & Training, University of Würzburg, Würzburg, Germany
| | - Kamiar Aminian
- Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Peter Düking
- Integrative and Experimental Exercise Science & Training, University of Würzburg, Würzburg, Germany
| | - Hans-Christer Holmberg
- Department of Health Sciences, Mid Sweden University, Östersund, Sweden.,School of Kinesiology, University of British Columbia, Vancouver, BC, Canada.,Department of Physiology and Pharmacology, Biomedicum C5, Karolinska Institutet, Stockholm, Sweden
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18
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Sperlich B, Kunz P, Düking P. Book of Abstract–German Exercise Science & Training Conference (GEST19) of the German Society of Sport Science (dvs), February 20th–22nd 2019. Ger J Exerc Sport Res 2019. [DOI: 10.1007/s12662-019-00567-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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19
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Düking P, Stammel C, Sperlich B, Sutehall S, Muniz-Pardos B, Lima G, Kilduff L, Keramitsoglou I, Li G, Pigozzi F, Pitsiladis YP. Necessary Steps to Accelerate the Integration of Wearable Sensors Into Recreation and Competitive Sports. Curr Sports Med Rep 2018; 17:178-182. [DOI: 10.1249/jsr.0000000000000495] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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20
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Düking P, Fuss FK, Holmberg HC, Sperlich B. Recommendations for Assessment of the Reliability, Sensitivity, and Validity of Data Provided by Wearable Sensors Designed for Monitoring Physical Activity. JMIR Mhealth Uhealth 2018; 6:e102. [PMID: 29712629 PMCID: PMC5952119 DOI: 10.2196/mhealth.9341] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 02/08/2018] [Accepted: 02/17/2018] [Indexed: 01/18/2023] Open
Abstract
Although it is becoming increasingly popular to monitor parameters related to training, recovery, and health with wearable sensor technology (wearables), scientific evaluation of the reliability, sensitivity, and validity of such data is limited and, where available, has involved a wide variety of approaches. To improve the trustworthiness of data collected by wearables and facilitate comparisons, we have outlined recommendations for standardized evaluation. We discuss the wearable devices themselves, as well as experimental and statistical considerations. Adherence to these recommendations should be beneficial not only for the individual, but also for regulatory organizations and insurance companies.
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Affiliation(s)
- Peter Düking
- Integrative & Experimental Exercise Science & Training, Institute for Sport Sciences, University of Würzburg, Würzburg, Germany.,Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden
| | - Franz Konstantin Fuss
- Smart Equipment Engineering and Wearable Technology Research Program, Centre for Design Innovation, Swinburne University of Technology, Melbourne, Australia
| | - Hans-Christer Holmberg
- Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden.,School of Sport Sciences, University of Tromsø - The Arctic University of Norway, Tromsø, Norway.,School of Kinesiology, University of British Columbia, Vancouver, BC, Canada
| | - Billy Sperlich
- Integrative & Experimental Exercise Science & Training, Institute for Sport Sciences, University of Würzburg, Würzburg, Germany
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21
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Düking P, Holmberg HC, Sperlich B. The Potential Usefulness of Virtual Reality Systems for Athletes: A Short SWOT Analysis. Front Physiol 2018; 9:128. [PMID: 29551978 PMCID: PMC5841195 DOI: 10.3389/fphys.2018.00128] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 02/07/2018] [Indexed: 12/26/2022] Open
Affiliation(s)
- Peter Düking
- Integrative & Experimental Exercise Science & Training, Institute for Sport Sciences, University of Würzburg, Würzburg, Germany.,Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden
| | - Hans-Christer Holmberg
- Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden.,School of Sport Sciences, UiT The Arctic University of Norway, Tromsø, Norway.,School of Kinesiology, University of British Columbia, Vancouver, BC, Canada
| | - Billy Sperlich
- Integrative & Experimental Exercise Science & Training, Institute for Sport Sciences, University of Würzburg, Würzburg, Germany
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22
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Fuss FK, Düking P, Weizman Y. Discovery of a Sweet Spot on the Foot with a Smart Wearable Soccer Boot Sensor That Maximizes the Chances of Scoring a Curved Kick in Soccer. Front Physiol 2018; 9:63. [PMID: 29487534 PMCID: PMC5816831 DOI: 10.3389/fphys.2018.00063] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Accepted: 01/18/2018] [Indexed: 11/13/2022] Open
Abstract
This paper provides the evidence of a sweet spot on the boot/foot as well as the method for detecting it with a wearable pressure sensitive device. This study confirmed the hypothesized existence of sweet and dead spots on a soccer boot or foot when kicking a ball. For a stationary curved kick, kicking the ball at the sweet spot maximized the probability of scoring a goal (58-86%), whereas having the impact point at the dead zone minimized the probability (11-22%). The sweet spot was found based on hypothesized favorable parameter ranges (center of pressure in x/y-directions and/or peak impact force) and the dead zone based on hypothesized unfavorable parameter ranges. The sweet spot was rather concentrated, independent of which parameter combination was used (two- or three-parameter combination), whereas the dead zone, located 21 mm from the sweet spot, was more widespread.
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Affiliation(s)
- Franz Konstantin Fuss
- Smart Equipment Engineering and Wearable Technology Research Program, Centre for Design Innovation, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Peter Düking
- Integrative and Experimental Training Science, Institute for Sport Sciences, Julius-Maximilians University Würzburg, Würzburg, Germany
| | - Yehuda Weizman
- Smart Equipment Engineering and Wearable Technology Research Program, Centre for Design Innovation, Swinburne University of Technology, Melbourne, VIC, Australia
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23
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Wahl Y, Düking P, Droszez A, Wahl P, Mester J. Criterion-Validity of Commercially Available Physical Activity Tracker to Estimate Step Count, Covered Distance and Energy Expenditure during Sports Conditions. Front Physiol 2017; 8:725. [PMID: 29018355 PMCID: PMC5615304 DOI: 10.3389/fphys.2017.00725] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 09/06/2017] [Indexed: 01/07/2023] Open
Abstract
Background: In the past years, there was an increasing development of physical activity tracker (Wearables). For recreational people, testing of these devices under walking or light jogging conditions might be sufficient. For (elite) athletes, however, scientific trustworthiness needs to be given for a broad spectrum of velocities or even fast changes in velocities reflecting the demands of the sport. Therefore, the aim was to evaluate the validity of eleven Wearables for monitoring step count, covered distance and energy expenditure (EE) under laboratory conditions with different constant and varying velocities. Methods: Twenty healthy sport students (10 men, 10 women) performed a running protocol consisting of four 5 min stages of different constant velocities (4.3; 7.2; 10.1; 13.0 km·h−1), a 5 min period of intermittent velocity, and a 2.4 km outdoor run (10.1 km·h−1) while wearing eleven different Wearables (Bodymedia Sensewear, Beurer AS 80, Polar Loop, Garmin Vivofit, Garmin Vivosmart, Garmin Vivoactive, Garmin Forerunner 920XT, Fitbit Charge, Fitbit Charge HR, Xaomi MiBand, Withings Pulse Ox). Step count, covered distance, and EE were evaluated by comparing each Wearable with a criterion method (Optogait system and manual counting for step count, treadmill for covered distance and indirect calorimetry for EE). Results: All Wearables, except Bodymedia Sensewear, Polar Loop, and Beurer AS80, revealed good validity (small MAPE, good ICC) for all constant and varying velocities for monitoring step count. For covered distance, all Wearables showed a very low ICC (<0.1) and high MAPE (up to 50%), revealing no good validity. The measurement of EE was acceptable for the Garmin, Fitbit and Withings Wearables (small to moderate MAPE), while Bodymedia Sensewear, Polar Loop, and Beurer AS80 showed a high MAPE up to 56% for all test conditions. Conclusion: In our study, most Wearables provide an acceptable level of validity for step counts at different constant and intermittent running velocities reflecting sports conditions. However, the covered distance, as well as the EE could not be assessed validly with the investigated Wearables. Consequently, covered distance and EE should not be monitored with the presented Wearables, in sport specific conditions.
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Affiliation(s)
- Yvonne Wahl
- Institute of Biomechanics and Orthopedics, German Sport University CologneCologne, Germany.,German Research Centre of Elite Sport, German Sport University CologneCologne, Germany
| | - Peter Düking
- Integrative and Experimental Exercise Science, Department of Sport Science, University of WürzburgWürzburg, Germany
| | - Anna Droszez
- German Research Centre of Elite Sport, German Sport University CologneCologne, Germany
| | - Patrick Wahl
- German Research Centre of Elite Sport, German Sport University CologneCologne, Germany.,Department of Molecular and Cellular Sport Medicine, Institute of Cardiovascular Research and Sport Medicine, German Sport University CologneCologne, Germany
| | - Joachim Mester
- German Research Centre of Elite Sport, German Sport University CologneCologne, Germany
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Sperlich B, Düking P, Holmberg HC. A SWOT Analysis of the Use and Potential Misuse of Implantable Monitoring Devices by Athletes. Front Physiol 2017; 8:629. [PMID: 28928670 PMCID: PMC5591786 DOI: 10.3389/fphys.2017.00629] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 08/11/2017] [Indexed: 12/01/2022] Open
Affiliation(s)
- Billy Sperlich
- Integrative and Experimental Exercise Science, Institute for Sport Sciences, University of WürzburgWürzburg, Germany
| | - Peter Düking
- Integrative and Experimental Exercise Science, Institute for Sport Sciences, University of WürzburgWürzburg, Germany.,Swedish Winter Sports Research Centre, Mid Sweden UniversityÖstersund, Sweden
| | - Hans-Christer Holmberg
- Swedish Winter Sports Research Centre, Mid Sweden UniversityÖstersund, Sweden.,School of Sport Sciences, UiT The Arctic University of NorwayTromsø, Norway.,School of Kinesiology, University of British ColumbiaVancouver, BC, Canada
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25
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Düking P, Holmberg HC, Sperlich B. Instant Biofeedback Provided by Wearable Sensor Technology Can Help to Optimize Exercise and Prevent Injury and Overuse. Front Physiol 2017; 8:167. [PMID: 28420998 PMCID: PMC5376581 DOI: 10.3389/fphys.2017.00167] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 03/07/2017] [Indexed: 12/01/2022] Open
Affiliation(s)
- Peter Düking
- Integrative and Experimental Exercise Science, Institute for Sport Sciences, Julius-Maximilians UniversityWürzburg, Germany
| | - Hans-Christer Holmberg
- Swedish Winter Sports Research Centre, Mid Sweden UniversityÖstersund, Sweden.,Department of Physiology and Pharmacology, Karolinska InstituteStockholm, Sweden.,School of Sport Sciences, UiT Arctic University of NorwayTromsø, Norway
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Institute for Sport Sciences, Julius-Maximilians UniversityWürzburg, Germany
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Hendricks S, Düking P, Mellalieu SD. Twitter Strategies for Web-Based Surveying: Descriptive Analysis From the International Concussion Study. JMIR Res Protoc 2016; 5:e179. [PMID: 27589958 PMCID: PMC5025563 DOI: 10.2196/resprot.4542] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2015] [Revised: 01/11/2016] [Accepted: 04/17/2016] [Indexed: 11/13/2022] Open
Abstract
Background Social media provides researchers with an efficient means to reach and engage with a large and diverse audience. Twitter allows for the virtual social interaction among a network of users that enables researchers to recruit and administer surveys using snowball sampling. Although using Twitter to administer surveys for research is not new, strategies to improve response rates are yet to be reported. Objective To compare the potential and actual reach of 2 Twitter accounts that administered a Web-based concussion survey to rugby players and trainers using 2 distinct Twitter-targeting strategies. Furthermore, the study sought to determine the likelihood of receiving a retweet based on the time of the day and day of the week of posting. Methods A survey based on previous concussion research was exported to a Web-based survey website Survey Monkey. The survey comprised 2 questionnaires, one for players, and one for those involved in the game (eg, coaches and athletic trainers). The Web-based survey was administered using 2 existing Twitter accounts, with each account executing a distinct targeting strategy. A list of potential Twitter accounts to target was drawn up, together with a list of predesigned tweets. The list of accounts to target was divided into ‘High-Profile’ and ‘Low-Profile’, based on each accounts’ position to attract publicity with a high social interaction potential. The potential reach (number of followers of the targeted account), and actual reach (number of retweets received by each post) between the 2 strategies were compared. The number of retweets received by each account was further analyzed to understand when the most likely time of day, and day of the week, a retweet would be received. Results The number of retweets received by a Twitter account decreased by 72% when using the ‘high-profile strategy’ compared with the ‘low-profile strategy’ (incidence rate ratio (IRR); 0.28, 95% confidence interval (CI) 0.21-0.37, P<.001). When taking into account strategy and day of the week, the IRR for the number of retweets received during the hours of 12 AM to 5:59 AM (IRR 2.98, 95% CI 1.88-4.71, P>.001) and 6 PM to 11:59 PM (IRR 1.48, 95% CI 1.05-2.09, P>.05) were significantly increased relative to 6 AM to 11:59 AM. However, posting tweets during the hours of 12 PM to 5:59 PM, decreased the IRR for retweets by 40% (IRR 0.60, 95% CI 0.46-0.79, P<.001) compared with 6 AM to 11:59 AM. Posting on a Monday (IRR 3.57, 95% CI 2.50-5.09, P<.001) or Wednesday (IRR 1.50, 95% CI 1.11-1.11, P<.01) significantly increased the IRR compared with posting on a Thursday. Conclusions Surveys are a useful tool to measure the knowledge, attitudes, and behaviors of a given population. Strategies to improve Twitter engagement include targeting low-profile accounts, posting tweets in the morning (12 AM-11:59 AM) or late evenings (6 PM-11:59 PM), and posting on Mondays and Wednesdays.
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Affiliation(s)
- Sharief Hendricks
- Division of Exercise Science and Sports Medicine, Department of Human Biology, University of Cape Town, Cape Town, South Africa.
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27
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Born DP, Zinner C, Düking P, Sperlich B. Multi-Directional Sprint Training Improves Change-Of-Direction Speed and Reactive Agility in Young Highly Trained Soccer Players. J Sports Sci Med 2016; 15:314-319. [PMID: 27274670 PMCID: PMC4879446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Accepted: 03/31/2016] [Indexed: 06/06/2023]
Abstract
The aim of this study was to evaluate the effect of a repeated sprint training with multi-directional change-of-direction (COD) movements (RSmulti) compared to repeated shuttle sprints (RSS) on variables related to COD speed and reactive agility. Nineteen highly-trained male U15 soccer players were assigned into two groups performing either RSmulti or RSS. For both groups, each training session involved 20 repeated 15 s sprints interspersed with 30 s recovery. With RSmulti the COD movements were randomized and performed in response to a visual stimulus, while the RSS involved predefined 180° COD movements. Before and following the six training sessions, performance in the Illinois agility test (IAT), COD speed in response to a visual stimulus, 20 m linear sprint time and vertical jumping height were assessed. Both groups improved their performance in the IAT (p < 0.01, ES = 1.13; p = 0.01, ES = 0.55). The COD speed in response to a visual stimulus improved with the RSmulti (p < 0.01, ES = 1.03), but not the RSS (p = 0.46, ES = 0.28). No differences were found for 20 m sprint time (P=0.73, ES = 0.07; p = 0.14, ES = 0.28) or vertical jumping height (p = 0.46, ES = 0.11; p = 0.29, ES = 0.12) for the RSmulti and RSS, respectively. In conclusion, performance in the IAT improved with the RSmulti as well as RSS. With the RSmulti however, the COD movements are performed in response to a visual stimulus, which may result in specific adaptations that improve COD speed and reactive agility in young highly trained soccer players. Key pointsDuring soccer, the players perform repeated sprints involving multi-directional COD movements, while most of these turns and twists are not pre-planned but executed in response to an external stimulus, such as ball movement, several interacting opponents and changing game situations.Both groups improved performance in the IAT. With the RSmulti on the Speedcourt however, the COD movements are performed in response to a visual stimulus, which may result in specific adaptations that improve COD speed and reactive agility.The Speedcourt could serve as a valuable method to design and individualize specific conditioning drills for young highly-trained soccer players.
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Affiliation(s)
- Dennis-Peter Born
- University of Wuerzburg, Integrative and Experimental Exercise Science, Institute for Sport Sciences , Wuerzburg, Germany
| | - Christoph Zinner
- University of Wuerzburg, Integrative and Experimental Exercise Science, Institute for Sport Sciences , Wuerzburg, Germany
| | - Peter Düking
- University of Wuerzburg, Integrative and Experimental Exercise Science, Institute for Sport Sciences , Wuerzburg, Germany
| | - Billy Sperlich
- University of Wuerzburg, Integrative and Experimental Exercise Science, Institute for Sport Sciences , Wuerzburg, Germany
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Düking P, Hotho A, Holmberg HC, Fuss FK, Sperlich B. Comparison of Non-Invasive Individual Monitoring of the Training and Health of Athletes with Commercially Available Wearable Technologies. Front Physiol 2016; 7:71. [PMID: 27014077 PMCID: PMC4783417 DOI: 10.3389/fphys.2016.00071] [Citation(s) in RCA: 88] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Accepted: 02/15/2016] [Indexed: 11/29/2022] Open
Abstract
Athletes adapt their training daily to optimize performance, as well as avoid fatigue, overtraining and other undesirable effects on their health. To optimize training load, each athlete must take his/her own personal objective and subjective characteristics into consideration and an increasing number of wearable technologies (wearables) provide convenient monitoring of various parameters. Accordingly, it is important to help athletes decide which parameters are of primary interest and which wearables can monitor these parameters most effectively. Here, we discuss the wearable technologies available for non-invasive monitoring of various parameters concerning an athlete's training and health. On the basis of these considerations, we suggest directions for future development. Furthermore, we propose that a combination of several wearables is most effective for accessing all relevant parameters, disturbing the athlete as little as possible, and optimizing performance and promoting health.
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Affiliation(s)
- Peter Düking
- Integrative and Experimental Training Science, Department of Sports Science, Institute for Sport Sciences, Julius-Maximilians University Würzburg Würzburg, Germany
| | - Andreas Hotho
- Data Mining and Information Retrieval Group, Computer Science VI, Artificial Intelligence and Applied Computer Science, Julius-Maximilians University Würzburg Würzburg, Germany
| | - Hans-Christer Holmberg
- Department of Health Sciences, Swedish Winter Sports Research Centre, Mid Sweden UniversityÖstersund, Sweden; School of Sport Sciences, UiT The Arctic University of NorwayTromsø, Norway
| | - Franz Konstantin Fuss
- Department of Mechanical and Automotive Engineering, School of Engineering, RMIT University Melbourne, Australia
| | - Billy Sperlich
- Integrative and Experimental Training Science, Department of Sports Science, Institute for Sport Sciences, Julius-Maximilians University Würzburg Würzburg, Germany
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