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Düking P, Ruf L, Altmann S, Thron M, Kunz P, Sperlich B. Assessment of Maximum Oxygen Uptake in Elite Youth Soccer Players: A Comparative Analysis of Smartwatch Technology, Yoyo Intermittent Recovery Test 2, and Respiratory Gas Analysis. J Sports Sci Med 2024; 23:351-357. [PMID: 38841641 PMCID: PMC11149075 DOI: 10.52082/jssm.2024.351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 04/19/2024] [Indexed: 06/07/2024]
Abstract
The maximum oxygen uptake (VO2max) is a critical factor for endurance performance in soccer. Novel wearable technology may allow frequent assessment of V̇O2max during non-fatiguing warm-up runs of soccer players with minimal interference to soccer practice. The aim of this study was to assess the validity of VO2max provided by a consumer grade smartwatch (Garmin Forerunner 245, Garmin, Olathe, USA, Software:13.00) and the YoYo Intermittent Recovery Run 2 (YYIR2) by comparing it with respiratory gas analysis. 24 trained male youth soccer players performed different tests to assess VO2max: i) a treadmill test employing respiratory gas analysis, ii) YYIR2 and iii) during a non-fatiguing warm-up run of 10 min wearing a smartwatch as recommended by the device-manufacturer on 3 different days within 2 weeks. As the device-manufacturer indicates that validity of smartwatch-derived VO2max may differ with an increase in runs, 16 players performed a second run with the smartwatch to test this claim. The main evidence revealed that the smartwatch showed an ICC of 0.37 [95% CI: -0.25; 0.71] a mean absolute percentage error (MAPE) of 5.58% after one run, as well as an ICC of 0.54 [95% CI: -0.3; 8.4] and a MAPE of 1.06% after the second run with the smartwatch. The YYIR2 showed an ICC of 0.17 [95% CI: -5.7; 0.6]; and MAPE of 4.2%. When using the smartwatch for VO2max assessment in a non-fatiguing run as a warm-up, as suggested by the device manufacturer before soccer practice, the MAPE diminishes after two runs. Therefore, for more accurate VO2max assessment with the smartwatch, we recommend to perform at least two runs to reduce the MAPE and enhance the validity of the findings.
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Affiliation(s)
- Peter Düking
- Department of Sports Science and Movement Pedagogy, Technische Universität Braunschweig, Braunschweig, Germany
| | - Ludwig Ruf
- TSG ResearchLab gGmbH, Zuzenhausen, Germany
| | - Stefan Altmann
- TSG ResearchLab gGmbH, Zuzenhausen, Germany
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Maximiliane Thron
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Philipp Kunz
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
| | - Billy Sperlich
- Integrative and Experimental Exercise Science, Department of Sport Science, University of Würzburg, Würzburg, Germany
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Van Hooren B, Plasqui G, Meijer K. The Effect of Wearable-Based Real-Time Feedback on Running Injuries and Running Performance: A Randomized Controlled Trial. Am J Sports Med 2024; 52:750-765. [PMID: 38287728 PMCID: PMC10905988 DOI: 10.1177/03635465231222464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 11/06/2023] [Indexed: 01/31/2024]
Abstract
BACKGROUND Running technique and running speed are considered important risk factors for running injuries. Real-time feedback on running technique and running speed by wearables may help reduce injury risk. PURPOSE To investigate whether real-time feedback on spatiotemporal metrics and relative speed by commercially available pressure-sensitive insoles would reduce running injuries and improve running performance compared with no real-time feedback. STUDY DESIGN Randomized controlled trial; Level of evidence, 1. METHODS A total of 220 recreational runners were randomly assigned into the intervention and control groups. Both groups received pressure-sensitive insoles, but only the intervention group received real-time feedback on spatiotemporal metrics and relative speed. The feedback aimed to reduce loading on the joint/segment estimated to exhibit the highest load. Injury rates were compared between the groups using Cox regressions. Secondary outcomes compared included injury severity, the proportion of runners with multiple injuries, changes in self-reported personal best times and motivation (Behavioral Regulation in Exercise Questionnaire-2), and interest in continuing wearable use after study completion. RESULTS A total of 160 participants (73%) were included in analyses of the primary outcome. Intention-to-treat analysis showed no significant difference in injury rate between the groups (Hazard ratio [HR], 1.11; P = .70). This was expected, as 53 of 160 (33%) participants ended up in the unassigned group because they used incorrect wearable settings, nullifying any interventional effects. As-treated analysis showed a significantly lower injury rate among participants receiving real-time feedback (HR, 0.53; P = .03). Similarly, the first-time injury severity was significantly lower (-0.43; P = .042). Per-protocol analysis showed no significant differences in injury rates, but the direction favored the intervention group (HR, 0.67; P = .30). There were no significant differences in the proportion of patients with multiple injuries (HR, 0.82; P = .40) or changes in running performance (3.07%; P = .26) and motivation. Also, ~60% of the participants who completed the study showed interest in continuing wearable use. CONCLUSION Real-time feedback on spatiotemporal metrics and relative speed provided by commercially available instrumented insoles may reduce the rate and severity of injuries in recreational runners. Feedback did not influence running performance and exercise motivation. REGISTRATION NL8472 (Dutch Trial Register).
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Affiliation(s)
- Bas Van Hooren
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Department of Nutrition and Movement Sciences, Maastricht, the Netherlands
| | - Guy Plasqui
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Department of Nutrition and Movement Sciences, Maastricht, the Netherlands
| | - Kenneth Meijer
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Department of Nutrition and Movement Sciences, Maastricht, the Netherlands
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Van Hooren B, Souren T, Bongers BC. Accuracy of respiratory gas variables, substrate, and energy use from 15 CPET systems during simulated and human exercise. Scand J Med Sci Sports 2024; 34:e14490. [PMID: 37697640 DOI: 10.1111/sms.14490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/07/2023] [Accepted: 08/25/2023] [Indexed: 09/13/2023]
Abstract
PURPOSE Various systems are available for cardiopulmonary exercise testing (CPET), but their accuracy remains largely unexplored. We evaluate the accuracy of 15 popular CPET systems to assess respiratory variables, substrate use, and energy expenditure during simulated exercise. Cross-comparisons were also performed during human cycling experiments (i.e., verification of simulation findings), and between-session reliability was assessed for a subset of systems. METHODS A metabolic simulator was used to simulate breath-by-breath gas exchange, and the values measured by each system (minute ventilation [V̇E], breathing frequency [BF], oxygen uptake [V̇O2 ], carbon dioxide production [V̇CO2 ], respiratory exchange ratio [RER], energy from carbs and fats, and total energy expenditure) were compared to the simulated values to assess the accuracy. The following manufacturers (system) were assessed: COSMED (Quark CPET, K5), Cortex (MetaLyzer 3B, MetaMax 3B), Vyaire (Vyntus CPX, Oxycon Pro), Maastricht Instruments (Omnical), MGC Diagnostics (Ergocard Clinical, Ergocard Pro, Ultima), Ganshorn/Schiller (PowerCube Ergo), Geratherm (Ergostik), VO2master (VO2masterPro), PNOĒ (PNOĒ), and Calibre Biometrics (Calibre). RESULTS Absolute percentage errors during the simulations ranged from 1.15%-44.3% for V̇E, 1.05-3.79% for BF, 1.10%-13.3% for V̇O2 , 1.07%-18.3% for V̇CO2 , 0.62%-14.8% for RER, 5.52%-99.0% for Kcal from carbs, 5.13%-133% for Kcal from fats, and 0.59%-12.1% for total energy expenditure. Between-session variation ranged from 0.86%-21.0% for V̇O2 and 1.14%-20.2% for V̇CO2 , respectively. CONCLUSION The error of respiratory gas variables, substrate, and energy use differed substantially between systems, with only a few systems demonstrating a consistent acceptable error. We extensively discuss the implications of our findings for clinicians, researchers and other CPET users.
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Affiliation(s)
- Bas Van Hooren
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Tjeu Souren
- Independent Consultant, Utrecht, The Netherlands
| | - Bart C Bongers
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
- Department of Surgery, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
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Van Hooren B, Mennen B, Gronwald T, Bongers BC, Rogers B. Correlation properties of heart rate variability to assess the first ventilatory threshold and fatigue in runners. J Sports Sci 2023:1-10. [PMID: 37916488 DOI: 10.1080/02640414.2023.2277034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 10/22/2023] [Indexed: 11/03/2023]
Abstract
PURPOSE The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA-a1) of heart rate variability (HRV) has shown potential to delineate the first ventilatory threshold (VT1). The aims of this study were to investigate the accuracy of this method for VT1 determination in runners using a consumer grade chest belt and to explore the effects of acute fatigue. METHODS We compared oxygen uptake (V̇O2) and heart rate (HR) at gas exchange VT1 to V̇O2 and HR at a DFA-a1 value of 0.75. Gas exchange and HRV data were obtained from 14 individuals during a treadmill run involving two incremental ramps. Agreement was assessed using Bland-Altman analysis and linear regression. RESULTS Bland-Altman analysis between gas exchange and HRV V̇O2 and HR at VT1 during the first ramp showed a mean (95% limits of agreement) bias of -0.5 (-6.8 to 5.8) ml∙kg-1∙min-1, and -0.9 (-12.2 to 10.5) beats∙min-1, with R2 of 0.83 and 0.56, respectively. During the second ramp, the differences were -7.3 (-18.1 to 3.5) ml∙kg-1∙min-1 and -12.3 (-30.4 to 5.9) beats∙min-1, with R2 of 0.62 and 0.43, respectively. CONCLUSION A chest-belt derived DFA-a1 of 0.75 is closely related to gas exchange VT1, with the variability in accuracy at an individual level being similar to gas exchange methods. This suggests this to be a useful method for exercise intensity demarcation. The altered relationship during the second ramp indicates that DFA-a1 is only able to accurately demarcate exercise intensity thresholds in a non-fatigued state, but also opens opportunities for fatigue-based training prescription.
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Affiliation(s)
- 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
| | - Bram Mennen
- 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
| | - Thomas Gronwald
- MSH Medical School Hamburg, Institute of Interdisciplinary Exercise Science and Sports Medicine, Hamburg, Germany
| | - Bart C Bongers
- 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
- Department of Surgery, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Bruce Rogers
- College of Medicine, University of Central Florida, Orlando, Florida, USA
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Ye X, Sun M, Yu S, Yang J, Liu Z, Lv H, Wu B, He J, Wang X, Huang L. Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study. JMIR Mhealth Uhealth 2023; 11:e43340. [PMID: 37410528 PMCID: PMC10360014 DOI: 10.2196/43340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/11/2022] [Accepted: 06/09/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Cardiorespiratory fitness plays an important role in coping with hypoxic stress at high altitudes. However, the association of cardiorespiratory fitness with the development of acute mountain sickness (AMS) has not yet been evaluated. Wearable technology devices provide a feasible assessment of cardiorespiratory fitness, which is quantifiable as maximum oxygen consumption (VO2max) and may contribute to AMS prediction. OBJECTIVE We aimed to determine the validity of VO2max estimated by the smartwatch test (SWT), which can be self-administered, in order to overcome the limitations of clinical VO2max measurements. We also aimed to evaluate the performance of a VO2max-SWT-based model in predicting susceptibility to AMS. METHODS Both SWT and cardiopulmonary exercise test (CPET) were performed for VO2max measurements in 46 healthy participants at low altitude (300 m) and in 41 of them at high altitude (3900 m). The characteristics of the red blood cells and hemoglobin levels in all the participants were analyzed by routine blood examination before the exercise tests. The Bland-Altman method was used for bias and precision assessment. Multivariate logistic regression was performed to analyze the correlation between AMS and the candidate variables. A receiver operating characteristic curve was used to evaluate the efficacy of VO2max in predicting AMS. RESULTS VO2max decreased after acute high altitude exposure, as measured by CPET (25.20 [SD 6.46] vs 30.17 [SD 5.01] at low altitude; P<.001) and SWT (26.17 [SD 6.71] vs 31.28 [SD 5.17] at low altitude; P<.001). Both at low and high altitudes, VO2max was slightly overestimated by SWT but had considerable accuracy as the mean absolute percentage error (<7%) and mean absolute error (<2 mL·kg-1·min-1), with a relatively small bias compared with VO2max-CPET. Twenty of the 46 participants developed AMS at 3900 m, and their VO2max was significantly lower than that of those without AMS (CPET: 27.80 [SD 4.55] vs 32.00 [SD 4.64], respectively; P=.004; SWT: 28.00 [IQR 25.25-32.00] vs 32.00 [IQR 30.00-37.00], respectively; P=.001). VO2max-CPET, VO2max-SWT, and red blood cell distribution width-coefficient of variation (RDW-CV) were found to be independent predictors of AMS. To increase the prediction accuracy, we used combination models. The combination of VO2max-SWT and RDW-CV showed the largest area under the curve for all parameters and models, which increased the area under the curve from 0.785 for VO2max-SWT alone to 0.839. CONCLUSIONS Our study demonstrates that the smartwatch device can be a feasible approach for estimating VO2max. In both low and high altitudes, VO2max-SWT showed a systematic bias toward a calibration point, slightly overestimating the proper VO2max when investigated in healthy participants. The SWT-based VO2max at low altitude is an effective indicator of AMS and helps to better identify susceptible individuals following acute high-altitude exposure, particularly by combining the RDW-CV at low altitude. TRIAL REGISTRATION Chinese Clinical Trial Registry ChiCTR2200059900; https://www.chictr.org.cn/showproj.html?proj=170253.
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Affiliation(s)
- Xiaowei Ye
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Mengjia Sun
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Shiyong Yu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jie Yang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Zhen Liu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Hailin Lv
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Boji Wu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jingyu He
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xuhong Wang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Lan Huang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
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Tandon A, Nguyen HH, Avula S, Seshadri DR, Patel A, Fares M, Baloglu O, Amdani S, Jafari R, Inan OT, Drummond CK. Wearable Biosensors in Congenital Heart Disease: Needs to Advance the Field. JACC. ADVANCES 2023; 2:100267. [PMID: 37152621 PMCID: PMC10162770 DOI: 10.1016/j.jacadv.2023.100267] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 12/19/2022] [Accepted: 01/03/2023] [Indexed: 05/09/2023]
Abstract
Traditional measures of clinical status and physiology have generally been based in health care settings, episodic, short in duration, and performed at rest. Wearable biosensors provide an opportunity to obtain continuous non-invasive physiologic data from patients with congenital heart disease (CHD) in the real-world setting, over longer durations, and across varying levels of activity. However, there are significant technical limitations to the use of wearable biosensors in CHD. Here, we review current applications of wearable biosensors in CHD; how clinical and research uses of wearable biosensors must consider various CHD physiologies; the technical challenges in developing wearable biosensors for CHD; and special considerations for digital biomarkers in CHD.
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Affiliation(s)
- Animesh Tandon
- Department of Pediatric Cardiology, Pediatric Institute, Cleveland Clinic Children’s, Cleveland, Ohio, USA
- Cleveland Clinic Children's Center for Artificial Intelligence (C4AI), Cleveland Clinic Children’s, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Case School of Engineering at Case Western Reserve University, Cleveland, Ohio, USA
| | - Hoang H. Nguyen
- Division of Cardiology, Department of Pediatrics, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Sravani Avula
- Division of Cardiology, Department of Pediatrics, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Dhruv R. Seshadri
- Department of Orthopaedics, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Akash Patel
- Department of Pediatric Cardiology, Pediatric Institute, Cleveland Clinic Children’s, Cleveland, Ohio, USA
| | - Munes Fares
- Division of Cardiology, Department of Pediatrics, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Orkun Baloglu
- Cleveland Clinic Children's Center for Artificial Intelligence (C4AI), Cleveland Clinic Children’s, Cleveland, Ohio, USA
- Department of Critical Care, Pediatric Institute, Cleveland Clinic Children’s, Cleveland, Ohio, USA
| | - Shahnawaz Amdani
- Department of Pediatric Cardiology, Pediatric Institute, Cleveland Clinic Children’s, Cleveland, Ohio, USA
- Cleveland Clinic Children's Center for Artificial Intelligence (C4AI), Cleveland Clinic Children’s, Cleveland, Ohio, USA
| | - Roozbeh Jafari
- Departments of Biomedical Engineering, Computer Science and Electrical Engineering, Texas A&M University, College Station, Texas, USA
| | - Omer T. Inan
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Colin K. Drummond
- Department of Biomedical Engineering, Case School of Engineering at Case Western Reserve University, Cleveland, Ohio, USA
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