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DOI: 10.1055/a-1686-9068
Assessment of Peak Oxygen Uptake with a Smartwatch and its Usefulness for Training of Runners
Abstract
Peak oxygen uptake (˙VO2peak) is an important factor contributing to running performance. Wearable technology may allow the assessment of ˙VO2peak more frequently and on a larger scale. We aim to i) validate the ˙VO2peak 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; ˙VO2peak: 48.6±6.8 ml∙min−1∙kg−1) visited the laboratory twice to determine their ˙VO2peak during a treadmill ramp test. Between laboratory visits, participants wore a smartwatch and performed three outdoor runs to obtain ˙VO2peak values provided by the smartwatch. The ˙VO2peak 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 ˙VO2peak 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 ˙VO2peak 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.
Key words
data-guided training - digital health - digital training - eHealth - innovation - technology - wearable - mHealthPublikationsverlauf
Eingereicht: 09. Februar 2021
Angenommen: 20. Oktober 2021
Artikel online veröffentlicht:
30. Januar 2022
© 2019. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/).
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
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References
- 1 Zinner C, Sperlich B, Wahl P. et al. Classification of selected cardiopulmonary variables of elite athletes of different age, gender, and disciplines during incremental exercise testing. SpringerPlus 2015; 4: 544
- 2 Duking P, Holmberg HC, Kunz P. et al. Intra-individual physiological response of recreational runners to different training mesocycles: A randomized cross-over study. Eur J Appl Physiol. 2020
- 3 Jones AM, Kirby BS, Clark IE. et al. Physiological demands of running at 2-hour marathon race pace. J Appl Physiol (1985) 2020; 120: 2705-2713
- 4 Milanovic Z, Sporis G, Weston M. Effectiveness of high-intensity interval training (HIT) and continuous endurance training for VO2max improvements: A systematic review and meta-analysis of controlled trials. Sports Med 2015; 45: 1469-1481
- 5 Daniels JT, Yarbrough RA, Foster C. Changes in VO2 max and running performance with training. Eur J Appl Physiol Occup Physiol 1978; 39: 249-254
- 6 Martin-Rincon M, Calbet JAL. Progress update and challenges on V.O2max testing and interpretation. Front Physiol 2020; 11: 1070
- 7 Jamnick NA, Pettitt RW, Granata C. et al. An examination and critique of current methods to determine exercise intensity. Sports Med 2020; 50: 1729-1756
- 8 Zinner C, Olstad DS, Sperlich B. Mesocycles with different training intensity distribution in recreational runners. Med Sci Sports Exerc 2018; 50: 1641-1648
- 9 De Brabandere A, Op De Beeck T, Schutte KH. et al. Data fusion of body-worn accelerometers and heart rate to predict VO2max during submaximal running. PLoS One 2018; 13: e0199509
- 10 Passler S, Bohrer J, Blochinger L. et al. Validity of wrist-worn activity trackers for estimating VO2max and energy expenditure. Int J Environ Res Public Health 2019; 16: 3037
- 11 Klepin K, Wing D, Higgins M. et al. Validity of cardiorespiratory fitness measured with fitbit compared to VO2max. Med Sci Sports Exerc 2019; 51: 2251-2256
- 12 Düking P, Fuss FK, Holmberg HC. et al. 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
- 13 Düking P, Hotho A, Holmberg HC. et al. Comparison of non-invasive individual monitoring of the training and health of athletes with commercially available wearable technologies. Front Physiol 2016; 7: 71
- 14 Van Hooren B, Goudsmit J, Restrepo J. et al. Real-time feedback by wearables in running: current approaches, challenges and suggestions for improvements. J Sports Sci 2020; 38: 214-230
- 15 Harriss DJ, MacSween A, Atkinson G. Ethical standards in sport and exercise science research: 2020 update. Int J Sports Med 2019; 40: 813-817
- 16 Atkinson G, Williamson P, Batterham AM. Issues in the determination of ‘responders’ and ‘non-responders’ in physiological research. Exp Physiol 2019; 104: 1215-1225
- 17 Garmin Ltd. Forerunner (r) 245/245 Music Benutzerhandbuch. 2019
- 18 Schaun GZ. The maximal oxygen uptake verification phase: A light at the end of the tunnel?. Sports Med Open 2017; 3: 44
- 19 Borg G. Perceived exertion as an indicator of somatic stress. Scand J Rehabil Med 1970; 2: 92-98
- 20 Macfarlane DJ, Wong P. Validity, reliability and stability of the portable Cortex Metamax 3B gas analysis system. Eur J Appl Physiol 2012; 112: 2539-2547
- 21 Firstbeat Technologies Ltd. Automated Fitness Level (VO2max) Estimation with Heart Rate and Speed Data. 2014
- 22 Winkert K, Kirsten J, Dreyhaupt J. et al. The COSMED K5 in breath-by-breath and mixing chamber mode at low to high intensities. Med Sci Sports Exerc 2020; 52: 1153-1162
- 23 Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 2016; 15: 155-163
- 24 Lee JM, Kim Y, Welk GJ. Validity of consumer-based physical activity monitors. Med Sci Sports Exerc 2014; 46: 1840-1848
- 25 McArthur D, Dumas A, Woodend K. et al. Factors influencing adherence to regular exercise in middle-aged women: a qualitative study to inform clinical practice. BMC Womens Health 2014; 14: 26-49
- 26 Robison JI, Rogers MA. Adherence to exercise programmes. Recommendations. Sports Med 1994; 17: 39-52
- 27 Lyons EJ, Lewis ZH, Mayrsohn BG. et al. Behavior change techniques implemented in electronic lifestyle activity monitors: a systematic content analysis. J Med Internet Res 2014; 16: e192
- 28 American Colleague of Sports Medicine. ACSM’s Guidelines For Exercise Testing And Prescription. Philadelphia: Lippincott Williams & Wilkins; 2013
- 29 Sarzynski MA, Rankinen T, Earnest CP. et al. Measured maximal heart rates compared to commonly used age-based prediction equations in the Heritage Family Study. Am J Hum Biol 2013; 25: 695-701