دورية أكاديمية
Data fusion of body-worn accelerometers and heart rate to predict VO2max during submaximal running.
| العنوان: | Data fusion of body-worn accelerometers and heart rate to predict VO2max during submaximal running. |
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| المؤلفون: | De Brabandere A; Department of Computer Science, KU Leuven, Leuven, Belgium., Op De Beéck T; Department of Computer Science, KU Leuven, Leuven, Belgium., Schütte KH; Department of Movement Sciences, KU Leuven, Leuven, Belgium.; Department of Sport Sciences, Stellenbosch University, Stellenbosch, South Africa., Meert W; Department of Computer Science, KU Leuven, Leuven, Belgium., Vanwanseele B; Department of Movement Sciences, KU Leuven, Leuven, Belgium., Davis J; Department of Computer Science, KU Leuven, Leuven, Belgium. |
| المصدر: | PloS one [PLoS One] 2018 Jun 29; Vol. 13 (6), pp. e0199509. Date of Electronic Publication: 2018 Jun 29 (Print Publication: 2018). |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: San Francisco, CA : Public Library of Science |
| مواضيع طبية MeSH: | Exercise/*physiology , Heart Rate/*physiology , Running/*physiology, Acceleration ; Humans ; Linear Models ; Models, Theoretical ; Oxygen/metabolism |
| مستخلص: | Maximal oxygen uptake (VO2max) is often used to assess an individual's cardiorespiratory fitness. However, measuring this variable requires an athlete to perform a maximal exercise test which may be impractical, since this test requires trained staff and specialized equipment, and may be hard to incorporate regularly into training programs. The aim of this study is to develop a new model for predicting VO2max by exploiting its relationship to heart rate and accelerometer features extracted during submaximal running. To do so, we analyzed data collected from 31 recreational runners (15 men and 16 women) aged 19-26 years who performed a maximal incremental test on a treadmill. During this test, the subjects' heart rate and acceleration at three locations (the upper back, the lower back and the tibia) were continuously measured. We extracted a wide variety of features from the measurements of the warm-up and the first three stages of the test and employed a data-driven approach to select the most relevant ones. Furthermore, we evaluated the utility of combining different types of features. Empirically, we found that combining heart rate and accelerometer features resulted in the best model with a mean absolute error of 2.33 ml ⋅ kg-1 ⋅ min-1 and a mean absolute percentage error of 4.92%. The model includes four features: gender, body mass, the inverse of the average heart rate and the inverse of the variance of the total tibia acceleration during the warm-up stage of the treadmill test. Our model provides a practical tool for recreational runners in the same age range to estimate their VO2max from submaximal running on a treadmill. It requires two body-worn sensors: a heart rate monitor and an accelerometer positioned on the tibia. Competing Interests: The authors have declared that no competing interests exist. |
| References: | Res Q Exerc Sport. 2005 Dec;76(4):426-32. (PMID: 16739680) J Appl Physiol (1985). 2016 May 1;120(9):1082-96. (PMID: 26940653) J Sports Med Phys Fitness. 2012 Oct;52(5):465-73. (PMID: 22976732) Comput Biol Med. 2016 Dec 1;79:182-192. (PMID: 27810624) Fed Proc. 1987 Apr;46(5):1824-9. (PMID: 3493922) J Rehabil Res Dev. 2009;46(2):277-86. (PMID: 19533541) Med Sci Sports Exerc. 1982;14(5):377-81. (PMID: 7154893) J Sports Sci. 1996 Aug;14(4):321-7. (PMID: 8887211) Med Sci Sports Exerc. 2005 May;37(5):872-6. (PMID: 15870644) Med Sci Sports Exerc. 1991 Aug;23(8):966-73. (PMID: 1956273) J Sports Med Phys Fitness. 2012 Aug;52(4):337-43. (PMID: 22828454) J Appl Physiol (1985). 1991 Feb;70(2):683-7. (PMID: 2022559) Exerc Sport Sci Rev. 1995;23:25-63. (PMID: 7556353) PLoS One. 2009 Oct 06;4(10):e7355. (PMID: 19806216) J Appl Physiol (1985). 2001 Jul;91(1):451-8. (PMID: 11408463) Res Q Exerc Sport. 2000 Jun;71 Suppl 2:30-6. (PMID: 25680010) J Sci Med Sport. 2013 May;16(3):271-5. (PMID: 22883597) J Phys Act Health. 2013 Feb;10(2):280-7. (PMID: 22821953) Med Sci Sports Exerc. 2010 Jan;42(1):179-86. (PMID: 20010115) PLoS One. 2015 Oct 30;10(10):e0141957. (PMID: 26517261) Med Sci Sports Exerc. 2006 Aug;38(8):1510-4. (PMID: 16888467) Clin Biomech (Bristol, Avon). 1998 Jun;13(4-5):320-327. (PMID: 11415803) J Korean Med Sci. 2017 Dec;32(12):1947-1952. (PMID: 29115075) Med Sci Sports Exerc. 1997 Mar;29(3):415-23. (PMID: 9139183) Res Q Exerc Sport. 2000 Jun;71 Suppl 2:21-9. (PMID: 25680009) |
| سلسلة جزيئية: | figshare 10.6084/m9.figshare.5729043 |
| المشرفين على المادة: | S88TT14065 (Oxygen) |
| تواريخ الأحداث: | Date Created: 20180630 Date Completed: 20190411 Latest Revision: 20190411 |
| رمز التحديث: | 20231215 |
| مُعرف محوري في PubMed: | PMC6025864 |
| DOI: | 10.1371/journal.pone.0199509 |
| PMID: | 29958282 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0199509 |