دورية أكاديمية
Predicting oxygen uptake responses during cycling at varied intensities using an artificial neural network
| العنوان: | Predicting oxygen uptake responses during cycling at varied intensities using an artificial neural network |
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| المؤلفون: | Borror Andrew, Mazzoleni Michael, Coppock James, Jensen Brian C., Wood William A., Mann Brian, Battaglini Claudio L. |
| المصدر: | Biomedical Human Kinetics, Vol 11, Iss 1, Pp 60-68 (2019) |
| بيانات النشر: | Sciendo, 2019. |
| سنة النشر: | 2019 |
| المجموعة: | LCC:Sports medicine LCC:Physiology |
| مصطلحات موضوعية: | vo2, cardiorespiratory fitness, heart rate, machine learning, prediction model, Sports medicine, RC1200-1245, Physiology, QP1-981 |
| الوصف: | Study aim: Oxygen Uptake (VO2) is avaluable metric for the prescription of exercise intensity and the monitoring of training progress. However, VO2 is difficult to assess in anon-laboratory setting. Recently, an artificial neural network (ANN) was used to predict VO2 responses during aset walking protocol on the treadmill [9]. The purpose of the present study was to test the ability of an ANN to predict VO2 responses during cycling at self-selected intensities using Heart Rate (HR), time derivative of HR, power output, cadence, and body mass data. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2080-2234 |
| Relation: | https://doaj.org/toc/2080-2234 |
| DOI: | 10.2478/bhk-2019-0008 |
| URL الوصول: | https://doaj.org/article/0ca1425eed3b48548469422c93505f6a |
| رقم الأكسشن: | edsdoj.0ca1425eed3b48548469422c93505f6a |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20802234 |
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| DOI: | 10.2478/bhk-2019-0008 |