Hoffmann, K. ; Wiemeyer, J. (2017)
Predicting Short-Term HR Response to Varying Training Loads Using Exponential Equations.
In: International Journal of Computer Science in Sport, 16 (2)
doi: 10.1515/ijcss-2017-0011
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
Aim of this study was to test whether a monoexponential formula is appropriate to analyze and predict individual responses to the change of load bouts online during training. Therefore, 234 heart rate (HR) data sets obtained from extensive interval protocols of four participants during a twelve-week training intervention on a bike ergometer were analyzed. First, HR for each interval was approximated using a monoexponential formula. HR at onset of exercise (HRstart), HR induced by load (HRsteady) and the slope of HR (c) were analyzed. Furthermore, a calculation routine incrementally predicted HRsteady using measured HR data after onset of exercise. Validity of original and approximated data sets were very high (r² =0.962, SD =0.025; Max =0.991, Min =0.702). HRstart was significantly different between all participants (one exception). HRsteady was similar in all participants. Parameter c was independent of the duration of intervention and intervals regarding one training session but was significantly different in all participants (one exception). Final HR was correctly predicted on average after 58.8 s (SD = 34.77, Max =150 s, Min =30 s) based on a difference criteria of less than 5 bpm. In 3 participants, HRsteady was predicted correctly in 142 out of 175 courses (81.1%).
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Hoffmann, K. ; Wiemeyer, J. |
| Art des Eintrags: | Bibliographie |
| Titel: | Predicting Short-Term HR Response to Varying Training Loads Using Exponential Equations |
| Sprache: | Englisch |
| Publikationsjahr: | 2017 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | International Journal of Computer Science in Sport |
| Jahrgang/Volume einer Zeitschrift: | 16 |
| (Heft-)Nummer: | 2 |
| DOI: | 10.1515/ijcss-2017-0011 |
| URL / URN: | https://doi.org/10.1515/ijcss-2017-0011 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Aim of this study was to test whether a monoexponential formula is appropriate to analyze and predict individual responses to the change of load bouts online during training. Therefore, 234 heart rate (HR) data sets obtained from extensive interval protocols of four participants during a twelve-week training intervention on a bike ergometer were analyzed. First, HR for each interval was approximated using a monoexponential formula. HR at onset of exercise (HRstart), HR induced by load (HRsteady) and the slope of HR (c) were analyzed. Furthermore, a calculation routine incrementally predicted HRsteady using measured HR data after onset of exercise. Validity of original and approximated data sets were very high (r² =0.962, SD =0.025; Max =0.991, Min =0.702). HRstart was significantly different between all participants (one exception). HRsteady was similar in all participants. Parameter c was independent of the duration of intervention and intervals regarding one training session but was significantly different in all participants (one exception). Final HR was correctly predicted on average after 58.8 s (SD = 34.77, Max =150 s, Min =30 s) based on a difference criteria of less than 5 bpm. In 3 participants, HRsteady was predicted correctly in 142 out of 175 courses (81.1%). |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 700 Künste und Unterhaltung > 796 Sport |
| Fachbereich(e)/-gebiet(e): | 03 Fachbereich Humanwissenschaften 03 Fachbereich Humanwissenschaften > Institut für Sportwissenschaft |
| Hinterlegungsdatum: | 02 Aug 2024 12:33 |
| Letzte Änderung: | 02 Aug 2024 12:33 |
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| Suche nach Titel in: | TUfind oder in Google |
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Predicting Short-Term HR Response to Varying Training Loads Using Exponential Equations. (deposited 17 Dez 2017 20:55)
- Predicting Short-Term HR Response to Varying Training Loads Using Exponential Equations. (deposited 02 Aug 2024 12:33) [Gegenwärtig angezeigt]
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