Abstract
Modeling and predicting load courses and HR responses enables individually optimal training control. In HR controlled endurance training, load is expected to gradually decrease to keep HR levels constant due to cardiac drift. This paper analyzes if gender, time under load or progress of training influences characteristics of load controlled by HR in continuous exercise during a long-term training intervention. Nine healthy adults performed a twelve-week training intervention on a bike ergometer. During the Intensive Continuous Method, load was automatically adjusted (ALC) to keep individual HR in the range of 75% HRmax ± 5 bpm.
Load was reduced due to exceeding HR responses in all participants. Additionally, load increases were found in the first 5 and in the last 5 min of ALC. A weak influence of gender on load increases was found. No further influence of training, gender or time after onset of exercise was found. HR responses, characteristics of cardiac drift, and corresponding load adjustments were highly varying in individual participants. The findings should be integrated in HR models to improve HR control and prediction.
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Hoffmann, K. (2020). Automatic Load Control in Endurance Training. In: Lames, M., Danilov, A., Timme, E., Vassilevski, Y. (eds) Proceedings of the 12th International Symposium on Computer Science in Sport (IACSS 2019). IACSS 2019. Advances in Intelligent Systems and Computing, vol 1028. Springer, Cham. https://doi.org/10.1007/978-3-030-35048-2_16
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DOI: https://doi.org/10.1007/978-3-030-35048-2_16
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