TY - JOUR
T1 - Estimating the relationship between heart rate and power output for short term cycling exercises
AU - Meyer, Daniel
AU - Dungs, Carolin
AU - Senner, Veit
N1 - Publisher Copyright:
© 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
PY - 2015
Y1 - 2015
N2 - In this paper, we statistically analyze a dataset of performance diagnostics of 1940 subjects to examine the influence of different physical characteristics on the relationship between heart rate and power output. Five characteristics - the cyclist's height, weight, age, sex and fitness level - were identified as parameters for the model. Next, we divide the dataset into different subsets according to the statistical analysis and modify formulas found in the literature to estimate the maximum heart rate as well as the maximum power output for each group. Then, we derive formulas from the dataset to estimate the heart rate and power output at the individual anaerobic threshold (IAT) as well as the heart rate at low workload. A linear curve between these points describes the immediate relationship between heart rate and power. We compared the results of the adapted formulas to the results of the original formulas for experimental data of 15 subjects. The adapted formulas show better results in terms of mean absolute error (MAE) and sum of squared residuals (SSR) for estimating the maximum power output, but no improvement in estimating the maximum heart rate. The heart rate at IAT is predicted with a MAE of 9 beats per minute (bpm) and heart rate for low intensity with a MAE of 13 bpm. Power at the IAT is predicted with a MAE of 22 Watts.
AB - In this paper, we statistically analyze a dataset of performance diagnostics of 1940 subjects to examine the influence of different physical characteristics on the relationship between heart rate and power output. Five characteristics - the cyclist's height, weight, age, sex and fitness level - were identified as parameters for the model. Next, we divide the dataset into different subsets according to the statistical analysis and modify formulas found in the literature to estimate the maximum heart rate as well as the maximum power output for each group. Then, we derive formulas from the dataset to estimate the heart rate and power output at the individual anaerobic threshold (IAT) as well as the heart rate at low workload. A linear curve between these points describes the immediate relationship between heart rate and power. We compared the results of the adapted formulas to the results of the original formulas for experimental data of 15 subjects. The adapted formulas show better results in terms of mean absolute error (MAE) and sum of squared residuals (SSR) for estimating the maximum power output, but no improvement in estimating the maximum heart rate. The heart rate at IAT is predicted with a MAE of 9 beats per minute (bpm) and heart rate for low intensity with a MAE of 13 bpm. Power at the IAT is predicted with a MAE of 22 Watts.
KW - Electric bicycles
KW - Heart rate modeling
KW - Human physiology
KW - Power output estimation
UR - http://www.scopus.com/inward/record.url?scp=84945550065&partnerID=8YFLogxK
U2 - 10.1016/j.proeng.2015.07.206
DO - 10.1016/j.proeng.2015.07.206
M3 - Conference article
AN - SCOPUS:84945550065
SN - 1877-7058
VL - 112
SP - 237
EP - 243
JO - Procedia Engineering
JF - Procedia Engineering
T2 - 7th Asia-Pacific Congress on Sports Technology, APCST 2015
Y2 - 23 September 2015 through 25 September 2015
ER -