Hunt, Kenneth J.; Wang, Hanjie (2024). Identification of heart rate dynamics during treadmill and cycle ergometer exercise: the role of model zeros and dead time [version 1; peer review: awaiting peer review] F1000Research, 13, p. 894. Faculty of 1000 10.12688/f1000research.153397.1
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Background The response of heart rate to changes in exercise intensity is comprised of several dynamic modes with differing magnitudes and temporal characteristics. Investigations of empirical identification of dynamic models of heart rate showed that second-order models gave substantially and significantly better model fidelity compared to the first order case. In the present work, we aimed to reanalyse data from previous studies to more closely consider the effect of including a zero and a pure delay in the model. Methods This is a retrospective analysis of 22 treadmill (TM) and 54 cycle ergometer (CE) data sets from a total of 38 healthy participants. A linear, time-invariant plant model structure with up to two poles, a zero and a dead time is considered. Empirical estimation of the free parameters was performed using least-squares optimisation. The primary outcome measure is model fit, which is a normalised rootmean- square model error. Results A model comprising parallel connection of two first-order transfer functions, one with a dead time and one without, was found to give the highest fit (56.7 % for TM, 54.3 % for CE), whereby the non-delayed component appeared to merely capture initial transients in the data and the part with dead time likely represented the true dynamic response of heart rate to the excitation. In comparison, a simple firstorder model without dead time gave substantially lower fit than the parallel model (50.2 % for TM, 47.9 % for CE). Conclusions This preliminary analysis points to a linear first-order system with dead time as being an appropriate model for heart rate response to exercise using treadmill and cycle ergometer modalities. In order to avoid biased estimates, it is vitally important that, prior to parameter estimation and validation, careful attention is paid to data preprocessing in order to eliminate transients and trends.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
School of Engineering and Computer Science > Institute for Human Centered Engineering (HUCE) School of Engineering and Computer Science > Institute for Human Centered Engineering (HUCE) > Reha Lab School of Engineering and Computer Science |
Name: |
Hunt, Kenneth J. 0000-0002-6521-9455 and Wang, Hanjie 0000-0003-3505-3447 |
Subjects: |
T Technology > TA Engineering (General). Civil engineering (General) |
ISSN: |
2046-1402 |
Publisher: |
Faculty of 1000 |
Funders: |
[7] Swiss National Science Foundation |
Language: |
English |
Submitter: |
Kenneth James Hunt |
Date Deposited: |
14 Aug 2024 11:45 |
Last Modified: |
14 Aug 2024 11:46 |
Publisher DOI: |
10.12688/f1000research.153397.1 |
Related URLs: |
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Uncontrolled Keywords: |
Heart rate dynamics System identification Treadmill exercise Cycle ergometer exercise |
ARBOR DOI: |
10.24451/arbor.22127 |
URI: |
https://arbor.bfh.ch/id/eprint/22127 |
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