A1 Journal article (refereed)
A nonlinear mixed model approach to predict energy expenditure from heart rate (2021)
Kortelainen, L., Helske, J., Finni, T., Mehtätalo, L., Tikkanen, O., & Kärkkäinen, S. (2021). A nonlinear mixed model approach to predict energy expenditure from heart rate. Physiological Measurement, 42(3), Article 035001. https://doi.org/10.1088/1361-6579/abea25
JYU authors or editors
Publication details
All authors or editors: Kortelainen, Lauri; Helske, Jouni; Finni, Taija; Mehtätalo, Lauri; Tikkanen, Olli; Kärkkäinen, Salme
Journal or series: Physiological Measurement
ISSN: 0967-3334
eISSN: 1361-6579
Publication year: 2021
Volume: 42
Issue number: 3
Article number: 035001
Publisher: Institute of Physics
Publication country: United Kingdom
Publication language: English
DOI: https://doi.org/10.1088/1361-6579/abea25
Publication open access: Not open
Publication channel open access:
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/77613
Abstract
Approach: We propose a nonlinear (logistic) mixed model for EE and HR measurements and an approach to calibrate the model for a new person who does not belong to the data set used to estimate the model. The calibration utilizes the estimated model parameters and calibration measurements of HR and EE from the person in question. We compare the results of the logistic mixed model with a simpler linear mixed model for which the calibration is easier to perform.
Main results: We show that the calibration is beneficial already with only one pair of measurements on HR and EE. That is an important benefit over an individual-level model fitting which requires a larger number of measurements. Moreover, we present an algorithm for calculating the confidence and prediction intervals of the calibrated predictions. The analysis was based on up to eleven pairs of EE and HR measurements from each of 54 individuals of a heterogeneous group of people, who performed a maximal treadmill test.
Significance: The proposed method allows accurate energy expenditure predictions based on only a few calibration measurements from a new individual without access to the original dataset, thus making the approach viable for example on wearable computers.
Keywords: energy consumption (metabolism); physical activity; measuring methods; pulse; heart rate monitors; calibration; statistical models
Free keywords: energy expenditure; heart rate monitoring; individual calibration; logistic mixed model; physical activity
Contributing organizations
Related projects
- Competitive funding to strengthen universities’ research profiles. Profiling actions at the JYU, round 3
- Hämäläinen, Keijo
- Research Council of Finland
Ministry reporting: Yes
Reporting Year: 2021
JUFO rating: 1