A nonlinear mixed model approach to predict energy expenditure from heart rate
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
Published inPhysiological Measurement
© 2021 Institute of Physics and Engineering in Medicine
Objective: Heart rate (HR) monitoring provides a convenient and inexpensive way to predict energy expenditure (EE) during physical activity. However, there is a lot of variation among individuals in the EE-HR relationship, which should be taken into account in predictions. The objective is to develop a model that allows the prediction of EE based on HR as accurately as possible and allows an improvement of the prediction using calibration measurements from the target individual. 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. ...
PublisherInstitute of Physics
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Research profiles, AoF
Showing items with similar title or keywords.
Jurvelin, Heidi; Tanskanen-Tervo, Minna; Kinnunen, Hannu; Santtila, Matti; Kyröläinen, Heikki (Lippincott Williams & Wilkins, 2020)Purpose: To compare training load and energy expenditure during an 8-week military BT period among individuals having different fitness level using objective measurements in an authentic environment. Methods: Thirty-four ...
Recommendations for Determining the Validity of Consumer Wearables and Smartphones for the Estimation of Energy Expenditure : Expert Statement and Checklist of the INTERLIVE Network Argent, Rob; Hetherington-Rauth, Megan; Stang, Julie; Tarp, Jakob; Ortega, Francisco B.; Molina-Garcia, Pablo; Schumann, Moritz; Bloch, Wilhelm; Cheng, Sulin; Grøntved, Anders; Brønd, Jan Christian; Ekelund, Ulf; Sardinha, Luis B.; Caulfield, Brian (Springer Science and Business Media LLC, 2022)Background Consumer wearables and smartphone devices commonly offer an estimate of energy expenditure (EE) to assist in the objective monitoring of physical activity to the general population. Alongside consumers, healthcare ...
Gao, Ying; Silvennoinen, Mika; Pesola, Arto; Kainulainen, Heikki; Cronin, Neil; Finni Juutinen, Taija (American College of Sports Medicine; Lippincott Williams & Wilkins, 2017)Purpose While merely standing up interrupts sedentary behavior, it is important to study acute metabolic responses during single bouts of sitting and standing to understand the physiological processes affecting the health ...
Sedentary Thresholds for Accelerometry-Based Mean Amplitude Deviation and Electromyography Amplitude in 7–11 Years Old Children Gao, Ying; Haapala, Eero A.; Vanhala, Anssi; Sääkslahti, Arja; Rantakokko, Merja; Laukkanen, Arto; Pesola, Arto J.; Rantalainen, Timo; Finni, Taija (Frontiers Media, 2019)We investigated the ability of energy expenditure, movement sensing, and muscle activity to discriminate sedentary and non-sedentary activities in children. Thirty-five 7–11-year-old children participated in the study. ...
Validity of traditional physical activity intensity calibration methods and the feasibility of self-paced walking and running on individualised calibration of physical activity intensity in children Haapala, Eero A.; Gao, Ying; Vanhala, Anssi; Rantalainen, Timo; Finni, Taija (Nature Publishing Group, 2020)There are no practical and valid methods for the assessment of individualised physical activity (PA) intensity in observational studies. Therefore, we investigated the validity of commonly used metabolic equivalent of tasks ...