Using Open-Source Technology to Measure Energy Expenditure and Sleep Among Children 3 to 8 Years Old

NIH RePORTER · HL · R01 · $707,223 · view on reporter.nih.gov ↗

Abstract

Assessing children’s 24-hour movement behaviors (i.e., time spent active, sedentary, and asleep) can reveal the complex and interdependent ways energy expenditure and sleep are related to health outcomes. However, assessing energy expenditure and sleep among children in free-living conditions is inherently difficult, and no single method is without limitation. A combination of heart rate and accelerometry data provides a more precise estimate of energy expenditure and sleep than either heart rate or accelerometry alone, when compared to a criterion measure of indirect calorimetry or polysomnography, respectively. Yet, devices that measure both heart rate and acceleration (such as ActiHeart or Fitbit) were not designed for children and may be distracting or uncomfortable. Moreover, nearly all devices use proprietary algorithms and do not allow access to raw signal data, and thus, are fundamentally unverifiable. Our study team has developed the PATCH, a small, open-source wearable device which integrates multiple sensors to measure heart rate and acceleration among children. The proposed project leverages the initial PATCH calibration progress and extends this work to conduct a series of studies to establish the validity of the PATCH to measure children’s energy expenditure and sleep in both laboratory and free-living conditions. The objectives of the proposed project are (1) develop estimates of energy expenditure for children aged 3-8 years, (2) measure sleep, compared to criterion polysomnography and (3) validate PATCH estimates of energy expenditure and sleep in 24-hour free-living contexts. Our long-term goal is to advance the measurement field for epidemiologic- and intervention-based studies that measure energy expenditure and sleep in the context of free-living 24-hour movement behavior. This project is innovative because it leverages off-the-shelf hardware and open-source processing. This means that results from this project will enable other researchers to b

Key facts

NIH application ID
11229791
Project number
5R01HL171295-03
Recipient
UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
Principal Investigator
Bridget R. Armstrong
Activity code
R01
Funding institute
HL
Fiscal year
2026
Award amount
$707,223
Award type
5
Project period
2023-12-01T00:00:00 → 2028-11-30T00:00:00