Medicine and science in sports and exercise · 2025
Initial Validation of the PATCH: An Open-Source Device Designed to Measure Energy Expenditure among Children Aged 3-8 years.
СтатьяВалидационное исследованиеПоддержка NIH: внешняя программаНазвание и аннотация: Перевод в очереди
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Ghosal Rahul, Weaver R Glenn, Parker Hannah, Burkart Sarah, McAninch Jonas, Lane Abbi D, Smith Michal T, Hill Sydney, Pate Russell R, Chandrashekhar Mvs, Armstrong Bridget
Аннотация
BACKGROUND: Wearable devices that measure energy expenditure are not designed for children. Therefore, we developed the PATCH (Platform for Accurate Tracking of Children's Health), an open-source device to measure children's energy expenditure using heart rate (HR) and acceleration. This study examines three models to estimate children's oxygen consumption using HR and acceleration compared with a criterion of indirect calorimetry.
METHODS: Fifty-two children aged 3-8 years (mean age, 6.4 ± 1.7 years; 42% female; 73% White) completed a semistructured protocol ranging in intensity from inactive (e.g., using iPad) to vigorous (e.g., running). The PATCH was attached to the chest and measured HR (photoplethysmography) and acceleration (three-axis accelerometer, ±16 g). The criterion (Cosmed K5) measured breath-by-breath oxygen uptake (V̇O 2 ; mL·kg -1 ·min -1 ). We used cross-sectional time series (CSTS) models, generalized additive mixed models (GAMM), and random forest (RF) to predict oxygen consumption from a combination of HR, acceleration, and participant characteristics (biological sex, age, weight, height). We used 10-fold cross-validation, testing each fold and training on the rest, repeated for robustness. Model fit was assessed using mean bias, mean absolute error, mean absolute percent error, and variance explained ( R2 ). We reported out-of-sample R2 values without subject-specific random effects to ensure broad applicability.
RESULTS: Mean bias values for CSTS, GAMM, and RF were -0.01, 0.01, and 0.08 mL·kg -1 ·min -1 , respectively. Mean absolute error values were 1.54, 1.56, and 1.99 mL·kg -1 ·min -1 ; mean absolute percent error was 10% for CSTS and GAMM, and 13% for RF. The CSTS explained 86% (SD, 5%) of variance, GAMM explained 86% (SD, 5%), and RF explained 81% (SD, 6%) in oxygen consumption.
CONCLUSIONS: CSTS, GAMM, and RF models provide similarly accurate estimates of children's oxygen consumption using the PATCH device compared with indirect calorimetry. Further validation in larger, free-living samples is needed.
METHODS: Fifty-two children aged 3-8 years (mean age, 6.4 ± 1.7 years; 42% female; 73% White) completed a semistructured protocol ranging in intensity from inactive (e.g., using iPad) to vigorous (e.g., running). The PATCH was attached to the chest and measured HR (photoplethysmography) and acceleration (three-axis accelerometer, ±16 g). The criterion (Cosmed K5) measured breath-by-breath oxygen uptake (V̇O 2 ; mL·kg -1 ·min -1 ). We used cross-sectional time series (CSTS) models, generalized additive mixed models (GAMM), and random forest (RF) to predict oxygen consumption from a combination of HR, acceleration, and participant characteristics (biological sex, age, weight, height). We used 10-fold cross-validation, testing each fold and training on the rest, repeated for robustness. Model fit was assessed using mean bias, mean absolute error, mean absolute percent error, and variance explained ( R2 ). We reported out-of-sample R2 values without subject-specific random effects to ensure broad applicability.
RESULTS: Mean bias values for CSTS, GAMM, and RF were -0.01, 0.01, and 0.08 mL·kg -1 ·min -1 , respectively. Mean absolute error values were 1.54, 1.56, and 1.99 mL·kg -1 ·min -1 ; mean absolute percent error was 10% for CSTS and GAMM, and 13% for RF. The CSTS explained 86% (SD, 5%) of variance, GAMM explained 86% (SD, 5%), and RF explained 81% (SD, 6%) in oxygen consumption.
CONCLUSIONS: CSTS, GAMM, and RF models provide similarly accurate estimates of children's oxygen consumption using the PATCH device compared with indirect calorimetry. Further validation in larger, free-living samples is needed.