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수영 운동시 심박수를 이용한 에너지소비량 추정식의 타당도

Validity of Energy Expenditure Estimation Equation using Heart Rate in Swimming

이용희|박세정|이미현
한국운동생리학회|2023.05|운동과학 (Exercise Science)|제32권 제2호|pp. 215-221

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키워드

Heart rateCross validationEquationFront crawl

초록

PURPOSE: The purpose of this study was to develop an estimation equation that predicts energy expenditure (EE) during swimming exercise based on heart rate (HR). And, we also evaluated the validation for field application and compare it with the existing speed-based swimming EE equation. METHODS: A total of 63 healthy adults (ages 19-49 years) who could swim at various speeds were conveniently sampled. The experiment was conducted in an indoor 25 m pool. The protocol (measurement of individual best performance, 0.4, 0.6, 0.8, <1.0 m/s) was performed for 4 minutes each according to the level of the individual. EE was evaluated using a portable respiratory gas analyzer (K4b2 , Cosmed, Italy) and a swimming snorkel (Aqua Trainer Snorkel, Cosmed, Italy). HR was measured using a waterproof HR chest strap (Polar Electro Oy, Polar V800, Finland). A dummy control regression analysis was performed with the EE measured by the respiratory gas analyzer as the dependent variables and sex, age, height, weight, and HR during exercise as independent variables. RESULTS: The participants in this study were randomly divided into two groups; the equation development (n=42) and the validation group (n=21). The estimation of EE during swimming exercise is as follows; EEm=-18.197-1.966 (Gender: men=0, women=1)+.027 (Age, year)+.073 (Height, cm)+.008 (Weight, kg)+.092 (HR, bpm) R2=78% (adj. R2=77.2%). The HR-based swimming EE estimation equation (mean=0.7, difference=6.7) verified by the Bland & Altman plot showed the lowest error, followed by Monpetit (mean=1.6, difference=11.6) and Costill (Mean=0.4, difference=16.7). CONCLUSIONS: The EE during swimming was developed using physical characteristics such as sex, age, height, weight and HR in this study. This swimming EE equation might be used for commercial wearable devices.

Abstract

PURPOSE: The purpose of this study was to develop an estimation equation that predicts energy expenditure (EE) during swimming exercise based on heart rate (HR). And, we also evaluated the validation for field application and compare it with the existing speed-based swimming EE equation. METHODS: A total of 63 healthy adults (ages 19-49 years) who could swim at various speeds were conveniently sampled. The experiment was conducted in an indoor 25 m pool. The protocol (measurement of individual best performance, 0.4, 0.6, 0.8, <1.0 m/s) was performed for 4 minutes each according to the level of the individual. EE was evaluated using a portable respiratory gas analyzer (K4b2 , Cosmed, Italy) and a swimming snorkel (Aqua Trainer Snorkel, Cosmed, Italy). HR was measured using a waterproof HR chest strap (Polar Electro Oy, Polar V800, Finland). A dummy control regression analysis was performed with the EE measured by the respiratory gas analyzer as the dependent variables and sex, age, height, weight, and HR during exercise as independent variables. RESULTS: The participants in this study were randomly divided into two groups; the equation development (n=42) and the validation group (n=21). The estimation of EE during swimming exercise is as follows; EEm=-18.197-1.966 (Gender: men=0, women=1)+.027 (Age, year)+.073 (Height, cm)+.008 (Weight, kg)+.092 (HR, bpm) R2=78% (adj. R2=77.2%). The HR-based swimming EE estimation equation (mean=0.7, difference=6.7) verified by the Bland & Altman plot showed the lowest error, followed by Monpetit (mean=1.6, difference=11.6) and Costill (Mean=0.4, difference=16.7). CONCLUSIONS: The EE during swimming was developed using physical characteristics such as sex, age, height, weight and HR in this study. This swimming EE equation might be used for commercial wearable devices.

참고문헌 (29)

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