Accuracy of Polar S410 Heart Rate Monitor to Estimate Energy Cost of Exercise

Abstract

When the predicted values of VO2max and HRmax are used, the Polar S410 HRM provides a rough estimate of EE during running, rowing, and cycling. Using the actual values for VO2max and HRmax reduced the individual error scores for both genders, but in females the mean EE was still overestimated by 12%.

Less-than-expected weight loss in normal-weight women undergoing caloric restriction and exercise is accompanied by preservation of fat-free mass and metabolic adaptations

“…The thermic effect was defined as 10% of caloric intake. 34 Exercise expenditure was obtained from heart rate monitors, 35 and non-exercise activity was assessed by triaxial accelerometry (RT3, Stayhealthy). 36,37 Weight loss as well as changes in fat and fat-free mass were predicted using the National Institute of Health Body Weight Planner, 38 which utilizes mathematical modeling of human metabolism to simulate adaptations in energy expenditure during weight loss.…”

Does Exercise Motivation Predict Engagement in Objectively Assessed Bouts of Moderate-Intensity Exercise?: A Self-Determination Theory Perspective

“…Previous research validating the AHR has demonstrated excellent estimates for total energy expenditure against indirect calorimetry during walking and running in healthy young individuals (Brage et al, 2005;Thompson, Batterham, Bock, Robson, & Stokes, 2006), and for a range of low-to-moderate intensity lifestyle activities, such as sweeping with a broom, digging and transferring sand into boxes, simulated watering of house plants, and folding and stacking laundry (Thompson et al, 2006). Further, the branched-equation modeling of simultaneous accelerometry and heart rate monitoring should improve the estimation of directly measured energy expenditure for activities involving gross arm and leg movements (e.g., weight lifting, cycling, and rowing), as the sole use of either accelerometry or heart rate telemetry has been shown to underestimate or overestimate energy expenditure during nonlocomotor or upper-body activities (Bassett et al, 2000;Crouter, Albright, & Bassett, 2004).Using the AHR, the purpose of this investigation was to examine the utility of motivation from an SDT perspective in predicting variance in moderate-intensity exercise behavior. With respect to objectively assessed exercise behavior of moderate intensity, aligned with recent physical activity guidelines (see ACSM, 2006;Haskell et al, 2007), data were extracted based on three thresholds (i) time spent in bouts of moderate exercise for ≥10 min in length, (ii) time spent in bouts of moderate exercise for ≥20 min in length, and (iii) time spent in bouts of moderate exercise for bouts ≥10 min that contribute to meeting the ACSM/AHA guidelines.…”

“…Previous research validating the AHR has demonstrated excellent estimates for total energy expenditure against indirect calorimetry during walking and running in healthy young individuals (Brage et al, 2005;Thompson, Batterham, Bock, Robson, & Stokes, 2006), and for a range of low-to-moderate intensity lifestyle activities, such as sweeping with a broom, digging and transferring sand into boxes, simulated watering of house plants, and folding and stacking laundry (Thompson et al, 2006). Further, the branched-equation modeling of simultaneous accelerometry and heart rate monitoring should improve the estimation of directly measured energy expenditure for activities involving gross arm and leg movements (e.g., weight lifting, cycling, and rowing), as the sole use of either accelerometry or heart rate telemetry has been shown to underestimate or overestimate energy expenditure during nonlocomotor or upper-body activities (Bassett et al, 2000;Crouter, Albright, & Bassett, 2004).…”

Comparisons of Heart Rate and Energy Expenditure During Exergaming in College-age Adults

“…Because the FT4 Polar Heart Rate Monitor utilizes the same regression equations for EE as the S410 model, it was used as a reliable tool for measuring HR (Crouter et al, 2004). Upon completion of the song, the participant's HR (average and maximum per session) and EE were recorded.…”

“…With an estimated 54% of college-aged students not meeting the guidelines for Moderate to Vigorous Physical Activity [MVPA; ≥40% heart rate reserve (HRR)], (American College Health Association, 2015;Crouter, Albright, & Bassett, 2004) physical inactivity is one of major behavioral concerns for their health. Entertainment Software Association (2016) stated that 63% of U.S. households have at least one person who plays video games regularly (3 hours or more per week), which contribute to the sedentary behaviors.…”