Simple Prediction of Metabolic Equivalents of Daily Activities Using Heart Rate Monitor without Calibration of Individuals

Abstract

Background: Heart rate (HR) during physical activity is strongly affected by the level of physical fitness. Therefore, to assess the effects of fitness, we developed predictive equations to estimate the metabolic equivalent (MET) of daily activities, which includes low intensity activities, by % HR reserve (%HRR), resting HR, and multiple physical characteristics. Methods: Forty volunteers between the ages of 21 and 55 performed 20 types of daily activities while recording HR and sampling expired gas to evaluate METs values. Multiple regression analysis was performed to develop prediction models of METs with seven potential predictors, such as %HRR, resting HR, and sex. The contributing parameters were selected based on the brute force method. Additionally, leave-one-out method was performed to validate the prediction models. Results: %HRR, resting HR, sex, and height were selected as the independent variables. %HRR showed the highest contribution in the model, while the other variables exhibited small variances. METs were estimated within a 17.3% difference for each activity, with large differences in document arrangement while sitting (+17%), ascending stairs (−8%), and descending stairs (+8%). Conclusions: The results showed that %HRR is a strong predictor for estimating the METs of daily activities. Resting HR and other variables were mild contributors. (201 words)

Dynamic of Glucose Homeostasis in Virtual Patients: A Comparison between Different Behaviors

“…Based on the works of Caballero et al [ 32 ], Gilgen et al [ 33 ] and Kang et al [ 34 ], where the physical activity intensity is related to the percentage of subject’s maximum heart rate. In Equation ( 13 ) a mathematical relationship was proposed to calculate the exercise intensity percentage above the basal level ( u ), with respect to heart rate ( , bpm) and maximum heart rate ( , bpm) of subject …”

“…The approximate value of the metabolic equivalent per task (MET) developed in each subject was calculated based on the proposed mathematical representation ( 14 ). This representation is a Gaussian function that was parameterized based on the values of the relationship between the heart rate percentage and the number of METs developed per activity performed presented in Caballero et al [ 32 ]. …”

“…Figure 2 , presents the results of the estimation based on the data presented by Caballero et al [ 32 ], where the mean square error value was 0.1669. Parameters a, b and c are considered as adjustment parameters, a = 10.25 MET, b and c are parameters related to the system input (% developed), b = 89.26% and c = 62.36% .…”

“…In this study, 5 physical activities per virtual patient were contemplated, these activities were developed after a random time no longer than 3 h after each intake. Based on Caballero et al [ 32 ], the intensities of each physical activity developed by each of the sectors analyzed were contemplated, in the case of physically active people, walks between 55 to 100 m/min were contemplated and as an activity of greater effort physical runs of 130 m/min. For sedentary people, office activities were considered, such as the use of a computer and working with documentation while the person is sitting, as an activity of greater physical effort, domestic activities such as sweeping were contemplated.…”

Effects of Exercise on Biomarkers in Health and Disease: Some New Insights with Special Focus on Extreme Exercise and Healthy Ageing

“…Obesity epidemics have led to the need to quantify the energy cost of daily activities. Caballero et al [16] analyzed several of these activities and assessed predictors of its energy cost, concluding that relative heart rate reserve was the strongest predictor, with less than 10% estimation error when ascending or descending stairs.…”