No abstract

No abstract

This paper presents a new method that integrates heart rate, respiration, and motion information obtained from a wearable sensor system to estimate energy expenditure. The system measures electrocardiography, impedance pneumography, and acceleration from upper and lower limbs. A multilayer perceptron neural network model was developed, evaluated, and compared to two existing methods, with data from 11 subjects (mean age, 27 years, range, 21–65 years) who performed a 3-h protocol including submaximal tests, simulated work tasks, and periods of rest. Oxygen uptake was measured with an indirect calorimeter as a reference, with a time resolution of 15 s. When compared to the reference, the new model showed a lower mean absolute error (MAE = 1.65 mL/kg/min, R2 = 0.92) than the two existing methods, i.e., the flex-HR method (MAE = 2.83 mL/kg/min, R2 = 0.75), which uses only heart rate, and arm-leg HR+M method (MAE = 2.12 mL/kg/min, R2 = 0.86), which uses heart rate and motion information. As indicated, this new model may, in combination with a wearable system, be useful in occupational and general health applications.

Work metabolism (WM) can be accurately estimated by oxygen consumption (VO 2 ), which is commonly assessed by heart rate (HR) in field studies. However, the VO 2 -HR relationship is influenced by individual capacity and activity characteristics. The purpose of this study was to evaluate three models for estimating WM compared with indirect calorimetry, during simulated work activities. The techniques were: the HR-Flex model; HR branched model, combining HR with hipworn accelerometers (ACC); and HR þ arm-leg ACC model, combining HR with wrist-and thighworn ACC. Twelve participants performed five simulated work activities and three submaximal tests. The HR þ arm-leg ACC model had the overall best performance with limits of agreement (LoA) of À3.94 and 2.00 mL/min/kg, while the HR-Flex model had À5.01 and 5.36 mL/min/kg and the branched model, À6.71 and 1.52 mL/min/kg. In conclusion, the HR þ arm-leg ACC model should, when feasible, be preferred in wearable systems for WM estimation.Practitioner Summary: Work with high energy demand can impair employees' health and life quality. Three models were evaluated for estimating work metabolism during simulated tasks. The model combining heart rate, wrist-and thigh-worn accelerometers showed the best accuracy. This is, when feasible, suggested for wearable systems to assess work metabolism.Abbreviations: ACC: accelerometer; EE: energy expenditure; HR: heart rate; LoA: limits of agreement; RAS: relative aerobic strain; REE: resting energy expenditure; RHR: resting heart rate; VO2: oxygen consumption; WM: work metabolism ARTICLE HISTORY