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Accelerometer-based methods for energy expenditure using the smartphone

: Carneiro, Susana; Silva, Joana; Aguiar, Bruno; Rocha, Tiago; Sousa, Ines; Montanha, Tiago; Ribeiro, José


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Instrumentation and Measurement Society:
IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015. Proceedings : Torino, Italy, 7 - 9 May 2015
Piscataway, NJ: IEEE, 2015
ISBN: 978-1-4799-6478-9
ISBN: 978-1-4799-6476-5
ISBN: 978-1-4799-6477-2
International Symposium on Medical Measurements and Applications (MeMeA) <10, 2015, Torino>
Fraunhofer AICOS ()

Quantifying the energy expended during physical activity is an important metric to evaluate the quality and progress of individual training. There are several methods to estimate the energy expenditure using accelerometers, the most common are based on calculating counts per minute from the accelerometer signal to determinate the activity intensity in terms of metabolic equivalents (METs). This paper compares three methods to estimate the energy expenditure, the first has been proposed in a previous study and the last two are based on linear regressions derived from the data collected, one using speed, and the other using the feature root mean square (fRMS) of the magnitude of the accelerometer signal. These models were compared with indirect calorimetry outputs of energy expenditure during an incremental speed treadmill protocol. No statistically significant differences (p>0.05) were found between the indirect calorimetry and the model derived using the RMS feature, obtaining a normalized error of 20% for the METs estimation. In conclusion, this was found to be the most suitable method to estimate the energy expenditure from accelerometer data collected using a smartphone placed in the belt.