A Comparative Study on the Suitability of Smartphones and IMU for Mobile, Unsupervised Energy Expenditure Calculi
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AutorRuiz-Zafra, Ángel; Orantes-González, Eva; Noguera García, Manuel; Benghazi, Kawtar; Heredia Jiménez, José María
Energy expenditureAccelerometersPhysical activityMetabolic equivalent of taskSmartphonesMobileMET
Ruiz-Zafra, A.; et al. A Comparative Study on the Suitability of Smartphones and IMU for Mobile, Unsupervised Energy Expenditure Calculi. Sensors, 15(8): 18270-18286 (2015). [http://hdl.handle.net/10481/38429]
PatrocinadorThis research work was partially supported by the project ‘Sistema Ergonómico Integral para la evaluación de la locomoción como predictor de la calidad de vida relacionada con la salud en Mayores (Ergoloc)’, funded by the Spanish Ministry of Economy and Competitiveness under the project DEP2012-40069; Facultad de Educación, Economía y Tecnología de Ceuta under the “Contrato-programa” of research for the period 2013–2015 and by the Programa de Fortalecimiento de I+D+i de la Universidad de Granada 2014-15. The Ministry of Education, Culture and Sports of Spain supported the work of Orantes-González, E. (ref. FPU13/00162). The authors would also like to acknowledge contribution from COST Action IC1303.
The metabolic equivalent of task (MET) is currently the most used indicator for measuring the energy expenditure (EE) of a physical activity (PA) and has become an important measure for determining and supervising a person’s state of health. The use of new devices which are capable of measuring inertial movements by means of built-in accelerometers enable the PA to be measured objectively on the basis of the reckoning of “counts”. These devices are also known as inertial measurement units (IMUs) and each count is an aggregated value indicating the intensity of a movement and can be used in conjunction with other parameters to determine the MET rate of a particular physical activity and thus it’s associated EE. Various types of inertial devices currently exist that enable count calculus and physical activity to be monitored. The advent of mobile devices, such as smartphones, with empowered computation capabilities and integrated inertial sensors, has enabled EE to be measure in a distributed, ubiquitous and natural way, thereby overcoming the reluctance of users and practitioners associated with in-lab studies. From the point of view of the process analysis and infrastructure needed to manage data from inertial devices, there are also various differences in count computing: extra devices are required, out-of-device processing, etc. This paper presents a study to discover whether the estimation of energy expenditure is dependent on the accelerometer of the device used in measurements and to discover the suitability of each device for performing certain physical activities. In order to achieve this objective, we have conducted several experiments with different subjects on the basis of the performance of various daily activities with different smartphones and IMUs.