Scientifically validated applications for monitoring the practice of physical activities and energy expenditure using the smartphone accelerometer: a integrative review




Apps; Smartphone; Energy Expenditure; Accelerometers; Physical activity.


Introduction: Mobile technologies, especially smartphone applications, have contributed a lot in the area of health and physical activity, but there is an increasing concern with the validation criteria of these tools. It is extremely important to know if the physiological parameters used are safe and reliable to promote and monitor the practice of physical activity. With technological innovation, it is possible to process the data of accelerometer to measure energy expenditure. Objective: this study searched for evidence of scientific validation in Apps that uses smartphone’s accelerometer as energy expenditure indicator. Method: The keywords, inclusion and exclusion criteria were defined. The selected articles were categorized using an adapted questionnaire. Result: In a total of 1923 articles, eight articles meted all inclusion criteria that developed and validated apps for physical activity analysis. Conclusion: The results induced the effectiveness of smartphone's accelerometer to recognize physical activity and energy expenditure. It can be used to encourage healthy and safe practices, leading to improvements in quality of life. The limited number of articles with scientifically validated Applications indicates the need for more research.


Aladwani, A., & Palvia, P. (2002). Developing and Validating an Instrument for Measuring User-Perceived Web Quality. Information & Management, 39, 467–476.

Appelboom, G., Camacho, E., Abraham, M. E., Bruce, S. S., Dumont, E. L., Zacharia, B. E., D’Amico, R., Slomian, J., Reginster, J. Y., Bruyère, O., & Connolly, E. S. (2014). Smart wearable body sensors for patient self-assessment and monitoring. Arch Public Health, 72(1), 28.

Bayat, A., Pomplun, M., & Tran, D. A. (2014). A Study on Human Activity Recognition Using Accelerometer Data from Smartphones. Procedia Computer Science, 34, 450–457.

Bouten, C. V. C., Koekkoek, K. T. M., Verduin, M., Kodde, R., & Janssen, J. D. (1997). A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity. IEEE Transactions on Biomedical Engineering, 44(3), 136–147.

Chen, K. Y., & Sun, M. (1997). Improving energy expenditure estimation by using a triaxial accelerometer. Journal of Applied Physiology, 83(6), 2112–2122.

Cisco Annual Internet Report—Cisco Annual Internet Report (2018–2023) White Paper. ([s.d.]). Cisco Annual Internet Report (2018–2023) White Paper. e

Costa, J., Fazendeiro, P., & Ferreira, F. (2016). A mobile application to improve the quality of life via exercise. 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP), 55–62.

Dunton, G., Dzubur, E., Kawabata, K., Yanez, B., Bo, B., & Intille, S. (2014). Development of a Smartphone Application to Measure Physical Activity Using Sensor-Assisted Self-Report. Frontiers in Public Health, 2, 12.

Easton, C., Philip, N., Aleksandravicius, A., Pawlak, J., Muggeridge, D. J., Domene, P. A., & Istepanian, R. S. H. (2014). Validity of Smartphone Accelerometers for Assessing Energy Expenditure during Fast Running. In L. M. Roa Romero (Org.), XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013 (p. 1911–1914). Springer International Publishing.

Faria, G. S., Polese, J. C., Ribeiro-Samora, G. A., Scianni, A. A., Faria, C. D. C. M., & Teixeira-Salmela, L. F. (2019). Validity of the accelerometer and smartphone application in estimating energy expenditure in individuals with chronic stroke. Brazilian Journal of Physical Therapy, 23(3), 236–243.

Fournier, V., Bretonnière, S., & Spranzi, M. (2020). Empirical research in clinical ethics: The ‘committed researcher’ approach. Bioethics, 34(7), 719–726.

Girardello, A., & Michahelles, F. (2010). AppAware: Which mobile applications are hot? Proceedings of the 12th international conference on Human computer interaction with mobile devices and services, 431–434.

Goulart, L. J., Boni, G. N., Morgado, E. M., Tokunaga, M. K., & Bornia, B. (2006). Saúde e Tecnologia da Informação: Convergência e Mobilidade (No 10). 1, 537–541.

Guidoux, R., Duclos, M., Fleury, G., Lacomme, P., Lamaudière, N., Saboul, D., Ren, L., & Rousset, S. (2017). The eMouveRecherche application competes with research devices to evaluate energy expenditure, physical activity and still time in free-living conditions. J Biomed Inform, 69, 128–134.

Guillén, S., Sanna, A., Ngo, J., Meneu, T., Del Hoyo, E., & Demeester, M. (2009). New technologies for promoting a healthy diet and active living. Nutrition Reviews, 67(suppl_1), S107–S110.

Hills, A. P., Mokhtar, N., & Byrne, N. M. (2014). Assessment of Physical Activity and Energy Expenditure: An Overview of Objective Measures. Frontiers in Nutrition, 1, 5.

Junior, J. V. M., D’Castro, R. J., Rodrigues, F. M. M., Gusmão, C. M. G. de, Lyra, N. R. S., & Sarinho, S. W. (2011). InteliMed: Uma experiência de desenvolvimento de sistema móvel de suporte ao diagnóstico médico. Revista Brasileira de Computação Aplicada, 3(1), 30–42.

Kooiman, T. J. M., Dontje, M. L., Sprenger, S. R., Krijnen, W. P., van der Schans, C. P., & de Groot, M. (2015). Reliability and validity of ten consumer activity trackers. BMC Sports Science, Medicine and Rehabilitation, 7(1), 24.

Kuehnhausen, M., & Frost, V. S. (2013). Trusting smartphone Apps? To install or not to install, that is the question. 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 30–37.

Kwapisz, J. R., Weiss, G. M., & Moore, S. A. (2011). Activity recognition using cell phone accelerometers. ACM SIGKDD Explorations Newsletter, 12(2), 74–82.

Lee, J.-M., Kim, Y., & Welk, G. J. (2014). Validity of Consumer-Based Physical Activity Monitors. Medicine & Science in Sports & Exercise, 46(9), 1840–1848.

Maddison, R., Gemming, L., Monedero, J., Bolger, L., Belton, S., Issartel, J., Marsh, S., Direito, A., Solenhill, M., Zhao, J., Exeter, D. J., Vathsangam, H., & Rawstorn, J. C. (2017). Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study. JMIR MHealth and UHealth, 5(8), e7167.

Olsina, L., & Rossi, G. (2002). Measuring Web application quality with WebQEM. Multimedia, IEEE, 9, 20–29. MUL.2002.1041945

Organization, W. H. (2009). Global health risks: Mortality and burden of disease attributable to selected major risks (p. vi, 62 p.). World Health Organization.

Pande, A., Zhu, J., Das, A. K., Zeng, Y., Mohapatra, P., & Han, J. J. (2015). Using Smartphone Sensors for Improving Energy Expenditure Estimation. IEEE J. Transl. Eng. Health Med., 3, 1–12.

Pires, I. M., Marques, G., Garcia, N. M., Flórez-revuelta, F., Ponciano, V., & Oniani, S. (2020). A research on the classification and applicability of the mobile health applications. Journal of Personalized Medicine, 10(1).

Rodriguez, V. H., Medrano, C., Plaza, I., Corella, C., Abarca, A., & Julian, J. A. (2019). Comparison of Several Algorithms to Estimate Activity Counts with Smartphones as an Indication of Physical Activity Level. IRBM, 40(2), 95–102.

Seethamraju, R. T. (2004). Measurement of user-perceived web quality. In T. Leino, T. Saarinen, & S. Klein (Orgs.), Proceedings of the 13th European Conference on Information Systems, The European IS Profession in the Global Networking Environment, ECIS 2004, Turku, Finland, June 14-16, 2004 (p. 1745–1757).

Shoaib, M., Bosch, S., Incel, O. D., Scholten, H., & Havinga, P. J. M. (2014). Fusion of Smartphone Motion Sensors for Physical Activity Recognition. Sensors, 14(6), 10146–10176.

Sirard, J. R., Kubik, M. Y., Fulkerson, J. A., & Arcan, C. (2008). Objectively Measured Physical Activity in Urban Alternative High School Students. Med Sci Sports Exerc, 40(12), 2088–2095.

Van Coevering, P., Harnack, L., Schmitz, K., Fulton, J. E., Galuska, D. A., & Gao, S. (2005). Feasibility of Using Accelerometers to Measure Physical Activity in Young Adolescents. Medicine & Science in Sports & Exercise, 37(5), 867–871.

Warburton, D. E. R., Nicol, C. W., & Bredin, S. S. D. (2006). Health benefits of physical activity: The evidence. CMAJ, 174(6), 801–809.

Wiehe, S. E., Carroll, A. E., Liu, G. C., Haberkorn, K. L., Hoch, S. C., Wilson, J. S., & Fortenberry, Jd. (2008). Using GPS-enabled cell phones to track the travel patterns of adolescents. International Journal of Health Geographics, 7(1), 22.




How to Cite

ZANIN, N. B. .; WATANABE, W. T.; RESCIGNO, W. R.; ISHIZAKI, M. T.; SILVA, R. R. da .; GOROSO, D. G. . Scientifically validated applications for monitoring the practice of physical activities and energy expenditure using the smartphone accelerometer: a integrative review. Research, Society and Development, [S. l.], v. 10, n. 13, p. e511101321399, 2021. DOI: 10.33448/rsd-v10i13.21399. Disponível em: Acesso em: 6 dec. 2021.



Health Sciences