189
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Using Accelerometers to Detect Activity Type in a Sport Setting: Challenges with Using Multiple Types of Conventional Machine Learning Approaches

, , , , ORCID Icon, , & show all

References

  • Ahmadi, A., Mitchell, E., Destelle, F., Gowing, M., O’Connor, N. E., Richter, C., & Moran, K. M. (2015). Toward automatic activity classification and movement assessment during a sports training session. IEEE Internet of Things Journal, 2(1), 23–32. https://doi.org/10.1109/JIOT.2014.2377238
  • Atallah, L., Lo, B., King, R., & Yang, G. (2011). Sensor positioning for activity recognition using wearable accelerometers. IEEE Transactions on Biomedical Circuits and Systems, 5(4), 320–329. https://doi.org/10.1109/TBCAS.2011.2160540
  • Bastian, T., Maire, A., Dugas, J., Ataya, A., Villars, C., Gris, F., Perrin, E., Caritu, Y., Doron, M., Blanc, S., Jallon, P., & Simon, C. (2015). Automatic identification of physical activity types and sedentary behaviors from triaxial accelerometer: Laboratory-based calibrations are not enough. Journal of Applied Physiology, 118(6), 716–722. https://doi.org/10.1152/japplphysiol.01189.2013
  • Beleites, C., Neugebauer, U., Bocklitz, T., Krafft, C., & Popp, J. (2013). Sample size planning for classification models. Analytica Chimica Acta, 760(14), 25–33. https://doi.org/10.1016/j.aca.2012.11.007
  • Bonomi, A. G., Goris, A. H., Yin, B., & Westerterp, K. R. (2009). Detection of type, duration, and intensity of physical activity using an accelerometer. Medicine and Science in Sports and Exercise, 41(9), 1770–1777. https://doi.org/10.1249/MSS.0b013e3181a24536
  • Camomilla, V., Bergamini, E., Fantozzi, S., & Vannozzi, G. (2018). Trends supporting the in-field use of wearable inertial sensors for sport performance evaluation: A systematic review. Sensors (Basel), 18(3), 873. https://doi.org/10.3390/s18030873
  • Cust, E. E., Sweeting, A. J., Ball, K., & Robertson, S. (2019). Machine and deep learning for sport-specific movement recognition: A systematic review of model development and performance. Journal of Sports Sciences, 37(5), 568–600. https://doi.org/10.1080/02640414.2018.1521769
  • Kate, R. J., Swartz, A. M., Welch, W. A., & Strath, S. J. (2016). Comparative evaluation of features and techniques for identifying activity type and estimating energy cost from accelerometer data. Physiological Measurement, 37(3), 360–379. https://doi.org/10.1088/0967-3334/37/3/360
  • Liaw, A., & Wiener, M. (2002). Classification and regression by randomForest. R News, 2(3), 18–22. http://cran.r-project.org/doc/Rnews/
  • Matthews, C. E., Hagstromer, M., Pober, D. M., & Bowles, H. R. (2012). Best practices for using physical activity monitors in population-based research. Medicine and Science in Sports and Exercise, 44(1 Suppl 1), S68–76. https://doi.org/10.1249/MSS.0b013e3182399e5b
  • McHugh, M. L. (2012). Interrater reliability: The kappa statistic. Biochemia medica: casopis Hrvatskoga drustva medicinskih biokemicara / HDMB, 22(3), 276–282. https://doi.org/10.11613/BM.2012.031
  • Mitchell, E., Monaghan, D., & O’Connor, N. E. (2013). Classification of sporting activities using smartphone accelerometers. Sensors (Basel), 13(4), 5317–5337. https://doi.org/10.3390/s130405317
  • Montoye, A. H. K., & Mitrzyk, J. (2018). Validity of the blast athletic performance monitor for assessing vertical jump height in female volleyball players. Measurement in Physical Education and Exercise Science, 23(2) , 1–11. https://doi.org/10.1080/1091367X.2018.1539739
  • Montoye, A. H. K., Westgate, B. S., Fonley, M. R., & Pfeiffer, K. A. (2018). Cross-validation and out-of-sample testing of physical activity intensity predictions with a wrist-worn accelerometer. Journal of Applied Physiology, 124(5), 1284–1293. https://doi.org/10.1152/japplphysiol.00760.2017
  • O’Connell, J., & Hojsgaard, S. R. (2011). Hidden semi Markov models for multiple observation sequences: The mhsmm package for R. Journal of Statistical Software, 39(4), 1–22. doi:10.18637/jss.v039.i04
  • Preece, S. J., Goulermas, J. Y., Kenney, L. P., Howard, D., Meijer, K., & Crompton, R. (2009). Activity identification using body-mounted sensors–a review of classification techniques. Physiological Measurement, 30(4), R1–33. https://doi.org/10.1088/0967-3334/30/4/R01
  • Ross, S. M. (2010). Introduction to probability models (10 ed.). Elsevier.
  • Skazalski, C., Whiteley, R., Hansen, C., & Bahr, R. (2018). A valid and reliable method to measure jump-specific training and competition load in elite volleyball players. Scandinavian Journal of Medicine & Science in Sports, 28(5), 1578–1585. https://doi.org/10.1111/sms.13052
  • Street, G., James, R., & Cutt, H. (2007). The relationship between organised physical recreation and mental health. Health Promotion Journal of Australia: Official Journal of Australian Association of Health Promotion Professionals, 18(3), 236–239. https://doi.org/10.1071/he07236
  • Troiano, R. P., Berrigan, D., Dodd, K. W., Masse, L. C., Tilert, T., & McDowell, M. (2008). Physical activity in the United States measured by accelerometer. Medicine and Science in Sports and Exercise, 40(1), 181–188. https://doi.org/10.1249/mss.0b013e31815a51b3
  • Troiano, R. P., McClain, J. J., Brychta, R. J., & Chen, K. Y. (2014). Evolution of accelerometer methods for physical activity research. British Journal of Sports Medicine, 48(13), 1019–1023. https://doi.org/10.1136/bjsports-2014-093546
  • U.S. Department of Health and Human Services. (2018). Physical Activity Guidelines for Americans, 2nd edition. Washington, DC: U.S. Department of Health and Human Services.
  • Vella, S. A., Schranz, N. K., Davern, M., Hardy, L. L., Hills, A. P., Morgan, P. J., Plotnikoff, R. C., & Tomkinson, G. (2016). The contribution of organised sports to physical activity in Australia: Results and directions from the Active Healthy Kids Australia 2014 Report Card on physical activity for children and young people. Journal of Science and Medicine in Sport / Sports Medicine Australia, 19(5), 407–412. https://doi.org/10.1016/j.jsams.2015.04.011
  • Viterbi, A. (1967). Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory, 13(2), 260–269. https://doi.org/10.1109/TIT.1967.1054010
  • Wundersitz, D. W. T., Josman, C., Gupta, R., Netto, K. J., Gastin, P. B., & Robertson, S. (2015). Classification of team sport activities using a single wearable tracking device. Journal of Biomechanics, 48(15), 3975–3981. https://doi.org/10.1016/j.jbiomech.2015.09.015

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.