Validity of the iPhone M7 Motion Coprocessor to Estimate Physical Activity During Structured and Free-Living Activities in Healthy Adults

in Journal for the Measurement of Physical Behaviour
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  • 1 University of the West of Scotland
  • | 2 Strathclyde University
  • | 3 Hong Kong Baptist University
  • | 4 Edinburgh Napier University
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Modern smartphones such as the iPhone contain an integrated accelerometer, which can be used to measure body movement and estimate the volume and intensity of physical activity. Objectives: The primary objective was to assess the validity of the iPhone to measure step count and energy expenditure during laboratory-based physical activities. A further objective was to compare free-living estimates of physical activity between the iPhone and the ActiGraph GT3X+ accelerometer. Methods: Twenty healthy adults wore the iPhone 5S and GT3X+ in a waist-mounted pouch during bouts of treadmill walking, jogging, and other physical activities in the laboratory. Step counts were manually counted, and energy expenditure was measured using indirect calorimetry. During two weeks of free-living, participants (n = 17) continuously wore a GT3X+ attached to their waist and were provided with an iPhone 5S to use as they would their own phone. Results: During treadmill walking, iPhone (703 ± 97 steps) and GT3X+ (675 ± 133 steps) provided accurate measurements of step count compared with the criterion method (700 ± 98 steps). Compared with indirect calorimetry (8 ± 3 kcal·min−1), the iPhone (5 ± 1 kcal·min−1) underestimated energy expenditure with poor agreement. During free-living, the iPhone (7,990 ± 4,673 steps·day−1) recorded a significantly lower (p < .05) daily step count compared with the GT3X+ (9,085 ± 4,647 steps·day−1). Conclusions: The iPhone accurately estimated step count during controlled laboratory walking but recorded a significantly lower volume of physical activity compared with the GT3X+ during free-living.

Thomson, Macrae, and Easton are with the Institute for Clinical Exercise and Health Science, University of the West of Scotland, Lanarkshire, United Kingdom. McMichan is with the Physical Activity and Health Group, School of Psychological Sciences and Health, University of Strathclyde, Glasgow, United Kingdom. Baker is with the Centre for Health and Exercise Science Research, Department of Sport and Physical Education, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China. Muggeridge is with the Sports, Exercise and Health Science Research Group, School of Applied Sciences, Edinburgh Napier University, Edinburgh, United Kingdom.

Easton (chris.easton@uws.ac.uk) is corresponding author.
  • Aadland, E., & Ylvisåker, E. (2015). Reliability of the actigraph GT3X+ accelerometer in adults under free-living conditions. PLoS One, 10(8), e0134606 . doi:10.1371/journal.pone.0134606

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Antero Kesaniemi (Chair), Y., Danforth, E., Jensen, M.D., Kopelman, P.G., Lefebvre, P., & Reeder, B.A. (2001). Dose-response issues concerning physical activity and health: An evidence-based symposium. Medicine & Science in Sports & Exercise, 33(Suppl.), S351S358.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barreira, T.V., Tudor-Locke, C., Champagne, C.M., Broyles, S.T., Johnson, W.D., & Katzmarzyk, P.T. (2013). Comparison of GT3X accelerometer and YAMAX pedometer steps/day in a free-living sample of overweight and obese adults. Journal of Physical Activity and Health, 10(2), 263270. doi:10.1123/jpah.10.2.263

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davies, D.S.C., Atherton, F., McBride, M., & Calderwood, C. (2019). UK Chief Medical Officers’ Physical Activity Guidelines. Department of Health and Social Care. Retrieved from https://www.gov.uk/government/publications/physical-activity-guidelines-uk-chief-medical-officers-report

    • Search Google Scholar
    • Export Citation
  • Dyrstad, S.M., Hansen, B.H., Holme, I.M., & Anderssen, S.A. (2014). Comparison of self-reported versus accelerometer-measured physical activity. Medicine & Science in Sports & Exercise, 46(1), 99106. PubMed ID: 23793232 doi:10.1249/MSS.0b013e3182a0595f

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ewing, C., Wilmore, J., Blair, S., Haskell, W., & Kraemer, W. (1998). ACSM position stand: The recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscular fitness, and flexibility in healthy adults. Medicine & Science in Sports & Exercise, 30(6), 975991. Retrieved from http://ovidsp.tx.ovid.com.libproxy.csun.edu/sp­3.15.1b/ovidweb.cgi

    • Search Google Scholar
    • Export Citation
  • Gastin, P.B., Cayzer, C., Dwyer, D., & Robertson, S. (2018). Validity of the ActiGraph GT3X+ and BodyMedia SenseWear Armband to estimate energy expenditure during physical activity and sport. Journal of Science and Medicine in Sport, 21(3), 291295. PubMed ID: 28797831 doi:10.1016/j.jsams.2017.07.022

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gatti, A.A., Stratford, P.W., Brenneman, E.C., & Maly, M.R. (2016). GT3X+ accelerometer placement affects the reliability of step-counts measured during running and pedal-revolution counts measured during bicycling. Journal of Sports Sciences, 34(12), 11681175. doi:10.1080/02640414.2015.1096018

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gordon, B.A., Bruce, L., & Benson, A.C. (2016). Physical activity intensity can be accurately monitored by smartphone global positioning system ‘app.’ European Journal of Sport Science, 16(5), 624631. PubMed ID: 26505223 doi:10.1080/17461391.2015.1105299

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Howe, C.C.F., Moir, H.J., & Easton, C. (2017). Classification of physical activity cut-points and the estimation of energy expenditure during walking using the GT3X+ accelerometer in overweight and obese adults. Measurement in Physical Education and Exercise Science, 21(3), 127133. doi:10.1080/1091367X.2016.1271801

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jarrett, H., Fitzgerald, L., & Routen, A. (2015). Inter-instrument reliability of the Actigraph GT3X+ ambulatory activity monitor during free-living conditions in adults manuscript. Critical Studies on Security, 2(2), 210222.

    • Search Google Scholar
    • Export Citation
  • Jones, A.M., & Doust, J.H. (1996). A 1% treadmill grade most accurately reflects the energetic cost of outdoor running. Journal of Sports Sciences, 14(4), 321327. PubMed ID: 8887211 doi:10.1080/02640419608727717

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Le Masurier, G.C., Lee, S.M., & Tudor-Locke, C. (2004). Motion sensor accuracy under controlled and free-living conditions. Medicine & Science in Sports & Exercise, 36(5), 905910. PubMed ID: 15126728 doi:10.1249/01.MSS.0000126777.50188.73

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, J.A., Williams, S.M., Brown, D.D., & Laurson, K.R. (2014). Concurrent validation of the Actigraph GT3X+, Polar Active accelerometer, Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings. Journal of Sports Sciences, 33(10), 9911000. PubMed ID: 25517396 doi:10.1080/02640414.2014.981848

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, L.I. (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics, 45(1), 255268. PubMed ID: 2720055 doi:10.2307/2532051

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Major, M.J., & Alford, M. (2016). Validity of the iPhone M7 motion co-processor as a pedometer for able-bodied ambulation. Journal of Sports Sciences, 34(23), 21602164. PubMed ID: 27240005 doi:10.1080/02640414.2016.1189086

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Martin Bland, J., & Altman, D. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet, 327(8476), 307310. doi:10.1016/S0140-6736(86)90837-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mcminn, D., Acharya, R., Rowe, D.A., Gray, S.R., & Allan, J.L. (2013). Measuring activity energy expenditure: Accuracy of the GT3X+ and actiheart monitors. International Journal of Exercise Science, 6(3), 217229.

    • Search Google Scholar
    • Export Citation
  • Migueles, J.H., Cadenas-Sanchez, C., Ekelund, U., Delisle Nyström, C., Mora-Gonzalez, J., Löf, M., . . . Ortega, F.B. (2017). Accelerometer data collection and processing criteria to assess physical activity and other outcomes: A systematic review and practical considerations. Sports Medicine, 47(9), 18211845. PubMed ID: 28303543 doi:10.1007/s40279-017-0716-0

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Brien, W.J., Shultz, S.P., Firestone, R.T., George, L., Breier, B.H., & Kruger, R. (2017). Exploring the challenges in obtaining physical activity data from women using hip-worn accelerometers. European Journal of Sport Science, 17(7), 922930. PubMed ID: 28504054 doi:10.1080/17461391.2017.1323952

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ozemek, C., Kirschner, M.M., Wilkerson, B.S., Byun, W., & Kaminsky, L.A. (2014). Intermonitor reliability of the GT3X+ accelerometer at hip, wrist and ankle sites during activities of daily living. Physiological Measurement, 35(2), 129138. PubMed ID: 24399138 doi:10.1088/0967-3334/35/2/129

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prince, S.A., Adamo, K.B., Hamel, M.E., Hardt, J., Connor Gorber, S., & Tremblay, M. (2008). A comparison of direct versus self-report measures for assessing physical activity in adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 5(56), 1–24.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reid, R.E.R., Insogna, J.A., Carver, T.E., Comptour, A.M., Bewski, N.A., Sciortino, C., & Andersen, R.E. (2017). Validity and reliability of Fitbit activity monitors compared to ActiGraph GT3X+ with female adults in a free-living environment. Journal of Science and Medicine in Sport, 20(6), 578582. PubMed ID: 27887786 doi:10.1016/j.jsams.2016.10.015

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Santos-Lozano, A., Santín-Medeiros, F., Cardon, G., Torres-Luque, G., Bailón, R., Bergmeir, C., . . . Garatachea, N. (2013). Actigraph GT3X: Validation and determination of physical activity intensity cut points. International Journal of Sports Medicine, 34(11), 975982. PubMed ID: 23700330 doi:10.1055/s-0033-1337945

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sasaki, J.E., John, D., & Freedson, P.S. (2011). Validation and comparison of ActiGraph activity monitors. Journal of Science and Medicine in Sport, 14(5), 411416. PubMed ID: 21616714 doi:10.1016/j.jsams.2011.04.003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tanaka, H., Monahan, K.D., & Seals, D.R. (2001). Age-predicted maximal heart rate revisited. Journal of the American College of Cardiology, 37(1), 153156. PubMed ID: 11153730 doi:10.1016/S0735-1097(00)01054-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, K., & Silver, L. (2019). Smartphone ownership is growing rapidly around the world, but not always equally. Retrieved from http://www.pewglobal.org/2019/02/05/smartphone-ownership-is-growing-rapidly-around-the-world-but-not-always-equally/

    • Search Google Scholar
    • Export Citation
  • The American College of Sports Medicine. (2017). ACSM’s guidelines for exercise testing and prescription (Vol. 10, 10th ed.). Philadelphia: Wolters Kluwer.

    • Search Google Scholar
    • Export Citation
  • Troiano, R.P., Berrigan, D., Dodd, K.W., Mâsse, L.C., Tilert, T., & Mcdowell, M. (2008). Physical activity in the United States measured by accelerometer. Medicine & Science in Sports & Exercise, 40(1), 181188. PubMed ID: 18091006 doi:10.1249/mss.0b013e31815a51b3

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tudor-Locke, C., Barreira, T.V., & Schuna, J.M. (2015). Comparison of step outputs for waist and wrist accelerometer attachment sites. Medicine & Science in Sports & Exercise, 47(4), 839842. PubMed ID: 25121517 doi:10.1249/MSS.0000000000000476

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Dyck, D., Cerin, E., De Bourdeaudhuij, I., Hinckson, E., Reis, R.S., Davey, R., . . . Sallis, J.F. (2015). International study of objectively measured physical activity and sedentary time with body mass index and obesity: IPEN adult study. International Journal of Obesity, 39(2), 199207. PubMed ID: 24984753 doi:10.1038/ijo.2014.115

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weir, J.B.de V. (1949). New methods for calculating metabolic rate with special reference to protein metabolism. Journal of Physiology, 109(1–2), 19. doi:10.1113/jphysiol.1949.sp004363

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wijndaele, K., Westgate, K., Stephens, S.K., Blair, S.N., Bull, F.C., Chastin, S.F.M., . . . Healy, G.N. (2015). Utilization and harmonization of adult accelerometry data: Review and expert consensus. Medicine & Science in Sports & Exercise, 47(10), 21292139. PubMed ID: 25785929 doi:10.1249/MSS.0000000000000661

    • Crossref
    • Search Google Scholar
    • Export Citation
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