Test-Retest and Inter-Monitor Reliability of The Atlas Activity Monitor For Assessing Resistance Training Exercises

in Journal for the Measurement of Physical Behaviour
Restricted access

Purchase article

USD  $24.95

Student 1 year subscription

USD  $37.00

1 year subscription

USD  $50.00

Student 2 year subscription

USD  $71.00

2 year subscription

USD  $93.00

Background: Resistance training (RT) is an integral component of physical activity guidelines, but methods for the objective assessment of RT have been limited. Recently, the Atlas Wearables Wristband2 has been marketed to measure RT, but its reliability is unknown. Purpose: To determine the reliability of the Wristband2 for measuring RT exercises. Methods: Participants (n = 62) aged 18–52 yrs. wore two Wristband2 monitors on the left wrist and performed 2 sets of 12 repetitions of 14 different resistance training exercises. Test-retest reliability was determined by calculating percent agreement for exercise type and for repetitions recorded by a single Wristband2 between sets 1 and 2 for each exercise, and inter-monitor reliability was determined by calculating percent agreement for exercise type and for repetitions recorded by both Wristband2 monitors in set 1 of each exercise. Results: Test-retest reliability for exercise type was 80.0 ± 1.0% (lowest: 69.4% for bench press; highest: 95.2% for biceps curls) and for repetition count was 47.9 ± 2.2% (lowest: 19.4% for calf raises; highest: 82.3% for lateral raises). Inter-monitor reliability for exercise type was 80.4 ± 1.3% (lowest: 66.1% for bench press; highest: 95.2% for biceps curls) and for repetition count was 59.6 ± 2.2% (lowest: 32.3% for calf raises; highest: 88.7% for lateral raises). Subgroup analyses by gender, RT experience, and participant height revealed minimal differences in reliability. Repetition agreement of ≤1 repetition increased test-retest reliability to 74.7% and inter-monitor reliability to 83.7%. Conclusion: The Wristband2 had acceptable test-retest and inter-monitor reliability for the majority of exercises tested and for counting repetitions to within 1 repetition/set.

Montoye and Mitrzyk are with the Department of Integrative Physiology and Health Science, Alma College, Alma, MI. Conger and Fox are with the Department of Kinesiology, Boise State University, Boise, ID. Beach and Steeves are with the Department of Exercise Science, Maryville College, Maryville, TN.

Montoye (montoyeah@alma.edu) is corresponding author.
  • Atlas Wearables. (2018). Wristband2. Retrieved from https://atlaswearables.com/products/atlas-wristband-2

  • Balsalobre-Fernandez, C., Kuzdub, M., Poveda-Ortiz, P., & Campo-Vecino, J.D. (2016). Validity and reliability of the PUSH wearable device to measure movement velocity during the back squat exercise. Journal of Strength and Conditioning Research, 30(7), 1968–1974. PubMed ID: 26670993 doi:10.1519/JSC.0000000000001284

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Balsalobre-Fernandez, C., Marchante, D., Baz-Valle, E., Alonso-Molero, I., Jimenez, S.L., & Munoz-Lopez, M. (2017). Analysis of wearable and smartphone-based technologies for the measurement of barbell velocity in different resistance training exercises. Frontiers in Physiology, 8, 649. PubMed ID: 28894425 doi:10.3389/fphys.2017.00649

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bastian, T., Maire, A., Dugas, J., Ataya, A., Villars, C., Gris, F., . . . Simon, C. (2015). Automatic identification of physical activity types and sedentary behaviors from 3-axial accelerometer: lab-based calibrations are not enough. Journal of Applied Physiology, 118(6), 716–722. PubMed ID: 25593289 doi:10.1152/japplphysiol.01189.2013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bock, J.M., Kaminsky, L.A., Harber, M.P., & Montoye, A.H.K. (2017). Determining the reliability of several consumber-based physical activity monitors. Technologies, 5(3), 47. doi:10.3390/technologies5030047

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Centers for Disease Control and Prevention. (2014). Summary Health Statistics Tables: National Health Interview Survey. Retrieved from https://ftp.cdc.gov/pub/Health_Statistics/NCHS/NHIS/SHS/2014_SHS_Table_A-14.pdf

    • Search Google Scholar
    • Export Citation
  • Chang, K., Chen, M.Y., & Canny, J. (2007). Tracking free-weight exercises. Paper presented at the UbiComp 2007: Ubiquitous Computing, Innsbruck, Austria.

    • Search Google Scholar
    • Export Citation
  • Chu, Y., Fleisig, G.S., Simpson, K.J., & Andrews, J.R. (2009). Biomechanical comparison between elite female and male baseball pitchers. Journal of Applied Biomechanics, 25(1), 22–31. PubMed ID: 19299827 doi:10.1123/jab.25.1.22

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Conger, S.A., Guo, J., Fulkerson, S.M., Pedigo, L., Chen, H., & Bassett, D.R., Jr. (2016). Objective assessment of strength training exercises using a wrist-worn accelerometer. Medicine and Science in Sports and Exercise, 48(9), 1847–1855. PubMed ID: 27054678 doi:10.1249/MSS.0000000000000949

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Sousa, M., Swartz, L., da Silveira, J.L., Kulkamp, W., Dias, J.A., & Borges, N.G. (2012). Measuring the speed of execution of the resistance training exercise using a triaxial accelerometer. IEEE 14th International Conference on e-Health Networking, Applications and Services, Beijing, China.

    • Search Google Scholar
    • Export Citation
  • Dong, B., Montoye, A., Moore, R., Pfeiffer, K., & Biswas, S. (2013). Energy-aware activity classification using wearable sensor networks. Proceedings of SPIE--the International Society for Optical Engineering, 8723, 87230Y. PubMed Id: 25075266

    • Search Google Scholar
    • Export Citation
  • Evenson, K.R., Goto, M.M., & Furberg, R.D. (2015). Systematic review of the validity and reliability of consumer-wearable activity trackers. International Journal for Behavioral Nutrition and Physical Activity, 12, 159. doi:10.1186/s12966-015-0314-1

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gomez-Piriz, P.T., Sanchez, E.T., Manrique, D.C., & Gonzalez, E.P. (2013). Reliability and comparability of the accelerometer and the linear position measuring device in resistance training. Journal of Strength and Conditioning Research, 27(6), 1664–1670. PubMed ID: 22847523 doi:10.1519/JSC.0b013e318269f809

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gyllensten, I.C., & Bonomi, A.G. (2011). Identifying types of physical activity with a single accelerometer: evaluating laboratory-trained algorithms in daily life. IEEE Transactions on Biomedical Engineering, 58(9), 2656–2663. PubMed ID: 21712150 doi:10.1109/TBME.2011.2160723

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landry, S.C., McKean, K.A., Hubley-Kozey, C.L., Stanish, W.D., & Deluzio, K.J. (2007). Neuromuscular and lower limb biomechanical differences exist between male and female elite adolescent soccer players during an unanticipated run and crosscut maneuver. American Journal of Sports Medicine, 35(11), 1901–1911. PubMed ID: 17761606 doi:10.1177/0363546507307400

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Margarito, J., Helaoui, R., Bianchi, A.M., Sartor, F., & Bonomi, A.G. (2016). User-independent recognition of sports activities from a single wrist-worn accelerometer: A template-matching-based approach. IEEE Transactions on Biomedical Engineering, 63(4), 788–796. PubMed ID: 26302509

    • Search Google Scholar
    • Export Citation
  • Muyor, J.M., Granero-Gil, P., & Pino-Ortega, J. (2017). Reliability and validity of a new accelerometer (Wimu) system for measuring velocity during resistance exercises. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 232(3), 218–224.

    • Search Google Scholar
    • Export Citation
  • Pernek, I., Hummel, K.A., & Kokol, P. (2012). Exercise repetition detection for resistance training based on smartphones. Personal and ubiquitous computing, 17(4), 771–782. doi:10.1007/s00779-012-0626-y

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pernek, I., Kurillo, G., Stiglic, G., & Bajcsy, R. (2015). Recognizing the intensity of strength training exercises with wearable sensors. Journal of Biomedical Informatics, 58, 145–155. PubMed ID: 26453822 doi:10.1016/j.jbi.2015.09.020

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Swanson, E. (2014). Validity, reliability, and the questionable role of psychometrics in plastic surgery. Plastic and Reconstructive Surgery Global Open, 2(6), 161. PubMed ID: 25289354 doi:10.1097/GOX.0000000000000103

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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. PubMed ID: 18091006 doi:10.1249/mss.0b013e31815a51b3

    • Crossref
    • Search Google Scholar
    • Export Citation
  • U.S. Department of Health and Human Services. (2018). Physical Activity Guidelines for Americans, (2nd ed.). Washington DC, WA: Author. Retrieved from www.health.gov/paguidelines/second-edition/

    • Search Google Scholar
    • Export Citation
  • Welk, G.J. (2002). Use of Accelerometry-Based Activity Monitors to Assess Physical Activity. In G.J. Welk (Ed.), Physical Activity Assessments for Health-Related Research (pp. 125–142). Champaign, IL: Human Kinetics, Inc.

    • Search Google Scholar
    • Export Citation
  • Williams, M.A., Haskell, W.L., Ades, P.A., Amsterdam, E.A., Bittner, V., Franklin, B.A., . . . Metabolism. (2007). Resistance exercise in individuals with and without cardiovascular disease: 2007 update: A scientific statement from the American Heart Association Council on Clinical Cardiology and Council on Nutrition, Physical Activity, and Metabolism. Circulation, 116(5), 572–584. PubMed ID: 17638929 doi:10.1161/CIRCULATIONAHA.107.185214

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 82 82 16
Full Text Views 5 5 3
PDF Downloads 2 2 1