De la Fuente Robles YM, Ricoy Cano AJ, Albín Rodríguez AP, López Ruiz JL, Espinilla EM. Past, present and future of research on wearable technologies for healthcare: a bibliometric analysis using scopus. Sensors. 2022;22:8599. https://doi.org/10.3390/s22228599.
Kuratomi D, Shin C, Duffy VG. Systematic literature review on the advances of wearable technologies. 2023:78–95. https://doi.org/10.1007/978-3-031-48047-8_5.
Fortino G, Gravina R, Galzarano S. Wearable computing: from modeling to implementation of wearable systems based on body sensor networks. Wiley-IEEE Press; 2018.
Mühlen JM, Stang J, Lykke Skovgaard E, Judice PB, Molina-Garcia P, Johnston W, et al. Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network. Br J Sports Med. 2021. https://doi.org/10.1136/bjsports-2020-103148.
Johnston W, Judice PB, Molina García P, Mühlen JM, Lykke Skovgaard E, Stang J, et al. Recommendations for determining the validity of consumer wearable and smartphone step count: expert statement and checklist of the INTERLIVE network. Br J Sports Med. 2021;55:780–93. https://doi.org/10.1136/BJSPORTS-2020-103147.
Molina-Garcia P, Notbohm HL, Schumann M, Argent R, Hetherington-Rauth M, Stang J, et al. Validity of estimating the maximal oxygen consumption by consumer wearables: a systematic review with meta-analysis and expert statement of the INTERLIVE Network. Sports Med. 2022;52:1577–97. https://doi.org/10.1007/S40279-021-01639-Y.
Article PubMed PubMed Central Google Scholar
Argent R, Hetherington-Rauth M, Stang J, Tarp J, Ortega FB, Molina-Garcia P, et al. Recommendations for determining the validity of consumer wearables and smartphones for the estimation of energy expenditure: expert statement and checklist of the INTERLIVE network. Sports Med. 2022;52:1817–32. https://doi.org/10.1007/S40279-022-01665-4.
Article PubMed PubMed Central Google Scholar
McDonough DJ, Su X, Gao Z. Health wearable devices for weight and BMI reduction in individuals with overweight/obesity and chronic comorbidities: systematic review and network meta-analysis. Br J Sports Med. 2021;55:917–25. https://doi.org/10.1136/BJSPORTS-2020-103594.
Gao Z, Liu W, McDonough DJ, Zeng N, Lee JE. The dilemma of analyzing physical activity and sedentary behavior with wrist accelerometer data: challenges and opportunities. J Clin Med. 2021;10:5951. https://doi.org/10.3390/JCM10245951.
Article PubMed PubMed Central Google Scholar
Clevenger KA, Montoye AHK, Van Camp CA, Strath SJ, Pfeiffer KA. Methods for estimating physical activity and energy expenditure using raw accelerometry data or novel analytical approaches: a repository, framework, and reporting guidelines. Physiol Meas. 2022. https://doi.org/10.1088/1361-6579/ac89c9.
Migueles JH, Cadenas-Sanchez C, Ekelund U, Delisle Nyström C, Mora-Gonzalez J, Löf M, et al. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sports Med. 2017. https://doi.org/10.1007/s40279-017-0716-0.
Migueles JH, Aadland E, Andersen LB, Brønd JC, Chastin SF, Hansen BH, et al. GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies. Br J Sports Med. 2022;56:376–84. https://doi.org/10.1136/BJSPORTS-2020-103604.
Pulsford RM, Brocklebank L, Fenton SAM, Bakker E, Mielke GI, Tsai L-T, et al. The impact of selected methodological factors on data collection outcomes in observational studies of device-measured physical behaviour in adults: a systematic review. Int J Behav Nutr Phys Act. 2023;20:26. https://doi.org/10.1186/s12966-022-01388-9.
Article PubMed PubMed Central Google Scholar
Seiler KS, Kjerland GØ. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sports. 2006;16:49–56. https://doi.org/10.1111/J.1600-0838.2004.00418.X.
Jamnick NA, Pettitt RW, Granata C, Pyne DB, Bishop DJ. An examination and critique of current methods to determine exercise intensity. Sports Med. 2020;50:1729–56. https://doi.org/10.1007/S40279-020-01322-8.
Davis JA, Convertino VA. A comparison of heart rate methods for predicting endurance training intensity. Med Sci Sports. 1975;7:295–8. https://doi.org/10.1249/00005768-197500740-00010.
Article CAS PubMed Google Scholar
American College of Sports Medicine. ACSM’s guidelines for exercise testing and prescription. Philadelphia: Lippincott Williams & Wilkins; 2021. p. 11.
Norton K, Norton L, Sadgrove D. Position statement on physical activity and exercise intensity terminology. J Sci Med Sport. 2010;13:496–502. https://doi.org/10.1016/j.jsams.2009.09.008.
Laricchia F. Global smartwatch market share 2020–2022. Counterpoint Technology Market Research. 2023.
Fernhall B, Mccubbin JA, Pitetti KH, Rintala P, Rimmer JH, Lynn Millar A, et al. Prediction of maximal heart rate in individuals with mental retardation. Med Sci Sports Exerc. 2001;33:1655–60. https://doi.org/10.1097/00005768-200110000-00007.
Article CAS PubMed Google Scholar
Lester M, Sheffield LT, Trammell P, Reeves TJ. The effect of age and athletic training on the maximal heart rate during muscular exercise. Am Heart J. 1968;76:370–6. https://doi.org/10.1016/0002-8703(68)90233-0.
Article CAS PubMed Google Scholar
Miller WC, Wallace JP, Eggert KE. Predicting max HR and the HR-VO2 relationship for exercise prescription in obesity. Med Sci Sports Exerc. 1993;25:1077–81. https://doi.org/10.1249/00005768-199309000-00017.
Article CAS PubMed Google Scholar
Whyte GP, George K, Shave R, Middleton N, Nevill AM. Training induced changes in maximum heart rate. Int J Sports Med. 2008;29:129–33. https://doi.org/10.1055/S-2007-965783/ID/18.
Article CAS PubMed Google Scholar
Logan N, Reilly JJ, Grant S, Paton JY. Resting heart rate definition and its effect on apparent levels of physical activity in young children. Med Sci Sports Exerc. 2000;32:162–6. https://doi.org/10.1097/00005768-200001000-00024.
Article CAS PubMed Google Scholar
Strzelczyk TA, Quigg RJ, Pfeifer PB, Parker MA, Greenland P. Accuracy of estimating exercise prescription intensity in patients with left ventricular systolic dysfunction. J Cardiopulm Rehabil. 2001;21:158–63. https://doi.org/10.1097/00008483-200105000-00007.
Article CAS PubMed Google Scholar
Goldberg L, Elliot DL, Kuehl KS. Assessment of exercise intensity formulas by use of ventilatory threshold. Chest. 1988;94:95–8. https://doi.org/10.1378/CHEST.94.1.95.
Article CAS PubMed Google Scholar
Meyer T, Gabriel HHW, Kindermann W. Is determination of exercise intensities as percentages of VO2max or HRmax adequate? Med Sci Sports Exerc. 1999;31:1342–5. https://doi.org/10.1097/00005768-199909000-00017.
Article CAS PubMed Google Scholar
Weltman A, Snead D, Seip R, Schurrer R, Weltman J, Rutt R, et al. Percentages of maximal heart rate, heart rate reserve and VO2max for determining endurance training intensity in male runners. Int J Sports Med. 1990;11:218–22. https://doi.org/10.1055/S-2007-1024795.
Article CAS PubMed Google Scholar
Hofmann P, Von Duvillard SP, Seibert FJ, Pokan R, Wonisch M, Lemura LM, et al. %HRmax target heart rate is dependent on heart rate performance curve deflection. Med Sci Sports Exerc. 2001;33:1726–31. https://doi.org/10.1097/00005768-200110000-00017.
Article CAS PubMed Google Scholar
Katch V, Weltman A, Sady S, Freedson P. Validity of the relative percent concept for equating training intensity. Eur J Appl Physiol Occup Physiol. 1978;39:219–27. https://doi.org/10.1007/BF00421445.
Article CAS PubMed Google Scholar
Sebastian LA, Reeder S, Williams M. Determining target heart rate for exercising in a cardiac rehabilitation program: a retrospective study. J Cardiovasc Nurs. 2015;30:164–71. https://doi.org/10.1097/JCN.0000000000000154.
Mielke M, Housh TJ, Hendrix RC, Zuniga J, Camic CL, Schmidt RJ, et al. A test for determining critical heart rate using the critical power model. J Strength Cond Res. 2011;25:504–10. https://doi.org/10.1519/JSC.0B013E3181B62C43.
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