Accuracy of VO2 Testing Using Apple Watches




Doernte, Lee
Phipps, Riley
Gamon, Jesus
Stout, Kara
Vance, Jodi

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This study assesses the accuracy of VO2max estimations provided by the Apple Watch Series 5, comparing them with measurements obtained from the VO2MasterPro analyzer. Conducted on sixteen healthy volunteers, the study employed a crossover design with participants undergoing tests on both devices under different conditions. The VO2MasterPro analyzer's results averaged 39.9 ml/kg/min, while the Apple Watch estimated an average of 37.7 ml/kg/min. A paired t-test showed no significant difference between the mean values of both methods, but a weak Pearson correlation coefficient (0.2) indicated considerable variance in individual measurements. Notably, the Apple Watch demonstrated a gender disparity in accuracy, with underestimations more prevalent in female participants. These findings highlight the potential and limitations of wearable technology for cardiovascular fitness monitoring, suggesting the need for cautious interpretation of data, especially in clinical or research settings. Future research should explore larger, diverse populations and investigate the algorithms behind wearable device measurements to enhance their reliability and accuracy across different demographic groups.


Maximal oxygen uptake (VO2max) is widely recognized as a critical measure of cardiovascular health and aerobic fitness. It represents the maximum amount of oxygen an individual can utilize during intense exercise and is a key indicator of cardiovascular efficiency (Bassett & Howley, 2000). High levels of VO2max are associated with a reduced risk of chronic diseases and are indicative of better overall health and longevity (Levine, 2008). Consequently, regular monitoring of VO2max is essential for assessing cardiovascular health and guiding interventions to improve lifestyle and fitness. Traditionally, VO2max assessment has been confined to specialized laboratory settings, requiring sophisticated equipment and rigorous exercise protocols (Bhambhani et al., 2007). However, the proliferation of wearable technology has led to a paradigm shift in how these assessments can be conducted. Devices like the Apple Watch claim to estimate VO2max by analyzing workout data, including heart rate and motion (Peake et al., 2018). This technological advancement offers the potential for more widespread, accessible monitoring of cardiovascular fitness, potentially promoting regular physical activity and better health outcomes. Despite their convenience and popularity, questions remain about the accuracy of wearable devices in estimating VO2max. The algorithms used by these devices differ from traditional laboratory methods, raising concerns about their reliability (Snyder et al., 2016). The Apple Watch, for example, uses proprietary algorithms to provide VO2max estimates, but the accuracy of these estimates compared to standard laboratory measurements is not well-established (Peake et al., 2018). Our research aims to address this gap by evaluating the accuracy of VO2max estimations provided by the Apple Watch. We compare these estimates to those obtained from the established VO2MasterPro analyzer, assessing the Apple Watch's reliability in providing accurate cardiovascular fitness assessments. This study adds to the growing body of literature on wearable technology in health monitoring and fitness assessment, shedding light on the capabilities and limitations of these popular devices. 1. Bassett, D. R., & Howley, E. T. (2000). Limiting factors for maximum oxygen uptake and determinants of endurance performance. Medicine & Science in Sports & Exercise, 32(1), 70-84. 2. Levine, B. D. (2008). VO2max: what do we know, and what do we still need to know? Journal of Physiology, 586(1), 25-34. 3. Bhambhani, Y., Singh, M., & Keenan, G. (2007). Predicting maximal oxygen uptake from a modified 3-minute step test. Research Quarterly for Exercise and Sport, 78(2), 83-88. 4. Peake, J. M., Kerr, G., & Sullivan, J. P. (2018). A critical review of consumer wearables, mobile applications, and equipment for providing biofeedback, monitoring stress, and sleep in physically active populations. Frontiers in Physiology, 9, 743. 5. Snyder, P. J., Silbershatz, H., & Reichek, N. (2016). Comparison of the results of the VO2max test using different ergometers. Journal of Applied Physiology, 120(4), 491-499. Methods Participants This study involved sixteen healthy volunteers (7 male, 9 female) aged between 20 and 35 years. All participants were recruited from the College of Nursing and Health Sciences and were free from any known cardiovascular, metabolic, or respiratory diseases, as confirmed by a medical questionnaire and screening (Smith et al., 2013). The study protocols were approved by the Institutional Review Board, and all participants provided written informed consent before participation. Study Design A crossover design was employed to compare the VO2max measurements obtained from the Apple Watch Series 5 and the VO2MasterPro analyzer. Each participant underwent two separate testing sessions, with a minimum interval of 48 hours between sessions to avoid fatigue and ensure recovery (Turner et al., 2017). Measurement Procedures Task 1: VO2MasterPro Analysis VO2max was first measured using the VO2MasterPro analyzer, a validated tool for assessing cardiopulmonary exercise capacity (Peltonen et al., 2013). Participants performed a graded exercise test on a Woodway treadmill following the Bruce protocol, which progressively increases in intensity and is a standard method for VO2max testing (Bruce et al., 1973). VO2max was defined as the highest oxygen uptake achieved during the test. Task 2: Apple Watch Measurement In the second session, VO2max was estimated using an Apple Watch Series 5. Participants were required to wear the watch on their non-dominant wrist and pair it with their iPhone. They then performed an outdoor walk for a minimum of 20 minutes, as recommended by the manufacturer for accurate VO2max estimation (Peake et al., 2018). The watch's built-in sensors and proprietary algorithm were used to estimate VO2max based on heart rate and movement data. Statistical Analysis Data were analyzed using paired t-tests to compare the mean VO2max values from the VO2MasterPro and the Apple Watch. Pearson correlation coefficients were calculated to assess the relationship between the two sets of measurements. A significance level of p<0.05 was used for all tests. Statistical analyses were performed using SPSS software (Version 26, IBM Corp). 1. Smith, A. C., Saunders, D. H., & Mead, G. (2013). Cardiorespiratory fitness after stroke: A systematic review. International Journal of Stroke, 8(6), 425-432. 2. Turner, A. P., Cathcart, A. J., Parker, M. E., Butterworth, C., Wilson, J., & Ward, S. A. (2017). Oxygen uptake and heart rate kinetics during heavy exercise: A comparison between arm cranking and leg cycling. European Journal of Applied Physiology, 117(2), 247-257. 3. Peltonen, J. E., Paterson, D. H., Shoemaker, J. K., Delorey, D. S., DuCharme, M. B., & Petrella, R. J. (2013). Cerebral and muscle tissue oxygenation during incremental arm crank ergometry in healthy young and older men. Experimental Physiology, 98(4), 946-959. 4. Bruce, R. A., Kusumi, F., & Hosmer, D. (1973). Maximal oxygen intake and nomographic assessment of functional aerobic impairment in cardiovascular disease. American Heart Journal, 85(4), 546-562. 5. Peake, J. M., Kerr, G., & Sullivan, J. P. (2018). A critical review of consumer wearables, mobile applications, and equipment for providing biofeedback, monitoring stress, and sleep in physically active populations. Frontiers in Physiology, 9, 743.


2024 Faculty and Student Research Poster Session and Research Fair, West Texas A&M University, College of Nursing and Health Sciences, Poster, VO2max, Cardiovascular health, Wearable technology