Instantaneous VO2 from a wearable device

Assessing the Accuracy of Smartwatch-Based Estimation of Maximum Oxygen Uptake Using the Apple Watch Series 7: Validation Study

BACKGROUND

Determining maximum oxygen uptake (VO2max) is essential for evaluating cardiorespiratory fitness. While laboratory-based testing is considered the gold standard, sports watches or fitness trackers offer a convenient alternative. However, despite the high number of wrist-worn devices, there is a lack of scientific validation for VO2max estimation outside the laboratory setting.

OBJECTIVE

This study aims to compare the Apple Watch Series 7's performance against the gold standard in VO2max estimation and Apple's validation findings.

METHODS

A total of 19 participants (7 female and 12 male), aged 18 to 63 (mean 28.42, SD 11.43) years were included in the validation study. VO2max for all participants was determined in a controlled laboratory environment using a metabolic gas analyzer. Thereby, they completed a graded exercise test on a cycle ergometer until reaching subjective exhaustion. This value was then compared with the estimated VO2max value from the Apple Watch, which was calculated after wearing the watch for at least 2 consecutive days and measured directly after an outdoor running test.

RESULTS

The measured VO2max (mean 45.88, SD 9.42 mL/kg/minute) in the laboratory setting was significantly higher than the predicted VO2max (mean 41.37, SD 6.5 mL/kg/minute) from the Apple Watch (t18=2.51; P=.01) with a medium effect size (Hedges g=0.53). The Bland-Altman analysis revealed a good overall agreement between both measurements. However, the intraclass correlation coefficient ICC(2,1)=0.47 (95% CI 0.06-0.75) indicated poor reliability. The mean absolute percentage error between the predicted and the actual VO2max was 15.79%, while the root mean square error was 8.85 mL/kg/minute. The analysis further revealed higher accuracy when focusing on participants with good fitness levels (mean absolute percentage error=14.59%; root-mean-square error=7.22 ml/kg/minute; ICC(2,1)=0.60 95% CI 0.09-0.87).

CONCLUSIONS

Similar to other smartwatches, the Apple Watch also overestimates or underestimates the VO2max in individuals with poor or excellent fitness levels, respectively. Assessing the accuracy and reliability of the Apple Watch's VO2max estimation is crucial for determining its suitability as an alternative to laboratory testing. The findings of this study will apprise researchers, physical training professionals, and end users of wearable technology, thereby enhancing the knowledge base and practical application of such devices in assessing cardiorespiratory fitness parameters.

Cardiorespiratory Fitness Estimation Based on Heart Rate and Body Acceleration in Adults With Cardiovascular Risk Factors: Validation Study

Background

Cardiorespiratory fitness (CRF) is an independent risk factor for cardiovascular morbidity and mortality. Adding CRF to conventional risk factors (eg, smoking, hypertension, impaired glucose metabolism, and dyslipidemia) improves the prediction of an individual’s risk for adverse health outcomes such as those related to cardiovascular disease. Consequently, it is recommended to determine CRF as part of individualized risk prediction. However, CRF is not determined routinely in everyday clinical practice. Wearable technologies provide a potential strategy to estimate CRF on a daily basis, and such technologies, which provide CRF estimates based on heart rate and body acceleration, have been developed. However, the validity of such technologies in estimating individual CRF in clinically relevant populations is poorly known.

Objective

The objective of this study is to evaluate the validity of a wearable technology, which provides estimated CRF based on heart rate and body acceleration, in working-aged adults with cardiovascular risk factors.

Methods

In total, 74 adults (age range 35-64 years; n=56, 76% were women; mean BMI 28.7, SD 4.6 kg/m²) with frequent cardiovascular risk factors (eg, n=64, 86% hypertension; n=18, 24% prediabetes; n=14, 19% type 2 diabetes; and n=51, 69% metabolic syndrome) performed a 30-minute self-paced walk on an indoor track and a cardiopulmonary exercise test on a treadmill. CRF, quantified as peak O₂ uptake, was both estimated (self-paced walk: a wearable single-lead electrocardiogram device worn to record continuous beat-to-beat R-R intervals and triaxial body acceleration) and measured (cardiopulmonary exercise test: ventilatory gas analysis). The accuracy of the estimated CRF was evaluated against that of the measured CRF.

Results

Measured CRF averaged 30.6 (SD 6.3; range 20.1-49.6) mL/kg/min. In all participants (74/74, 100%), mean difference between estimated and measured CRF was −0.1 mL/kg/min (P=.90), mean absolute error was 3.1 mL/kg/min (95% CI 2.6-3.7), mean absolute percentage error was 10.4% (95% CI 8.5-12.5), and intraclass correlation coefficient was 0.88 (95% CI 0.80-0.92). Similar accuracy was observed in various subgroups (sexes, age, BMI categories, hypertension, prediabetes, and metabolic syndrome). However, mean absolute error was 4.2 mL/kg/min (95% CI 2.6-6.1) and mean absolute percentage error was 16.5% (95% CI 8.6-24.4) in the subgroup of patients with type 2 diabetes (14/74, 19%).

Conclusions

The error of the CRF estimate, provided by the wearable technology, was likely below or at least very close to the clinically significant level of 3.5 mL/kg/min in working-aged adults with cardiovascular risk factors, but not in the relatively small subgroup of patients with type 2 diabetes. From a large-scale clinical perspective, the findings suggest that wearable technologies have the potential to estimate individual CRF with acceptable accuracy in clinically relevant populations.

Enhancing instantaneous oxygen uptake estimation by non-linear model using cardio-pulmonary physiological and motion signals

Oxygen uptake (VO₂) is an important parameter in sports medicine, health assessment and clinical treatment. At present, more and more wearable devices are used in daily life, clinical treatment and health care. The parameters obtained by wearables have great research potential and application prospect. In this paper, an instantaneous VO₂ estimation model based on XGBoost was proposed and verified by using data obtained from a medical-grade wearable device (Beijing SensEcho) at different posture and activity levels. Furthermore, physiological characteristics extracted from single-lead electrocardiogram, thoracic and abdominal respiration signal and tri-axial acceleration signal were studied to optimize the model. There were 29 healthy volunteers recruited for the study to collect data while stationary (lying, sitting, standing), walking, Bruce treadmill test and recuperating with SensEcho and the gas analyzer (Metalyzer 3B). The results show that the VO₂ values estimated by the proposed model are in good agreement with the true values measured by the gas analyzer (R² = 0.94 ± 0.03, n = 72,235), and the mean absolute error (MAE) is 1.83 ± 0.59 ml/kg/min. Compared with the estimation method using a separate heart rate as input, our method reduced MAE by 54.70%. At the same time, other factors affecting the performance of the model were studied, including the influence of different input signals, gender and movement intensity, which provided more enlightenment for the estimation of VO₂. The results show that the proposed model based on cardio-pulmonary physiological signals as inputs can effectively improve the accuracy of instantaneous VO₂ estimation in various scenarios of activities and was robust between different motion modes and state. The VO₂ estimation method proposed in this paper has the potential to be used in daily life covering the scenario of stationary, walking and maximal exercise.

Sports Participation and Physical Activity in Individuals with Heritable Thoracic Aortic Disease and Aortopathy Conditions

The evaluation and management of athletes with HTAD and aortopathy conditions requires shared decision-making encompassing the underlying condition, family history, aortic diameter, and type and intensity of sports and exercise. Mouse models of thoracic aortic disease show that low-to-moderate-level aerobic exercise can maintain aortic architecture and attenuate pathologic aortic root dilation. Although controlled trials in human are lacking, recreational physical activities performed at a low-to-moderate aerobic pace are generally low risk for most individuals with aortopathy conditions. High-intensity, competitive, and contact sports or physical activities are generally prohibited in individuals with aortopathy conditions.

Design, simulation, and fabrication of an ingestible capsule with gastric balloon for obesity treatment

The treatment of obesity based only on lifestyle changes has been shown ineffectiveness in a long-term period. The development of more definitive and non-invasive therapies has been the subject of study. In this paper, a magnetically driven ingestible capsule with the capacity to inflate a gastric balloon is devised, simulated, and fabricated. The balloon is inflated to a volume of 150 ml using an acid-base reaction between citric acid and potassium bicarbonate. Finite element method simulations were performed to study the interaction between the permanent external magnet and the ingestible capsule and confirm the magnetic activation mechanism. A fabrication process was proposed to manufacture a polydimethylsiloxane (PDMS) balloon in a simple, functional, and reproducible way. The two layers and 1:8 ratio balloons are the most cost-effective without compromising their mechanical properties. The capsule body parts manufactured by a three-dimensional (3D) printing process - Digital Light Processing (DLP) showed high accuracy and excellent resolution. This study demonstrated that the proposed ingestible capsule would successfully inflate the gastric balloon to treat obesity.

Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor

OBJECTIVE

To estimate instantaneous oxygen uptake VO₂ with a small, low-cost wearable sensor during exercise and daily activities in order to enable monitoring of energy expenditure (EE) in uncontrolled settings. We aim to do so using a combination of seismocardiogram (SCG), electrocardiogram (ECG) and atmospheric pressure (AP) signals obtained from a minimally obtrusive wearable device.

METHODS

In this study, subjects performed a treadmill protocol in a controlled environment and an outside walking protocol in an uncontrolled environment. During testing, the COSMED K5 metabolic system collected gold standard breath-by-breath (BxB) data and a custom-built wearable patch placed on the mid-sternum collected SCG, ECG and AP signals. We extracted features from these signals to estimate the BxB VO₂ data obtained from the COSMED system.

RESULTS

In estimating instantaneous VO₂, we achieved our best results on the treadmill protocol using a combination of SCG (frequency) and AP features (RMSE of 3.68 ± 0.98 ml/kg/min and R² of 0.77). For the outside protocol, we achieved our best results using a combination of SCG (frequency), ECG and AP features (RMSE of 4.3 ± 1.47 ml/kg/min and R² of 0.64). In estimating VO₂ consumed over one minute intervals during the protocols, our median percentage error was 15.8[Formula: see text] for the treadmill protocol and 20.5[Formula: see text] for the outside protocol.

CONCLUSION

SCG, ECG and AP signals from a small wearable patch can enable accurate estimation of instantaneous VO₂ in both controlled and uncontrolled settings. SCG signals capturing variation in cardio-mechanical processes, AP signals, and state of the art machine learning models contribute significantly to the accurate estimation of instantaneous VO₂.

SIGNIFICANCE

Accurate estimation of VO₂ with a low cost, minimally obtrusive wearable patch can enable the monitoring of VO₂ and EE in everyday settings and make the many applications of these measurements more accessible to the general public.

Lessons learned from a pilot randomized clinical trial of home-based exercise prescription before allogeneic hematopoietic cell transplantation

Allogeneic hematopoietic cell transplantation (alloHCT) is a life-saving technology that can cure otherwise incurable diseases, but imposes significant physiologic stress upon recipients. This stress leads to short-term toxicity and mid- to long-term physical function impairment in some recipients. Exercise interventions have demonstrated preliminary efficacy in preserving physical function in HCT recipients, but the role of these interventions prior to HCT (prehabilitative) is less known. We tested a 5- to 12-week, prehabilitative higher intensity home-based aerobic exercise intervention in a randomized study of alloHCT candidates. Of 113 patients screened, 34 were randomized to control or intervention groups, 16 underwent pre- and post-intervention peak oxygen consumption (VO2peak) testing, and 12 underwent pre- and post-intervention 6-min walk distance (6MWD) testing. No significant differences in VO2peak or 6MWD were seen pre- to post-intervention between intervention and control groups, but final numbers of evaluable participants in each group were too small to draw inferences regarding the efficacy of the intervention. We conclude that the design of our prehabilitative intervention was not feasible in this pilot randomized study, and make recommendations regarding the design of future exercise intervention studies in alloHCT.

Prediction of energy expenditure during activities of daily living by a wearable set of inertial sensors

Physical inactivity is responsible for 7-10% of all premature deaths worldwide. Thus, valid, reliable and unobtrusive methods for monitoring activities of daily living (ADL) to predict total energy expenditure (TEE) is desired. Multiple methods exist to quantify TEE, but microelectromechanical systems (MEMSs) are the only method, which has shown promising results and are applicable for long-term monitoring in the field. However, no perfect method exists for predicting TEE on a daily basis. The present study evaluates TEE estimation based on a MEMS (Xsens Link system) taking gender and heart rate into account. Fifteen individuals performed seven ADL wearing the Xsens Link system, a heart rate belt and an oxygen mask. Multiple linear regression models were established for sedentary and dynamic activities and evaluated by leave-one-out cross-validation and compared with indirect calorimetry. The linear regression model showed better prediction for dynamic activities (adjusted R² 0.95±0.16) compared to sedentary activities (adjusted R² 0.61±0.19). The root-mean-square error for the TEE estimation ranged between 0.02 and 0.08 kJ/min/kg for the sedentary and dynamic models, respectively. The study showed a viable approach to predict TEE in ADL compared to previously published results. Further studies are warranted to reduce the number of sensors in the estimation of TEE.

Innovations in energy expenditure assessment

PURPOSE OF REVIEW

Optimal nutritional therapy has been associated with better clinical outcomes and requires providing energy as closed as possible to measured energy expenditure. We reviewed the current innovations in energy expenditure assessment in humans, focusing on indirect calorimetry and other new alternative methods.

RECENT FINDINGS

Although considered the reference method to measure energy expenditure, the use of indirect calorimetry is currently limited by the lack of an adequate device. However, recent technical developments may allow a broader use of indirect calorimetry for in-patients and out-patients. An ongoing international academic initiative to develop a new indirect calorimeter aimed to provide innovative and affordable technical solutions for many of the current limitations of indirect calorimetry. New alternative methods to indirect calorimetry, including CO2 measurements in mechanically ventilated patients, isotopic approaches and accelerometry-based fitness equipments, show promises but have been either poorly studied and/or are not accurate compared to indirect calorimetry. Therefore, to date, energy expenditure measured by indirect calorimetry remains the gold standard to guide nutritional therapy.

SUMMARY

Some new innovative methods are demonstrating promises in energy expenditure assessment, but still need to be validated. There is an ongoing need for easy-to-use, accurate and affordable indirect calorimeter for daily use in in-patients and out-patients.