Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study

Kwon, Soon Bin; Ahn, Joong Woo; Lee, Seung Min; Lee, Joonnyong; Lee, Dong Hoon; Hong, Jee-Young; Kim, Hee Chan; Yoon, Hyung‐Jin

doi:10.2196/13327

Cited by 17 publications

(12 citation statements)

References 28 publications

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“…These percentages increased by 11-16% following to addition of the PA score obtained using the questionnaire in the model (Table 4) These SEE values can be replaced with %SEE values of 10.8-11.2%. Other types of VO 2max estimation studies reported %SEE values of 11.4% in the 20-m shuttle run test study [26] and 10-15% in wearable device studies [13,27,28]. The SEE values in the present study seem to be favorable when compared with those calculated in other VO 2max prediction studies.…”

Section: Discussionsupporting

confidence: 58%

Workers’ physical activity data contribute to estimating maximal oxygen consumption: a questionnaire study to concurrently assess workers’ sedentary behavior and cardiorespiratory fitness

Matsuo

Takahashi

2020

BMC Public Health

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Background: Sedentary behavior (SB) and cardiorespiratory fitness (CRF) are important issues in occupational health. Developing a questionnaire to concurrently assess workers' SB and CRF could fundamentally improve epidemiological research. The Worker's Living Activity-time Questionnaire (WLAQ) was developed previously to assess workers' sitting time. WLAQ can be modified to evaluate workers' CRF if additional physical activity (PA) data such as PA frequency, duration, and intensity are collected. Methods: A total of 198 working adults (93 women and 105 men; age, 30-60 years) completed anthropometric measurements, a treadmill exercise test for measuring maximal oxygen consumption (VO 2max), and modified WLAQ (m-WLAQ, which included questions about PA data additional to the original questions). Multiple regression analyses were performed to develop prediction equations for VO 2max. The generated models were cross-validated using the predicted residual error sum of squares method. Among the participants, the data of 97 participants who completed m-WLAQ twice after a 1-week interval were used to calculate intraclass correlation coefficient (ICC) for the test-retest reliability analyses. Results: Age (r = − 0.29), sex (r = 0.48), body mass index (BMI, r = − 0.20), total sitting time (r = − 0.15), and PA score (total points for PA data, r = 0.47) were significantly correlated with VO 2max. The models that included age, sex, and BMI accounted for 43% of the variance in measured VO 2max [standard error of the estimate (SEE) = 5.04 ml•kg − 1 •min − 1 ]. These percentages increased to 59% when the PA score was included in the models (SEE = 4.29 ml•kg − 1 •min − 1). Cross-validation analyses demonstrated good stability of the VO 2max prediction models, while systematic underestimation and overestimation of VO 2max were observed in individuals with high and low fitness, respectively. The ICC of the PA score was 0.87 (0.82-0.91), indicating excellent reliability. Conclusions: The PA score obtained using m-WLAQ, rather than sitting time, correlated well with measured VO 2max. The equation model that included the PA score as well as age, sex, and BMI had a favorable validity for estimating VO 2max. Thus, m-WLAQ can be a useful questionnaire to concurrently assess workers' SB and CRF, which makes it a reasonable resource for future epidemiological surveys on occupational health.

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Section: Discussionsupporting

confidence: 58%

Workers’ physical activity data contribute to estimating maximal oxygen consumption: a questionnaire study to concurrently assess workers’ sedentary behavior and cardiorespiratory fitness

Matsuo

Takahashi

2020

BMC Public Health

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“…The resulting regression equation showed a good correlation between estimated and measured V O 2max (r ϭ 0.85), and the standard error of the estimate was 14% (437 mL O 2 /min). A similar approach was presented in a recent report (16) showing how daily energy expenditure and HR could be combined with anthropometric variables to predict V O 2max as derived by submaximal tests. The main disadvantage of those methods using free-living data to generate a fitness index from wearable sensor data is the high bias toward sedentary data, which is abundant during the monitoring period.…”

Section: Discussionmentioning

confidence: 94%

Cardiorespiratory fitness estimation from heart rate and body movement in daily life

Bonomi

Hoor

Morree

et al. 2020

Journal of Applied Physiology

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Low cardiorespiratory fitness (CRF) increases risk of all-cause mortality and cardiovascular events. Periodic CRF assessment can have an important preventive function. The objective of this study was to develop a protocol-free method to estimate CRF in daily life based on heart rate (HR) and body acceleration measurements. Acceleration and HR data were collected from 37 subjects (men = 49%) while they performed a standardized laboratory activity protocol (sitting, walking, running, cycling) and during a 5-day free-living monitoring period. CRF was determined by oxygen uptake (V̇o2max) during maximal exercise testing. A doubly labeled water-validated equation was used to predict total energy expenditure (TEE) from acceleration data. A fitness index was defined as the ratio between TEE and HR (TEE-pulse). Activity recognition techniques were used to process acceleration features and classify sedentary, ambulatory, and other activity types. Regression equations based on TEE-pulse data from each activity type were developed to predict V̇o2max. TEE-pulse measured within each activity type of the laboratory protocol was highly correlated with V̇o2max ( r from 0.74–0.91). Averaging the outcome of each activity-type specific equation based on TEE-pulse from the laboratory data led to accurate estimates of V̇o2max [root mean square error (RMSE): 300 mL O2/min, or 10%]. The difference between laboratory and free-living determined TEE-pulse was 3.7 ± 11% ( r = 0.85). The prediction method preserved the prediction accuracy when applied to free-living data (RMSE: 367 mL O2/min, or 12%). Measurements of body acceleration and HR can be used to predict V̇o2max in daily life. Activity-specific prediction equations are needed to achieve highly accurate estimates of CRF. NEW & NOTEWORTHY This is among the very few studies validating, in free-living conditions, a method to estimate cardiorespiratory fitness using heart rate and body acceleration data. A novel parameter called TEE-pulse, which was defined as the ratio between accelerometer-determined energy expenditure and heart rate, was highly correlated with maximal oxygen uptake (V̇o2max). Activity classification and the use of activity-selective prediction equations outperformed previously published methods for estimating V̇o2max from heart rate and acceleration data.

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“…There are a number of validated tests including the 6-minute walk test, 18 activity monitors 19 and the resting heart rate method 20 that can be used to give an estimate of a patient's VO 2 max. All three methods can be performed remotely, be self administered 19,20 or in the case of resting heart rate be extracted from existing data in healthcare records. This would allow clinicians to remotely assess patients' exercise capacity at home, without any additional burden in clinic time.…”

Section: How Could We Practically Test Exercise Capacity On a Large Smentioning

confidence: 99%

COVID-19 – does exercise prescription and maximal oxygen uptake (VO2 max) have a role in risk-stratifying patients?

Ahmed

2020

Clinical Medicine

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As the UK shields 'high risk' patients and enforces social distancing measures, patients will be at risk of significantly reducing physical activity levels. We explore the evidence base for COVID-19-specific recommendations and exercise interventions to 'precondition' patients prior to infection and appraise the role of maximal oxygen uptake (VO 2 max) as a risk-stratifying triage tool. We conclude that structured exercise programmes can be used to maintain physical activity levels and prevent deconditioning and that VO 2 max has the potential to be used as a clinically relevant triage tool during the COVID-19 outbreak.

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Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study

Cited by 17 publications

References 28 publications

Workers’ physical activity data contribute to estimating maximal oxygen consumption: a questionnaire study to concurrently assess workers’ sedentary behavior and cardiorespiratory fitness

Workers’ physical activity data contribute to estimating maximal oxygen consumption: a questionnaire study to concurrently assess workers’ sedentary behavior and cardiorespiratory fitness

Cardiorespiratory fitness estimation from heart rate and body movement in daily life

COVID-19 – does exercise prescription and maximal oxygen uptake (VO2 max) have a role in risk-stratifying patients?

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