Evaluation of the SenseWear Pro Armband??? to Assess Energy Expenditure during Exercise

Jakicic, John M.; Marcus, Marsha D.; Gallagher, Kara I.; Randall, Colby; Thomas, Erin L.; Goss, Fredric L.; Robertson, Robert J.

doi:10.1249/01.mss.0000126805.32659.43

Cited by 298 publications

(289 citation statements)

References 10 publications

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“…However, no prior publication has suggested that the data collected by the physiologic sensors significantly may reduce the error in EE compared to accelerometry alone, in either normal or diseased subjects. This improvement in measurement accuracy likely due to the additional sensors may account for previous reports of improved accuracy of the PAM over a broader range of exercise intensities (42) and during activities such as upper arm exercise and cycling (21,41), which are reported to be less accurately measured using accelerometers alone (36).…”

Section: Discussionmentioning

confidence: 87%

“…The PAM in this study has previously been validated in normal subjects (21,41,42) and we have additionally documented its reproducibility and accuracy in COPD subjects. However, we further demonstrated that either the PAM proprietary software modeling or (most likely) the additional sensors improved significantly the explained variance in EE determination compared to the accelerometer data alone, from 68% to 88%.…”

Section: Discussionmentioning

confidence: 92%

“…This error is due to a number of factors: (a) individual variability in mechanical and metabolic efficiency, (b) non-linearity in the relationship of acceleration and EE (36), (c) creation of a single prediction equation in a pooled manner across diverse types of activities (21), and (d) the inability to estimate EE during activities which are poorly reflected solely by accelerometer activity, such as walking on an incline or cycling (36). As such, investigators have used advanced software approaches, such as non-linear (19), patientspecific (38) and activity-specific prediction equations (21), or hardware approaches, such as additional physiologic sensors, to improve EE determination (20,39,40).…”

Section: Discussionmentioning

confidence: 99%

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Activity Monitoring and Energy Expenditure in COPD Patients: A Validation Study

Patel

Benzo

Slivka

et al. 2007

COPD: Journal of Chronic Obstructive Pulmonary Disease

128

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There is increasing interest in the objective measurement of physical activity in chronic obstructive pulmonary disease (COPD) patients due to the close relationship between physical activity level, health, disability and mortality. We aimed to (a) determine the validity and reproducibility of an activity monitor that integrates accelerometry with multiple physiologic sensors in the determination of energy expenditure in COPD subjects and (b) to document the independent contribution of the additional physiologic sensors to accelerometry measures in improving true energy expenditure determination. Eight subjects (4 male, FEV 1 56.4 ± 14.1%, RV 145.0 ± 75.7%) performed 2 separate 6-minute walk and 2 incremental shuttle walk exercise tests. Energy expenditure was calculated during each exercise test using the physiologic activity monitor and compared to a validated exhaled breath metabolic system. Test-retest reproducibility of physiologic activity monitor during the walking tests was comparable to an exhaled breath metabolic system. Physiologic sensor data significantly improved the explained variance in energy expenditure determination (r 2 = 0.88) compared to accelerometry data alone (r 2 = 0.68). This physiologic activity monitor provides a valid and reproducible estimate of energy expenditure during slow to moderate paced walking in a laboratory setting and represents an objective method to assess activity in COPD subjects.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

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Activity Monitoring and Energy Expenditure in COPD Patients: A Validation Study

Patel

Benzo

Slivka

et al. 2007

COPD: Journal of Chronic Obstructive Pulmonary Disease

128

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“…39 Interestingly, physical activity was not increased by CPAP treatment, suggesting that OSA per se is not the main contributor to reduced physical activity levels. 40 In our study, we measured physical activity patterns with an accelerometer validated in healthy subjects 41 and in diabetics. 34 This device, which has also been recently validated in OSA during sleep, 39 is considered one of the most reliable means of estimating physical activity and its patterns in free living conditions.…”

Section: Discussionmentioning

confidence: 99%

Low Physical Activity Is a Determinant for Elevated Blood Pressure in High Cardiovascular Risk Obstructive Sleep Apnea

Mendelson

Tamisier

Laplaud³

et al. 2013

Respir Care

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INTRODUCTION:Obstructive sleep apnea (OSA) is associated with cardiovascular morbidity, including hypertension. Beyond the severity of nocturnal hypoxia, other factors such as metabolic abnormalities but also sedentary behaviors and insufficient physical activity may contribute to elevated blood pressure (BP). To clarify the respective role of these factors as determinants of BP in OSA patients, we examined the relationship between BP and anthropometrics, severity of sleep apnea, and objectively measured physical activity and sedentary behaviors. METHODS: Ninetyfive adults presenting with OSA (apnea-hypopnea index > 10 events/h) and high cardiovascular risk (63.3 ؎ 8.8 y; body mass index: 29.9 ؎ 4.9 kg/m 2 ; apnea-hypopnea index: 41.3 ؎ 17.5/h; cardiovascular risk score: 13.5 ؎ 3.7%) were included. Physical activity and sedentary behaviors were objectively assessed by actigraphy, and self-measured home BP monitoring was measured. Logistic regression models adjusted for sex, age, and body mass index were built to identify the predictors of self-measured morning and evening BP. RESULTS: Physical activity was significantly related to obesity but not to the severity of sleep apnea or sleepiness. Sedentary behaviors were associated with self-measured morning and evening systolic BP (r ‫؍‬ 0.32, P ‫؍‬ .002; r ‫؍‬ 0.29, P ‫؍‬ .004). Steps per day were inversely associated with evening BP (r ‫؍‬ ؊0.27, P ‫؍‬ .01). Univariate analysis identified steps/d and time spent in vigorous physical activity as determinants for evening self-measured BP. In multivariate analysis, only steps/d were identified as a significant determinant of evening BP. CONCLUSIONS: Physical activity is the major determinant for evening BP in adults with OSA presenting high cardiovascular risk. Our results emphasize the need for lifestyle counseling programs in combination with CPAP to encourage regular physical activity in OSA subjects to obtain better BP control. (ClinicalTrials.gov registration NCT01226641.)

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“…The activities in this category (dressing, washing and drying dishes, and folding laundry) are activities that use a large degree of upper extremity movement. Jakicic et al (34) found overestimation by the SWA of 21.7% in an arm ergometry task, despite finding underestimation in the other activities included in the exercise protocol. This might signify that the SWA does not accurately represent energy expenditure accrued during upper extremity activities.…”

mentioning

confidence: 94%

Study to Determine the Criterion Validity of the SenseWear Armband as a Measure of Physical Activity in People With Rheumatoid Arthritis

Tierney

Fraser

Purtill

et al. 2013

Arthritis Care & Research

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Objective. Measuring physical activity in people with rheumatoid arthritis (RA) is of great importance in light of the increased mortality in this population due to cardiovascular disease. Validation of activity monitors in specific populations is recommended to ensure the accuracy of physical activity measurement. Thus, the purpose of this study was to determine the validity of the SenseWear Pro3 Armband (SWA) as a measure of physical activity during activities of daily living (ADL) in people with RA. Methods. Fourteen subjects (8 men and 6 women) with a diagnosis of RA were recruited from rheumatology clinics at the Mid-Western Regional Hospitals, Limerick, Ireland. Participants undertook a series of ADL of varying intensities. The SWA was compared to the criterion measures of the Oxycon Mobile indirect calorimetry system (energy expenditure in kJ) and of manual video observation (step count). Bland and Altman, intraclass correlation coefficient (ICC), and correlation analyses were done using SPSS, version 19.0. Results. The SWA showed substantial agreement (ICC 0.717, P < 0.001) and a strong relationship (Pearson's correlation coefficient ‫؍‬ 0.852) compared with the criterion measure when estimating energy expenditure during ADL. However, it was found that the SWA overestimated energy expenditure, particularly at higher intensity levels. The ability of the SWA to estimate step counts during ADL was poor (ICC 0.304, P ‫؍‬ 0.038). Conclusion. The SWA can be considered a valid tool to estimate energy expenditure during ADL in the RA population; however, attention should be paid to its tendency to overestimate energy expenditure.

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Evaluation of the SenseWear Pro Armband??? to Assess Energy Expenditure during Exercise

Cited by 298 publications

References 10 publications

Activity Monitoring and Energy Expenditure in COPD Patients: A Validation Study

Activity Monitoring and Energy Expenditure in COPD Patients: A Validation Study

Low Physical Activity Is a Determinant for Elevated Blood Pressure in High Cardiovascular Risk Obstructive Sleep Apnea

Study to Determine the Criterion Validity of the SenseWear Armband as a Measure of Physical Activity in People With Rheumatoid Arthritis

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