ASSESSMENT OF FREE-LIVING DAILY PHYSICAL ACTIVITY IN OLDER CLAUDICANTS: VALIDATION AGAINST DOUBLY LABELED WATER 432

1997 ◽  
Vol 29 (Supplement) ◽  
pp. 75
Author(s):  
A. W. Gardner ◽  
E. T. Poehlman
Keyword(s):  
Physical Activity ◽  
Daily Physical Activity ◽  
Doubly Labeled Water ◽  
Free Living

scholarly journals Daily physical activity assessment: comparison between movement registration and doubly labeled water

1996 ◽  
Vol 81 (2) ◽  
pp. 1019-1026 ◽  
Author(s):  
C. V. Bouten ◽  
W. P. Verboeket-van de Venne ◽  
K. R. Westerterp ◽  
M. Verduin ◽  
J. D. Janssen
Keyword(s):  
Physical Activity ◽  
Metabolic Rate ◽  
Body Movement ◽  
Daily Physical Activity ◽  
Activity Level ◽  
Energy Estimates ◽  
Physical Activity Assessment ◽  
Doubly Labeled Water ◽  
Free Living ◽  
Activity Assessment

The use of movement registration for daily physical activity assessment was evaluated during a 7-day period in 30 free-living subjects. Body movement was registered with a Tracmor motion sensor consisting of a triaxial accelerometer and a data unit for on-line processing of accelerometer output over 1-min intervals. Average Tracmor output was correlated against four different energy estimates: 1) average daily metabolic rate (ADMR), determined with doubly labeled water; 2) ADMR-sleeping metabolic rate (SMR; determined in a respiration chamber); 3) (ADMR-SMR) per kilogram of body mass; and 4) the overall physical activity level (PAL = ADMR/SMR). The highest correlation was found for the relationship between Tracmor output and PAL (r = 0.58). After correction for Tracmor values arising from vibrations produced by transportation means, this correlation was improved to 0.73. There was no difference between Tracmor output and PAL in discriminating between overall activity levels with "low" (PAL < 1.60), "moderate" (1.60 < or = PAL < or = 1.85), and "high" (PAL > 1.85) intensity. It is concluded that the Tracmor can be used in free-living subjects to distinguish among interindividual as well as intraindividual levels of daily physical activity.

scholarly journals A Machine Learning Classifier for Detection of Physical Activity Types and Postures During Free-Living

2021 ◽  
pp. 1-8
Author(s):  
Kerstin Bach ◽  
Atle Kongsvold ◽  
Hilde Bårdstu ◽  
Ellen Marie Bardal ◽  
Håkon S. Kjærnli ◽  
...  
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Ground Truth ◽  
Daily Physical Activity ◽  
Gradient Boosting ◽  
Free Living ◽  
Recording Time ◽  
Learning Classifier ◽  
Extreme Gradient Boosting ◽  
Activity Types

Introduction: Accelerometer-based measurements of physical activity types are commonly used to replace self-reports. To advance the field, it is desirable that such measurements allow accurate detection of key daily physical activity types. This study aimed to evaluate the performance of a machine learning classifier for detecting sitting, standing, lying, walking, running, and cycling based on a dual versus single accelerometer setups during free-living. Methods: Twenty-two adults (mean age [SD, range] 38.7 [14.4, 25–68] years) were wearing two Axivity AX3 accelerometers positioned on the low back and thigh along with a GoPro camera positioned on the chest to record lower body movements during free-living. The labeled videos were used as ground truth for training an eXtreme Gradient Boosting classifier using window lengths of 1, 3, and 5 s. Performance of the classifier was evaluated using leave-one-out cross-validation. Results: Total recording time was ∼38 hr. Based on 5-s windowing, the overall accuracy was 96% for the dual accelerometer setup and 93% and 84% for the single thigh and back accelerometer setups, respectively. The decreased accuracy for the single accelerometer setup was due to a poor precision in detecting lying based on the thigh accelerometer recording (77%) and standing based on the back accelerometer recording (64%). Conclusion: Key daily physical activity types can be accurately detected during free-living based on dual accelerometer recording, using an eXtreme Gradient Boosting classifier. The overall accuracy decreases marginally when predictions are based on single thigh accelerometer recording, but detection of lying is poor.

Effect of Free-Living Daily Physical Activity on Salivary Secretory IgA in Elderly

2007 ◽  
Vol 39 (4) ◽  
pp. 593-598 ◽  
Author(s):  
KAZUHIRO SHIMIZU ◽  
FUMINORI KIMURA ◽  
TAKAYUKI AKIMOTO ◽  
TAKAO AKAMA ◽  
SHINYA KUNO ◽  
...  
Keyword(s):  
Physical Activity ◽  
Daily Physical Activity ◽  
Secretory Iga ◽  
Free Living

scholarly journals The Relationship between Free-Living Daily Physical Activity and the Severity of Peripheral Arterial Occlusive Disease

1997 ◽  
Vol 2 (4) ◽  
pp. 286-291 ◽  
Author(s):  
Debra J Sieminski ◽  
Andrew W Gardner
Keyword(s):  
Physical Activity ◽  
Intermittent Claudication ◽  
Peripheral Arterial Occlusive Disease ◽  
Ankle Brachial Index ◽  
Arterial Occlusive Disease ◽  
Daily Physical Activity ◽  
Occlusive Disease ◽  
Free Living ◽  
Peripheral Arterial ◽  
The Relationship

The purposes of this study were to assess the magnitude of the reduction in free-living daily physical activity of claudicants compared with age-matched controls, and to examine the relationship between the severity of peripheral arterial occlusive disease (PAOD) and free-living daily physical activity. Eighty-five PAOD patients with intermittent claudication and 59 non-PAOD subjects with a resting ankle/brachial index (ABI) of 0.63 ± 0.20 and 1.21 ± 0.08, respectively, were monitored for 2 consecutive weekdays with an accelerometer and pedometer worn on each hip. The times to onset and to maximal claudication pain were also measured in the claudicants during a graded treadmill test to assess the functional limitations imposed by PAOD. The PAOD group had a 42% lower energy expenditure as measured from the accelerometer (357 ± 238 kcal/day versus 616 ± 363 kcal/day; p < 0.001) and a 45% lower pedometer reading (4737 ± 2712 steps/day versus 8672 ± 4235 steps/day; p < 0.001) than the non-PAOD group. Furthermore, the relationship between free-living daily physical activity and ABI in PAOD patients was significant for both the accelerometer ( r = 0.41; p < 0.001) and the pedometer ( r = 0.41; p < 0.001). The rate of decline in free-living daily activity was 42 kcal/day and 612 steps/day per 0.10 drop in ABI. The correlation between free-living daily physical activity and time to maximal claudication pain (6:25 ± 3:30 min:s) in the PAOD group was significant for both the accelerometer ( r = 0.30; p = 0.05) and the pedometer ( r = 0.36; p = 0.03). However, the time to onset of claudication pain (3:02 ± 2:22 min:s) in the PAOD group was not related to either the accelerometer ( r = −0.02; p = 0.86) or the pedometer ( r = 0.18; p = 0.28) activity values. In conclusion, free-living daily physical activity was 42% to 45% lower in PAOD patients with intermittent claudication than in apparently healthy subjects of similar age. Moreover, claudicants were progressively more sedentary with an increase in PAOD severity.

scholarly journals Energy Requirements and Physical Activity of Older Free-Living African-Americans: A Doubly Labeled Water Study1

1998 ◽  
Vol 83 (5) ◽  
pp. 1529-1534
Author(s):  
Raymond D. Starling ◽  
Michael J. Toth ◽  
Dwight E. Matthews ◽  
Eric T. Poehlman
Keyword(s):  
Physical Activity ◽  
African Americans ◽  
Energy Requirements ◽  
Doubly Labeled Water ◽  
Free Living

The Effect of Cigarette Smoking on Free-Living Daily Physical Activity in Older Claudication Patients

Angiology ◽  
1997 ◽  
Vol 48 (11) ◽  
pp. 947-955 ◽  
Author(s):  
Andrew W. Gardner ◽  
Debra J. Sieminski ◽  
Lois A. Killewich ◽  
Andrew W. Gardner
Keyword(s):  
Physical Activity ◽  
Cigarette Smoking ◽  
Daily Physical Activity ◽  
Free Living

scholarly journals Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study

10.2196/13938 ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. e13938 ◽  
Author(s):  
Haruka Murakami ◽  
Ryoko Kawakami ◽  
Satoshi Nakae ◽  
Yosuke Yamada ◽  
Yoshio Nakata ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Wearable Devices ◽  
Doubly Labeled Water ◽  
Free Living ◽  
Daily Lives ◽  
Self Monitoring ◽  
Metabolic Chamber ◽  
Positive Correlations

Background Self-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established. Objective We examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method. Methods A total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices. Results On the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=−.13 to .37) and Spearman (ρ=−.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw. Conclusions Most wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Sign in / Sign up

Export Citation Format

Share Document