scholarly journals Measurement of Physical Activity by Shoe-Based Accelerometers—Calibration and Free-Living Validation

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2333
Author(s):  
Jonatan Fridolfsson ◽  
Daniel Arvidsson ◽  
Stefan Grau
Keyword(s):  
Physical Activity ◽  
Feasible Solution ◽  
Laboratory Data ◽  
Laboratory Setting ◽  
Free Living ◽  
Conflicting Evidence ◽  
Calibration Models ◽  
Workplace Setting ◽  
The Relationship ◽  
Sensor Positions

There is conflicting evidence regarding the health implications of high occupational physical activity (PA). Shoe-based accelerometers could provide a feasible solution for PA measurement in workplace settings. This study aimed to develop calibration models for estimation of energy expenditure (EE) from shoe-based accelerometers, validate the performance in a workplace setting and compare it to the most commonly used accelerometer positions. Models for EE estimation were calibrated in a laboratory setting for the shoe, hip, thigh and wrist worn accelerometers. These models were validated in a free-living workplace setting. Furthermore, additional models were developed from free-living data. All sensor positions performed well in the laboratory setting. When the calibration models derived from laboratory data were validated in free living, the shoe, hip and thigh sensors displayed higher correlation, but lower agreement, with measured EE compared to the wrist sensor. Using free-living data for calibration improved the agreement of the shoe, hip and thigh sensors. This study suggests that the performance of a shoe-based accelerometer is similar to the most commonly used sensor positions with regard to PA measurement. Furthermore, it highlights limitations in using the relationship between accelerometer output and EE from a laboratory setting to estimate EE in a free-living setting.

scholarly journals Objective measurement of physical activity in Macaca fascicularis

1982 ◽  
Vol 16 (3) ◽  
pp. 240-243
Author(s):  
Wayne T. Corbett ◽  
Harry M. Schey ◽  
A. W. Green
Keyword(s):  
Physical Activity ◽  
Standard Deviation ◽  
Macaca Fascicularis ◽  
Living Environment ◽  
Activity Levels ◽  
Free Living ◽  
Activity Measurements ◽  
Active Intermediate ◽  
The Mean ◽  
The Relationship

The mean and standard deviation over 24 h for 3 groups of animals - active, intermediate and inactive - in physical activity units were 10948 ± 3360, 2611 ± 1973 and 484 ± 316 respectively. The differences were significant ( P = 0·004), demonstrating the ability of the method to distinguish between groups that can be visibly differentiated. The small within-animal physical activity standard deviation (18·85 PAU) obtained in another group, suggests that it also yields reliable physical activity measurements for non-human primates. The monitoring device used can discriminate between individual nonhuman primate physical activity levels in a free-living environment and does not alter daily behaviour. This makes possible the study of the relationship between physical activity and atherosclerosis in nonhuman primates.

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.

Evaluating Relationships Between Sleep and Next-Day Physical Activity in Young Women

2020 ◽  
Vol 17 (9) ◽  
pp. 874-880
Author(s):  
Bruce W. Bailey ◽  
Landon S. Deru ◽  
William F. Christensen ◽  
Andrew J. Stevens ◽  
Stephen Tanner Ward ◽  
...  
Keyword(s):  
Physical Activity ◽  
Structural Equation ◽  
Vigorous Physical Activity ◽  
Equation Model ◽  
Driving Factor ◽  
Adult Women ◽  
Free Living ◽  
Wake Time ◽  
The Relationship ◽  
Free Living Conditions

Background: To evaluate the relationship between sleep and next-day physical activity (PA) under free-living conditions in women. Methods: Sleep and PA were measured objectively for 7 consecutive days by accelerometry in 330 young adult women (aged 17–25 y). A structural equation model was used to evaluate the relationship between the driving factor of sleep (total sleep or morning wake time) and the amount of nonsleep sedentary (SED) and moderate to vigorous physical activity (MVPA) each day. Results: With sleep duration as the driving factor, the estimates of βSED and βMVPA were −0.415 and −0.093, respectively (P ≤ .05). For every hour slept, a 24.9-minute reduction in SED time and a 5.58-minute reduction in MVPA were observed. With wake time as the driving factor, the estimates of βSED and βMVPA were −0.636 and −0.149, respectively. For every wake time that was 1 hour later, a 38.2-minute decrease in SED and a 8.9-minute decrease in MVPA (P ≤ .05) were observed. Conclusions: Women who wake later or who sleep longer tend to get less MVPA throughout the day. Getting up earlier and going to bed earlier may support behaviors that improve PA and lifestyle.

scholarly journals IS VARIABILITY OF FREE-LIVING ACTIVITY ASSOCIATED WITH PHYSICAL AND MENTAL FATIGABILITY IN OLDER ADULTS?

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S233-S234
Author(s):  
Jessica L Graves ◽  
Robert T Krafty ◽  
Jaroslaw Harezlak ◽  
Eric J Shiroma ◽  
Nancy W Glynn
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Cohort Study ◽  
Standard Deviation ◽  
Rise Time ◽  
Activity Patterns ◽  
Relative Activity ◽  
Energy Reserves ◽  
Free Living ◽  
The Relationship

Abstract Greater fatigability in older adults may be moderated by physical activity (PA). However, what features of PA timing are most strongly related to fatigability remains unknown. We examined the relationship between variability of free-living activity patterns and perceived physical and mental fatigability using the Pittsburgh Fatigability Scale (PFS, 0-50pts, higher=greater fatigability) in older adults from the Developmental Epidemiologic Cohort Study (DECOS, n=57, age=70-91yrs, 61% female). We assessed PA using ActiGraph GT3X+ over 7 days. Mean activity, standard deviation (SD) of mean activity across days, and relative activity [(mean at each bin)/(total mean)] were calculated across 24-hours in 4-hour bins , adjusting for estimated rise-time. Lower SD of PA from 0-4 hours after rising was associated with greater PFS physical scores (r=-0.27, p=0.05). No measures of PA correlated with PFS mental scores. In older adults with lower physical fatigability, associations with greater variability in activity may indicate larger energy reserves.

scholarly journals Relation of body composition to daily physical activity in free-living Japanese adult women

2011 ◽  
Vol 106 (7) ◽  
pp. 1117-1127 ◽  
Author(s):  
Jonghoon Park ◽  
Kazuko Ishikawa-Takata ◽  
Shigeho Tanaka ◽  
Yuki Hikihara ◽  
Kazunori Ohkawara ◽  
...  
Keyword(s):  
Physical Activity ◽  
Vigorous Physical Activity ◽  
Physical Activities ◽  
Activity Level ◽  
Fat Free Mass ◽  
Adult Women ◽  
Japanese Adult ◽  
Free Living ◽  
Daily Physical Activities ◽  
The Relationship

The objective of the present study was to investigate the relationship between the indices of body size such as BMI, fat-free mass index (FFMI, FFM/height2), fat mass index (FMI, FM/height2), and body fat percentage (%BF), and physical activities assessed by the doubly-labelled water (DLW) method and an accelerometer in free-living Japanese adult women. We conducted a cross-sectional study in 100 female subjects ranging in age from 31 to 69 years. Subjects were classified in quartiles of BMI, FFMI, FMI and %BF. Daily walking steps and the duration of light to vigorous physical activity were simultaneously assessed by an accelerometer for the same period as the DLW experiment. Only physical activity-related energy expenditure (PAEE)/FFM and PAEE/body weight (BW) decreased in the highest quartile of BMI. Physical activity level, PAEE/FFM and PAEE/BW decreased in the highest quartile of FMI and %BF, whereas they were not different among quartiles of FFMI. Daily walking steps and the duration of moderate- and vigorous-intensity physical activities decreased or tended to decrease in the highest quartile of FMI and %BF, but did not differ among quartiles of FFMI and BMI. These results clearly showed that Japanese adult women with higher fat deposition obviously had a low level of physical activities assessed by both the DLW method and accelerometry, but those with larger BMI had lower PAEE/FFM and PAEE/BW only. Our data suggest that the relationship between obesity and daily physical activities should be discussed using not only BMI but also FMI or %BF.

scholarly journals The Relationship Between Iron Status and Free‐Living Physical Activity in Indian School Children

2015 ◽  
Vol 29 (S1) ◽  
Author(s):  
Brendan Denvir ◽  
Sarah Luna ◽  
Shobha Udipi ◽  
Padmini Ghugre ◽  
Eric Przybyszewski ◽  
...  
Keyword(s):  
Physical Activity ◽  
School Children ◽  
Iron Status ◽  
Free Living ◽  
Indian School ◽  
The Relationship

scholarly journals Actigraphy-Based Associations Between Chronotype and Physical Activity in Older Adults

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 784-784
Author(s):  
Hilary Hicks ◽  
Genna Losinski ◽  
Alexandra Laffer ◽  
Amber Watts
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Older Adult ◽  
Total Activity ◽  
Time Of Day ◽  
Living Environment ◽  
Future Research ◽  
Free Living ◽  
Middle Aged Adults ◽  
The Relationship

Abstract Chronotype is a measure of the time of day people prefer to be most active or to sleep. There is a known relationship between chronotype and engagement in physical activity in young and middle-aged adults, such that individuals with a morning chronotype engage in more physical activity compared to those with an evening chronotype. Our study aimed to replicate this finding in an older adult sample. Actigraphy can be used to measure both physical activity and sleep. Because of its ability to capture information about bedtime and arise time, actigraphy can serve as an objective measurement of chronotype. Participants were 159 older adults (ages 60-89, M = 74.73) who wore an ActiGraph GT9X on their non-dominant wrist for 7 days in a free-living environment. Chronotype was measured continuously using the midpoint of the ActiGraph-calculated sleep interval. We used multiple regression to determine the relationship between physical activity and chronotype adjusting for sex, age, and body mass index. Results suggest that while these variables explain a significant amount of variance in physical activity, R2 = 19.0%, F (4, 152) = 8.921, p &lt; .001, there is no significant relationship between chronotype and total physical activity in our sample, ß= -.117, p = .114. These findings are inconsistent with what has been shown in younger samples and suggest that the relationship between chronotype and physical activity may change as one ages. Future research should consider whether particular physical activity intensities (vs. total activity) may have a relationship with chronotype in older adults.

scholarly journals What Is behind Changes in Resting Heart Rate and Heart Rate Variability? A Large-Scale Analysis of Longitudinal Measurements Acquired in Free-Living

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7932
Author(s):  
Marco Altini ◽  
Daniel Plews
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Effect Size ◽  
Physical Activity Level ◽  
Alcohol Intake ◽  
Activity Level ◽  
Resting Heart Rate ◽  
Free Living ◽  
The Relationship

The aim of this study was to investigate the relationship between heart rate and heart rate variability (HRV) with respect to individual characteristics and acute stressors. In particular, the relationship between heart rate, HRV, age, sex, body mass index (BMI), and physical activity level was analyzed cross-sectionally in a large sample of 28,175 individuals. Additionally, the change in heart rate and HRV in response to common acute stressors such as training of different intensities, alcohol intake, the menstrual cycle, and sickness was analyzed longitudinally. Acute stressors were analyzed over a period of 5 years for a total of 9 million measurements (320±374 measurements per person). HRV at the population level reduced with age (p < 0.05, r = −0.35, effect size = moderate) and was weakly associated with physical activity level (p < 0.05, r = 0.21, effect size = small) and not associated with sex (p = 0.35, d = 0.02, effect size = negligible). Heart rate was moderately associated with physical activity level (p < 0.05, r = 0.30, effect size = moderate) and sex (p < 0.05, d = 0.63, effect size = moderate) but not with age (p = 0.35, r = −0.01). Similar relationships between BMI, resting heart rate (p < 0.05, r = 0.19, effect size = small), and HRV (p < 0.05, r = −0.10, effect size = small) are shown. In response to acute stressors, we report a 4.6% change in HRV (p < 0.05, d = 0.36, effect size = small) and a 1.3% change in heart rate (p < 0.05, d = 0.38, effect size = small) in response to training, a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and a 12% reduction in HRV (p < 0.05, d = 0.55, effect size = moderate) after high alcohol intake, a 1.6% change in heart rate (p < 0.05, d = 1.41, effect size = large) and a 3.2% change in HRV (p < 0.05, d = 0.80, effect size = large) between the follicular and luteal phases of the menstrual cycle, and a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and 10% reduction in HRV (p < 0.05, d = 0.47, effect size = moderate) during sickness. Acute stressors analysis revealed how HRV is a more sensitive but not specific marker of stress. In conclusion, a short resting heart rate and HRV measurement upon waking using a smartphone app can effectively be used in free-living to quantify individual stress responses across a large range of individuals and stressors.

scholarly journals RELATIONSHIP BETWEEN PHYSICAL ACTIVITY PARTICIPATION AND RECOVERY OUTCOMES IN COLLEGE-AGED ADULTS WITH A CONCUSSION

2021 ◽  
Author(s):  
Kyle M. Petit ◽  
Christopher Kuenze ◽  
Karin A. Pfeiffer ◽  
Nathan Fitton ◽  
Mathew Saffarian ◽  
...  
Keyword(s):  
Physical Activity ◽  
Symptom Severity ◽  
Recovery Time ◽  
Statistical Significance ◽  
A Priori ◽  
Free Living ◽  
Multiple Regressions ◽  
Percent Time ◽  
Cognitive Rest ◽  
The Relationship

ABSTRACT Context: Previously, the most common treatment for a concussion was prolonged physical and cognitive rest. Recent research suggests that earlier physical activity (PA) may be better at promoting recovery. Research has not evaluated the relationship between free-living PA (e.g., walking) and symptom reporting or recovery duration. Objective: To assess the relationship between free-living physical activity (PA) participation and two recovery outcomes in college-aged adults with a concussion. Design: Prospective Cohort Setting: Division 1 & 3 Universities Participants: Thirty-two college-aged adults (68.8% female, age: 19.8±1.4) with a concussion. Main Outcome Measures: Participants completed a post-concussion symptom evaluation at visits 1 (&lt;72 hours from concussion) and 2 (8 days later). Between visits, participants' PA was monitored using an Actigraph GT9X Link PA monitor and expressed as total PA (counts per minute) and percent time of PA spent in moderate-to-vigorous intensity (%MVPA). Recovery time was the number of days from injury occurrence to medical clearance. Separate hierarchical multiple regressions evaluated the relationship between total PA and each recovery variable (visit 2 symptom severity, recovery time). Additionally, separate exploratory hierarchical multiple regressions evaluated the relationship between %MVPA and each recovery variable. Statistical significance was set a priori at p ≤ .05. Results: Participants averaged 2446±441 counts per minute and spent 12.1±4.2% of their PA performing MVPA. Participants yielded median symptom severities of 28[24] and 2[8] for visit 1 and 2, respectively. Average recovery time was 14.7±7.5 days. Total PA did not significantly contribute to the model for visit 2 symptom severity (p=.122) or recovery time (p=.301). Similarly, %MVPA had little contribution to the model for visit 2 symptom severity (p=.358) or recovery time (p=.276). Conclusion: Results suggest that free-living PA may not be enough to reduce symptoms or shorten recovery. Thus, clinicians may need to provide patients with more structured PA protocols mimicking previous research.

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