Validity of Physical Activity Monitors for Estimating Energy Expenditure During Wheelchair Propulsion

2015 ◽  
Vol 12 (11) ◽  
pp. 1520-1526 ◽  
Author(s):  
Scott A. Conger ◽  
Stacy N. Scott ◽  
Eugene C. Fitzhugh ◽  
Dixie L. Thompson ◽  
David R. Bassett
Keyword(s):  
Energy Expenditure ◽  
Repeated Measures ◽  
Prediction Equation ◽  
Level Surface ◽  
Wheelchair Propulsion ◽  
Activity Monitors ◽  
Repeated Measures Anova ◽  
Main Effect ◽  
Physical Activity Monitors ◽  
Criterion Method

Background:It is unknown if activity monitors can detect the increased energy expenditure (EE) of wheelchair propulsion at different speeds or on different surfaces.Methods:Individuals who used manual wheelchairs (n = 14) performed 5 wheeling activities: on a level surface at 3 speeds, on a rubberized track at 1 fixed speed and on a sidewalk course at a self-selected speed. EE was measured using a portable indirect calorimetry system and estimated by an Actical (AC) worn on the wrist and a SenseWear (SW) activity monitor worn on the upper arm. Repeated-measures ANOVA was used to compare measured EE to the estimates from the standard AC prediction equation and SW using 2 different equations.Results:Repeated-measures ANOVA demonstrated a significant main effect between measured EE and estimated EE. There were no differences between the criterion method and the AC across the 5 activities. The SW overestimated EE when wheeling at 3 speeds on a level surface, and during sidewalk wheeling. The wheelchair-specific SW equation improved the EE prediction during low intensity activities, but error progressively increased during higher intensity activities.Conclusions:During manual wheelchair propulsion, the wrist-mounted AC provided valid estimates of EE, whereas the SW tended to overestimate EE.

scholarly journals Comparison of four Fitbit and Jawbone activity monitors with a research-grade ActiGraph accelerometer for estimating physical activity and energy expenditure

2017 ◽  
Vol 52 (13) ◽  
pp. 844-850 ◽  
Author(s):  
Mary T Imboden ◽  
Michael B Nelson ◽  
Leonard A Kaminsky ◽  
Alexander HK Montoye
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Repeated Measures ◽  
Prediction Equation ◽  
Activity Monitors ◽  
Actigraph Accelerometer ◽  
Repeated Measures Analysis ◽  
Research Grade ◽  
Similar Accuracy ◽  
Data Criterion

Background/aimConsumer-based physical activity (PA) monitors have become popular tools to track PA behaviours. Currently, little is known about the validity of the measurements provided by consumer monitors. We aimed to compare measures of steps, energy expenditure (EE) and active minutes of four consumer monitors with one research-grade accelerometer within a semistructured protocol.MethodsThirty men and women (18–80 years old) wore Fitbit One (worn at the waist), Fitbit Zip (waist), Fitbit Flex (wrist), Jawbone UP24 (wrist) and one waist-worn research-grade accelerometer (ActiGraph) while participating in an 80 min protocol. A validated EE prediction equation and active minute cut-points were applied to ActiGraph data. Criterion measures were assessed using direct observation (step count) and portable metabolic analyser (EE, active minutes). A repeated measures analysis of variance (ANOVA) was used to compare differences between consumer monitors, ActiGraph, and criterion measures. Similarly, a repeated measures ANOVA was applied to a subgroup of subjects who didn’t cycle.ResultsParticipants took 3321±571 steps, had 28±6 active min and expended 294±56 kcal based on criterion measures. Comparatively, all monitors underestimated steps and EE by 13%–32% (p<0.01); additionally the Fitbit Flex, UP24, and ActiGraph underestimated active minutes by 35%–65% (p<0.05). Underestimations of PA and EE variables were found to be similar in the subgroup analysis.ConclusionConsumer monitors had similar accuracy for PA assessment as the ActiGraph, which suggests that consumer monitors may serve to track personal PA behaviours and EE. However, due to discrepancies among monitors, individuals should be cautious when comparing relative and absolute differences in PA values obtained using different monitors.

Effect of Monitor Placement on the Daily Step Counts of Wrist and Hip Activity Monitors

2020 ◽  
Vol 3 (2) ◽  
pp. 164-169
Author(s):  
Susan Park ◽  
Lindsay P. Toth ◽  
Scott E. Crouter ◽  
Cary M. Springer ◽  
Robert T. Marcotte ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Styloid Process ◽  
Pairwise Comparisons ◽  
Daily Step ◽  
Ulnar Styloid ◽  
Activity Monitors ◽  
Step Counts ◽  
Main Effect ◽  
The Right ◽  
Main Effects

Purpose: To examine the effect of activity monitor placement on daily step counts when monitors are worn at different positions on the wrist/forearm and the hip. Methods: Participants (N = 18) wore eight different models (four wrist and four hip models) across four days. Each day, one hip and one wrist model were selected, and four identical monitors of each model were worn on the right hip and the non-dominant wrist/forearm, respectively, during all waking hours. Step counts of each monitor were compared to the same model worn in the referent position (wrist: proximal to ulnar styloid process; hip: midline of thigh). Percent of referent steps and mean difference between observed and referent positions were computed. Significant differences in steps between positions for each method were determined using one-way repeated measures ANOVAs. For significant main effects, pairwise comparisons with Bonferroni corrections were used to determine which positions were significantly different. Results: All wrist methods showed a significant main effect for placement (p < .05) and alternate positions were 1–16% lower than the referent position. For hip methods, only the Omron HJ-325 differed across positions (p < .05), but differences were among non-referent positions and all were within ±2% of steps recorded by the referent position. Conclusions: Researchers should be aware that positions that deviate from the manufacturer’s recommended position at the wrist could influence step counts. Of all hip methods examined, the Omron had a significant placement effect which did not constitute a practical difference.

Accuracy Of Three Physical Activity Monitors To Measure Energy Expenditure During Activities Of Daily Living

2005 ◽  
Vol 37 (Supplement) ◽  
pp. S115
Author(s):  
George A. King ◽  
Sarah E. Deemer ◽  
Bernadette M. Franco ◽  
Charlie Potter ◽  
Karen J. Coleman
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Activities Of Daily Living ◽  
Daily Living ◽  
Activity Monitors ◽  
Physical Activity Monitors

Accuracy Of Three Physical Activity Monitors To Measure Energy Expenditure During Activities Of Daily Living

2005 ◽  
Vol 37 (Supplement) ◽  
pp. S115
Author(s):  
George A. King ◽  
Sarah E. Deemer ◽  
Bernadette M. Franco ◽  
Charlie Potter ◽  
Karen J. Coleman
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Activities Of Daily Living ◽  
Daily Living ◽  
Activity Monitors ◽  
Physical Activity Monitors

Validation of Three Physical Activity Monitors for Assessment of Energy Expenditure in Older Women

2015 ◽  
Vol 47 ◽  
pp. 246
Author(s):  
Glen M. Davis ◽  
Jasmine Yee ◽  
Bridget Abell ◽  
Leigh C. Ward ◽  
David Currow ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Older Women ◽  
Activity Monitors ◽  
Physical Activity Monitors

Initial Evaluation of the LifeForce Yoga Program as a Therapeutic Intervention for Depression

2008 ◽  
Vol 18 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Shannon Bennett ◽  
Amy Weintraub ◽  
Sat Bir Khalsa
Keyword(s):  
Repeated Measures ◽  
Self Report ◽  
Initial Training ◽  
Home Practice ◽  
Repeated Measures Anova ◽  
Symptoms Of Depression ◽  
Main Effect ◽  
Symptom Scores ◽  
Assessment Time ◽  
Post Hoc

There is a growing body of literature citing Yoga as an effective intervention for decreasing symptoms of depression. This naturalistic pilot study investigated the efficacy of the LifeForce Yoga Program in decreasing reported symptoms of depression and other mood symptoms. The sample consisted of 94 individuals who completed self-report questionnaire before participating in a five-day LifeForce Yoga training. 54 of these individuals completed the same questionnaire after two weeks of home practice following the training, and 33 participants completed these questionnaires two months after the initial training. Repeated measures ANOVA tests demonstrated a main effect for time, indicating that mean symptom scores decreased significantly across the assessment time points on nearly all of the outcome measures of interest. Post hoc t-tests showed that the statistically significant change occurred between Time 1 and Time 2, and was then largely maintained from Time 2 to Time 3. These results suggest that participation in a comprehensive Yoga program, designed specifically to address mood, can lead to decreased symptoms of depression and associated physical or mood states.

Validity of resting energy expenditure estimated by an activity monitor compared to indirect calorimetry

2009 ◽  
Vol 102 (1) ◽  
pp. 155-159 ◽  
Author(s):  
Jocilyn E. Dellava ◽  
Daniel J. Hoffman
Keyword(s):  
Energy Expenditure ◽  
Body Fat ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
Bioelectrical Impedance ◽  
Activity Monitor ◽  
Prediction Equation ◽  
Activity Monitors ◽  
Percentage Of Body Fat ◽  
Resting Energy

The use of activity monitors (triaxial accelerometers) to estimate total energy expenditure in kilocalories is dependent on the estimation of resting energy expenditure (REE). However, the REE estimated by activity monitors has not been validated against more precise techniques, such as indirect calorimetry (IC). Therefore, the objective of the present study was to compare REE estimated by the Actical activity monitor (ActMon) to that measured by IC and standard prediction equations of REE. Fifty healthy adults between 18 and 43 years of age were measured for weight and percentage of body fat using a digital scale and bioelectrical impedance. The REE estimated by the ActMon was only 129 kJ/d higher, but not statistically different (P>0·05), than the REE measured with IC. Using multiple linear regression, there was a positive relationship for men, but not for women, between fat mass (kg) and percentage of body fat and the difference in REE estimated by the ActMon compared to IC (P < 0·001). Therefore, in the cohort studied, the use of an activity monitor to estimate REE is valid when compared to IC, but not to a standard prediction equation of REE.

scholarly journals Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure

2016 ◽  
Vol 41 (7) ◽  
pp. 758-766 ◽  
Author(s):  
John B. Correa ◽  
John W. Apolzan ◽  
Desti N. Shepard ◽  
Daniel P. Heil ◽  
Jennifer C. Rood ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Weight Change ◽  
Medium Effect ◽  
Sensewear Armband ◽  
Activity Monitors ◽  
Daily Energy ◽  
Total Daily Energy Expenditure ◽  
Calorie Diet ◽  
Physical Activity Monitors ◽  
Monitoring Devices

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland–Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity.

scholarly journals Ground Reaction Force Comparison Between Barefoot and Shod Single Leg Landing at Varied Heights

2021 ◽  
Vol 9 (4) ◽  
pp. 29
Author(s):  
Jocelyn E. Arnett ◽  
Cameron D. Addie ◽  
Ludmila M. Cosio-Lima ◽  
Lee E. Brown
Keyword(s):  
Ground Reaction Force ◽  
Repeated Measures ◽  
Reaction Force ◽  
Force Plate ◽  
Collegiate Athletes ◽  
Ground Reaction Forces ◽  
Repeated Measures Anova ◽  
Main Effect ◽  
Reaction Forces ◽  
Main Effects

Background: Landing is a common movement that occurs in many sports. Barefoot research has gained popularity in examining how shoes alter natural movements. However, it is unknown how a single leg landing under barefoot conditions, as well as landing height, affects ground reaction forces (GRF). Objective: The purpose of this research was to examine the differences in GRF during a single leg landing under barefoot and shod conditions from various heights. Methods: Sixteen female Division II collegiate athletes, 8 basketball (age: 19.88 ± 0.64 yrs; height: 1.77 ± 0.09 m; mass: 75.76 ± 12.97 kg) and 8 volleyball (age: 20.00 ± 1.07 yrs; height: 1.74 ± 0.08 m; mass: 72.41 ± 5.41 kg), performed single leg landings from 12, 18, 24, and 30 inches barefoot and shod. An AMTI AccuGait force plate was used to record GRF. A 2 (condition) x 4 (box height) x 2 (sport) repeated measures ANOVA was performed to determine any GRF differences. Results: There were no significant three way or two-way interactions (p > 0.05). There was also no main effect for sport (p > 0.05). There were main effects for footwear and box height (p = 0.000) where shod (2295.121 ± 66.025 N) had greater impact than barefoot (2090.233 ± 62.684 N). Conclusions: Single leg barefoot landings resulted in less vertical GRF than shod landings. This could be due to increased flexion at the joints which aids in force absorption.

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