Dataset Information

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

ABSTRACT:

Purpose

To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE) in manual wheelchair users (MWUs).

Methods

Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg) completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W) and upper arm (UA). Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis.

Results

Accelerometer outputs at each anatomical location were significantly (p < .01) associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88). Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W.

Conclusion

The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

SUBMITTER: Nightingale TE

PROVIDER: S-EPMC4425541 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

Nightingale Tom Edward TE Walhin Jean-Philippe JP Thompson Dylan D Bilzon James Lee John JL

PloS one 20150508 5

<h4>Purpose</h4>To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE) in manual wheelchair users (MWUs).<h4>Methods</h4>Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg) completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. GT3X+ and GEN ...[more]

PMID: 25955304

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Project description:Accurate, nonintrusive, and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) for the prediction of EE using room calorimetry and doubly labeled water (DLW) and established accelerometry cut points for PA levels.Fifty preschoolers, mean ± SD age of 4.5 ± 0.8 yr, participated in room calorimetry for minute-by-minute measurements of EE, accelerometer counts (AC) (Actiheart and ActiGraph GT3X+), and HR (Actiheart). Free-living 105 children, ages 4.6 ± 0.9 yr, completed the 7-d DLW procedure while wearing the devices. AC cut points for PA levels were established using smoothing splines and receiver operating characteristic curves.On the basis of calorimetry, mean percent errors for EE were -2.9% ± 10.8% and -1.1% ± 7.4% for CSTS models and -1.9% ± 9.6% and 1.3% ± 8.1% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. On the basis of DLW, mean percent errors were -0.5% ± 9.7% and 4.1% ± 8.5% for CSTS models and 3.2% ± 10.1% and 7.5% ± 10.0% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Applying activity EE thresholds, final accelerometer cut points were determined: 41, 449, and 1297 cpm for Actiheart x-axis; 820, 3908, and 6112 cpm for ActiGraph vector magnitude; and 240, 2120, and 4450 cpm for ActiGraph x-axis for sedentary/light, light/moderate, and moderate/vigorous PA (MVPA), respectively. On the basis of confusion matrices, correctly classified rates were 81%-83% for sedentary PA, 58%-64% for light PA, and 62%-73% for MVPA.The lack of bias and acceptable limits of agreement affirms the validity of the CSTS and MARS models for the prediction of EE in preschool-aged children. Accelerometer cut points are satisfactory for the classification of sedentary, light, and moderate/vigorous levels of PA in preschoolers.

Project description:BackgroundPhysical activity (PA) must be performed regularly to accrue health benefits. However, the majority of manual wheelchair users do not meet PA recommendations. Existing community-based PA programs for manual wheelchair users appear to work, but effect sizes are small and retention is low. Existing PA programs may not fully implement some psychosocial factors that are strongly linked with PA (eg, autonomy). The use of peers and mobile phone technology in the Smartphone Peer PA Counseling (SPPAC) program represents a novel approach to cultivating a PA-supportive environment for manual wheelchair users.ObjectiveThe primary objective is to compare change in objective PA between the experimental (SPPAC) and control groups from baseline to postintervention (10 weeks) and follow-up (3 months). Changes in and relationships between subjective PA, wheelchair skills, motivation, self-efficacy (for overcoming barriers to PA for manual wheelchair use), satisfaction of psychological needs for PA, and satisfaction with PA participation will be explored (secondary outcome). Program implementation will be explored (tertiary objective).MethodsA total of 38 community-living manual wheelchair users (≥18 years) will be recruited in a randomized controlled trial (RCT). Participants in both the control and experimental groups will receive existing PA guidelines. Participants in the experimental group will also receive the SPPAC program: 14 sessions (~30 min) over a 10-week period delivered by a peer trainer using a mobile phone. PA activities will be based on individuals' preferences and goals. Implementation of important theoretical variables will be enforced through a peer-trainer checklist. Outcomes for objective PA (primary) and subjective PA, wheelchair skills, motivation, self-efficacy, satisfaction of psychological needs, and satisfaction with participation will be collected at three time points (baseline, postintervention, follow-up). Multiple imputations will be used to treat missing data. A mixed-model ANCOVA will be conducted, controlling for covariates (primary and secondary objectives). The strength and direction of the relationships between the primary and secondary outcomes will be explored (secondary objective). Descriptive and content analysis will be used to appraise program implementation (tertiary objective).ResultsFunding has been obtained from the Craig Neilsen Foundation and the Canadian Disability Participation Project, with additional funds being sought from the Canadian Institute for Health Research and Fonds de Recherche du Québec-Santé. Pilot evaluation of intervention implementation is currently underway, with enrollment anticipated to begin early 2018.ConclusionsThere may be substantial benefits for the SPPAC program including limited burden on health care professionals, decreased barriers (eg. accessibility, transportation), development of peer social supports, and potential cost savings related to physical inactivity. Before conducting a large and expensive multisite RCT within a small heterogeneous population of manual wheelchair users, a pilot study affords a prudent step to establishing an adequate study protocol and implementation strategies.Trial registrationClinicalTrials.gov NCT02826707; https://clinicaltrials.gov/ct2/show/NCT02826707 (Archived by WebCite at http://www.webcitation.org/6pqIc14dU).

Project description:Background:Objective assessments of sedentary behavior and physical activity (PA) by using accelerometer-based wearable devices are ever expanding, given their importance in the global context of health maintenance. This study aimed to determine the reliability and validity of a new accelerometer-based analyzer (Fibion) for detecting different PAs and estimating energy expenditure (EE) during a simulated free-living day. Methods:The study consisted of two parts: a reliability (n = 18) and a validity (n = 19) test. Reliability was assessed by a 45 min protocol of repeated sitting, standing, and walking (i.e., 3 × 15 min, repeated twice), using both Fibion and ActiGraph. Validity was assessed by a 12 h continuous sequence tasks of different types (sitting, standing, walking, and cycling) and intensities (light [LPA], moderate [MPA], and vigorous [VPA]) of PA. Two Fibion devices were worn on the thigh (FT) and in the pocket (FP), respectively and were compared with criteria measures, such as direct observation (criterion 1) and oxygen consumption by a portable gas analyzer, K4b2 (criterion 2). Results:FT (intra-class correlation coefficients (ICCs): 0.687-0.806) provided similar reliability as the Actigraph (ICCs: 0.661-0.806) for EE estimation. However, the measurement error (ME) of FT compared to the actual time records indicated an underestimation of duration by 5.1 ± 1.2%, 3.8 ± 0.3% and 14.9 ± 2.6% during sitting, walking, and standing, respectively. During the validity test, FT but not FP showed a moderate agreement but lager variance with the criteria (1 and 2) in assessing duration of sitting, long sitting, LPA, MPA, and VPA (p > 0.05, ICCs: 0.071-0.537), as well as for EE estimation of standing, LPA, MPA, and VPA (p > 0.05, ICCs: 0.673-0.894). Conclusions:FT provided similar reliability to that of the Actigraph. However, low correlations between subsequent measurements of both devices indicated large random MEs, which were somewhat diminished during the simulated 12 h real-life test. Furthermore, FT may accurately determine the types, intensities of PA and EE during prolonged periods with substantial changes in postures, indicating that the location of the accelerometer is essential. Further study with a large cohort is needed to confirm the usability of Fibion, especially for detecting the low-intensity PAs.

Dataset Information

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

Purpose

Methods

Results

Conclusion

Publications

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

Similar Datasets

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