scholarly journals Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations

2017 ◽  
Vol 47 (9) ◽  
pp. 1821-1845 ◽  
Author(s):  
Jairo H. Migueles ◽  
Cristina Cadenas-Sanchez ◽  
Ulf Ekelund ◽  
Christine Delisle Nyström ◽  
Jose Mora-Gonzalez ◽  
...  
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Data Collection ◽  
Accelerometer Data

Effect of Incentive Amount on U.S. Adolescents’ Participation in an Accelerometer Data Collection Component of a National Survey

Field Methods ◽  
2021 ◽  
pp. 1525822X2198984
Author(s):  
April Y. Oh ◽  
Andrew Caporaso ◽  
Terisa Davis ◽  
Laura A. Dwyer ◽  
Linda C. Nebeling ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Collection ◽  
National Survey ◽  
Monetary Incentive ◽  
Behavioral Research ◽  
Accelerometer Data ◽  
Web Based ◽  
Demographic Subgroups

Behavioral research increasingly uses accelerometers to provide objective estimates of physical activity. This study extends research on methods for collecting accelerometer data among youth by examining whether the amount of a monetary incentive affects enrollment and compliance in a mail-based accelerometer study of adolescents. We invited a subset of adolescents in a national web-based study to wear an accelerometer for seven days and return it by mail; participants received either $20 or $40 for participating. Enrollment did not significantly differ by incentive amount. However, adolescents receiving the $40 incentive had significantly higher compliance (accelerometer wear and return). This difference was largely consistent across demographic subgroups. Those in the $40 group also wore the accelerometer for more time than the $20 group on the first two days of the study. Compared to $20, a $40 incentive may promote youth completion of mail-based accelerometer studies.

Feature Selection for Unsupervised Machine Learning of Accelerometer Data Physical Activity Clusters – A Systematic Review

2021 ◽  
Author(s):  
Petra J. Jones ◽  
Mike Catt ◽  
Melanie J. Davies ◽  
Charlotte L. Edwardson ◽  
Evgeny M. Mirkes ◽  
...  
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Systematic Review ◽  
Feature Selection ◽  
Accelerometer Data ◽  
Unsupervised Machine Learning ◽  
Selection For

scholarly journals Development and Evaluation of an Accelerometer-Based Protocol for Measuring Physical Activity Levels in Cancer Survivors: Development and Usability Study

10.2196/18491 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e18491
Author(s):  
Tracy E Crane ◽  
Meghan B Skiba ◽  
Austin Miller ◽  
David O Garcia ◽  
Cynthia A Thomson
Keyword(s):  
Physical Activity ◽  
Ovarian Cancer ◽  
Data Collection ◽  
Cancer Survivors ◽  
Accelerometer Data ◽  
Activity Tracking ◽  
Activity Data ◽  
Convenience Sample ◽  
Time Points ◽  
Activity Measurements

Background The collection of self-reported physical activity using validated questionnaires has known bias and measurement error. Objective Accelerometry, an objective measure of daily activity, increases the rigor and accuracy of physical activity measurements. Here, we describe the methodology and related protocols for accelerometry data collection and quality assurance using the Actigraph GT9X accelerometer data collection in a convenience sample of ovarian cancer survivors enrolled in GOG/NRG 0225, a 24-month randomized controlled trial of diet and physical activity intervention versus attention control. Methods From July 2015 to December 2019, accelerometers were mailed on 1337 separate occasions to 580 study participants to wear at 4 time points (baseline, 6, 12, and 24 months) for 7 consecutive days. Study staff contacted participants via telephone to confirm their availability to wear the accelerometers and reviewed instructions and procedures regarding the return of the accelerometers and assisted with any technology concerns. Results We evaluated factors associated with wear compliance, including activity tracking, use of a mobile app, and demographic characteristics with chi-square tests and logistic regression. Compliant data, defined as ≥4 consecutive days with ≥10 hours daily wear time, exceeded 90% at all study time points. Activity tracking, but no other characteristics, was significantly associated with compliant data at all time points (P<.001). This implementation of data collection through accelerometry provided highly compliant and usable activity data in women who recently completed treatment for ovarian cancer. Conclusions The high compliance and data quality associated with this protocol suggest that it could be disseminated to support researchers who seek to collect robust objective activity data in cancer survivors residing in a wide geographic area.

Calibration of raw accelerometer data to measure physical activity: A systematic review

2018 ◽  
Vol 61 ◽  
pp. 98-110 ◽  
Author(s):  
Márcio de Almeida Mendes ◽  
Inácio C.M. da Silva ◽  
Virgílio V. Ramires ◽  
Felipe F. Reichert ◽  
Rafaela C. Martins ◽  
...  
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Accelerometer Data

scholarly journals Relationship of Physical Activity and Sedentary Time with Metabolic Health in Children and Adolescents Measured by Accelerometer: A Narrative Review

Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 709
Author(s):  
Jungjun Lim ◽  
Joon-Sik Kim ◽  
Soyoung Park ◽  
On Lee ◽  
Wi-Young So
Keyword(s):  
Physical Activity ◽  
Data Collection ◽  
Children And Adolescents ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Health Indicators ◽  
Metabolic Health ◽  
Moderate Intensity ◽  
Accelerometer Data ◽  
Relationship Of

The purpose of this study was to summarize the associations of physical activity (PA) and sedentary time (SED) with metabolic health and examine the effects of time reallocation on metabolic health in adolescents using accelerometer data. A literature search was conducted using PubMed, ScienceDirect, Web of Science, Cochran Library, and Google Scholar, and 27 articles were reviewed. Recent research generally confirms the associations of PA and SED with metabolic health. High PA levels and low SED levels had a positive relationship with metabolic health. Moreover, reallocating 10 min of daily SED to PA was associated with better metabolic health indicators. These results were stronger for moderate-to-vigorous physical activity than for light intensity PA. Thus, efforts to convert SED into PA of at least moderate intensity appear to be an effective strategy to prevent metabolic disease development in children and adolescents. However, some of the associations between PA and metabolic health indicators were inconsistent, depending on age, obesity degree, and PA intensity. Additionally, various accelerometer data collection and processing criteria impact the interpretation of the results. Therefore, consistent accelerometer data collection and analysis methods are needed in future studies. Further, intervention studies are required to verify the causality and effectiveness of the isotemporal substitution model.

scholarly journals A Systematic Review of Data Collection Techniques Used to Measure Preschool Children’s Knowledge of and Preference for Physical Activity

2019 ◽  
Vol 16 (6) ◽  
pp. 964
Author(s):  
Nicola Wiseman ◽  
Christin Rossmann ◽  
Neil Harris
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Early Childhood ◽  
Data Collection ◽  
Accurate Data ◽  
Data Collection Tool ◽  
Validity And Reliability ◽  
Study Population ◽  
Activity Choices ◽  
Children’S Physical Activity

Background: Early childhood has been identified as a crucial period in which children develop physical activity preferences and behaviors. Both the knowledge of and preferences for physical activity are key proximal indicators of activity choices in children. Thus, accurate data collection tools are required to measure these variables. This review evaluates the data collection techniques that have been utilised to assess preschool children’s knowledge of and preference for physical activity, and examines the validity and reliability of existing techniques. Methods: A systematic search for relevant studies published from 1980 through to December 2017 was conducted via ProQuest, CINAHL, Embase, Scopus, ERIC, PubMed, MEDLINE, and ScienceDirect. Results: Fourteen studies were eligible for inclusion in the review. The identified studies employed a limited but disparate range of techniques to assess children’s physical activity knowledge and preferences. Findings reveal that four techniques were consistently used across the reviewed studies, including: interviews, structured play-based activities, questionnaires, and observations. Only four out of 14 included studies reported the assessment of the validity of the data collection tool used, and six reported testing the measures for at least one type of reliability. Conclusion: There is a need for validated and reliable measures to assess children’s knowledge of and preference for physical activity. Greater consideration is required to align data collection techniques with the characteristics, needs and abilities of this study population.

scholarly journals Development and Evaluation of an Accelerometer-Based Protocol for Measuring Physical Activity Levels in Cancer Survivors: Development and Usability Study (Preprint)

2020 ◽  
Author(s):  
Tracy E Crane ◽  
Meghan B Skiba ◽  
Austin Miller ◽  
David O Garcia ◽  
Cynthia A Thomson
Keyword(s):  
Physical Activity ◽  
Ovarian Cancer ◽  
Data Collection ◽  
Cancer Survivors ◽  
Accelerometer Data ◽  
Activity Tracking ◽  
Activity Data ◽  
Convenience Sample ◽  
Time Points ◽  
Activity Measurements

BACKGROUND The collection of self-reported physical activity using validated questionnaires has known bias and measurement error. OBJECTIVE Accelerometry, an objective measure of daily activity, increases the rigor and accuracy of physical activity measurements. Here, we describe the methodology and related protocols for accelerometry data collection and quality assurance using the Actigraph GT9X accelerometer data collection in a convenience sample of ovarian cancer survivors enrolled in GOG/NRG 0225, a 24-month randomized controlled trial of diet and physical activity intervention versus attention control. METHODS From July 2015 to December 2019, accelerometers were mailed on 1337 separate occasions to 580 study participants to wear at 4 time points (baseline, 6, 12, and 24 months) for 7 consecutive days. Study staff contacted participants via telephone to confirm their availability to wear the accelerometers and reviewed instructions and procedures regarding the return of the accelerometers and assisted with any technology concerns. RESULTS We evaluated factors associated with wear compliance, including activity tracking, use of a mobile app, and demographic characteristics with chi-square tests and logistic regression. Compliant data, defined as ≥4 consecutive days with ≥10 hours daily wear time, exceeded 90% at all study time points. Activity tracking, but no other characteristics, was significantly associated with compliant data at all time points (<i>P</i>&lt;.001). This implementation of data collection through accelerometry provided highly compliant and usable activity data in women who recently completed treatment for ovarian cancer. CONCLUSIONS The high compliance and data quality associated with this protocol suggest that it could be disseminated to support researchers who seek to collect robust objective activity data in cancer survivors residing in a wide geographic area.

OS10.5.A BrainWear: Longitudinal, objective assessment of physical activity in 42 HGG patients

2021 ◽  
Vol 23 (Supplement_2) ◽  
pp. ii13-ii14
Author(s):  
S Dadhania ◽  
L Pakzad-Shahabi ◽  
S Mistry ◽  
K Le-Calvez ◽  
W Saleem ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Collection ◽  
Objective Assessment ◽  
Moderate Activity ◽  
Accelerometer Data ◽  
Healthy Controls ◽  
Uk Biobank ◽  
Triaxial Accelerometer ◽  
High Quality ◽  
Wear Time

Abstract BACKGROUND In patients with High Grade Glioma (HGG), QoL and physical function decline with progressive disease (PD). Objective assessment of physical functioning is challenging as patients spend most of their time away from the hospital. Wearable technology allows measurement of objective, continuous activity data in a non-obtrusive manner. BrainWear is a phase II feasibility study, collecting longitudinal physical activity (PA) data from patients with primary and secondary brain tumours. MATERIAL AND METHODS All agreed to wear an Axivity AX3 triaxial accelerometer and completed the EORTC QLQ C30 and BN20, the Montreal Cognitive Assessment (MoCA) and Multidimensional fatigue inventory (MFI) questionnaires. Accelerometers were changed at 14-day intervals, and PRO questionnaires completed at pre-specified study intervals. Age-sex matched controls were identified from the UK Biobank 7-day accelerometer study. Raw accelerometer data was processed using UK Biobank accelerometer software and inclusion of high-quality wear time selected as ≥72 hours of data in a 7-day data collection and data in each 1-hour period of a 24-hour cycle over multiple days. We analysed variation in activity by patient demographics and treatment days. The wilcoxin-signed rank test was used to compare participant activity between radiotherapy treatment days and non-treatment days, mixed effects models were used to evaluate longitudinal changes in activity and we used k-means clustering to characterise clusters of PA behaviours. RESULTS We have collected 3458 days of accelerometer data from 42 HGG patients with a median age of 59, 80% of which has been classified as high quality. Patients &gt;60 years spend more time doing moderate activity compared to those &lt;60 years (52 vs 33 minutes/day, p=0.012), and there are significant differences in mean vector magnitude (17.12 vs 16.85 mg, p=0.013) and walking (91 vs 72 minutes/day) between radiotherapy and non-radiotherapy days. In patients having a 6-week RT course, time spent in daily moderate activity falls 4-fold between week 1 and the second week after RT completion (70 minutes to 16 minutes/day). Comparing HGG patients to healthy controls shows a significant difference in time spent across all activities (p&lt;0.05). K-means clustering analysis shows three distinct clusters, with 87% of HGG patients falling into the very inactive or moderately active groups. CONCLUSION Digital remote health monitoring is feasible and acceptable with 80% of data classified as high-quality wear-time suggesting good patient adherence. Triaxial accelerometer data collection captures objective evidence of a significant reduction in moderate daily activity at the time of expected peak RT side-effects and patients walk almost 30% less on non-RT treatment days. HGG patients show significantly lower levels of activity compared to matched healthy controls.

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