Journal for the measurement of physical behaviour最新文献_第6页

Investigating the Effects of Applying Different Actigraphy Processing Approaches to Examine the Sleep Data of Patients With Neuropathic Pain 探讨应用不同的活动描记处理方法检查神经性疼痛患者睡眠数据的效果

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0017

Hannah J. Coyle-Asbil, A. Bhatia, Andrew S. P. Lim, Mandeep Singh

{"title":"Investigating the Effects of Applying Different Actigraphy Processing Approaches to Examine the Sleep Data of Patients With Neuropathic Pain","authors":"Hannah J. Coyle-Asbil, A. Bhatia, Andrew S. P. Lim, Mandeep Singh","doi":"10.1123/jmpb.2022-0017","DOIUrl":"https://doi.org/10.1123/jmpb.2022-0017","url":null,"abstract":"Individuals suffering from neuropathic pain commonly report issues associated with sleep. To measure sleep in this population, researchers have used actigraphy. Historically, actigraphy data have been analyzed in the form of counts; however, due to the proprietary nature, many opt to quantify data in its raw form. Various processing techniques exist to accomplish this; however, it remains unclear how they compare to one another. This study sought to compare sleep measures derived using the GGIR R package versus the GENEActiv (GA) R Markdown tool in a neuropathic pain population. It was hypothesized that the processing techniques would yield significantly different sleep outcomes. One hundred and twelve individuals (mean age = 52.72 ± 13.01 years; 60 M) with neuropathic pain in their back and/or lower limbs were included. While simultaneously undergoing spinal cord stimulation, actigraphy devices were worn on the wrist for a minimum of 7 days (GA; 50 Hz). Upon completing the protocol, sleep outcome measures were calculated using (a) the GGIR R package and (b) the GA R Markdown tool. To compare these algorithms, paired-samples t tests and Bland–Altman plots were used to compare the total sleep time, sleep efficiency, wake after sleep onset, sleep onset time, and rise times. According to the paired-samples t test, the GA R Markdown yielded lower total sleep time and sleep efficiency and a greater wake after sleep onset, compared with the GGIR package. Furthermore, later sleep onset times and earlier rise times were reported by the GGIR package compared with the GA R Markdown.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87127070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CRIB: A Novel Method for Device-Based Physical Behavior Analysis CRIB:一种基于设备的物理行为分析新方法

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0059

P. Hibbing, S. Creasy, J. Carlson

{"title":"CRIB: A Novel Method for Device-Based Physical Behavior Analysis","authors":"P. Hibbing, S. Creasy, J. Carlson","doi":"10.1123/jmpb.2021-0059","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0059","url":null,"abstract":"Physical behaviors (e.g., sleep, sedentary behavior, and physical activity) often occur in sustained bouts that are punctuated with brief interruptions. To detect and classify these interrupted bouts, researchers commonly use wearable devices and specialized algorithms. Most algorithms examine the data in chronological order, initiating and terminating bouts whenever specific criteria are met. Consequently, the bouts may encapsulate or overlap with later periods that also meet the activation and termination criteria (i.e., alternative bout solutions). In some cases, it is desirable to compare these alternative bout solutions before making a final classification. Thus, comparison-focused algorithms are needed, which can be used in isolation or in concert with their chronology-focused counterparts. In this technical note, we present a comparison-focused algorithm called CRIB (Clustered Recognition of Interrupted Bouts). It uses agglomerative hierarchical clustering to facilitate the comparison of different bout solutions, with the final classification being made in favor of the smallest number of bouts that comply with user-specified criteria (i.e., limits on the number, individual duration, and cumulative duration of interruptions). For demonstration, we use CRIB to assess bouts of moderate to vigorous physical activity in accelerometer data from the National Health and Nutrition Examination Survey, and we include a comparison against results from two established chronology-focused algorithms. Our discussion explores strengths and limitations of CRIB, as well as potential considerations and applications for using it in future studies. An online vignette (https://github.com/paulhibbing/PBpatterns/blob/main/vignettes/CRIB.pdf) is available to assist users with implementing CRIB in R.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86297302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Use of Accelerometers in Young Children: A Methodological Scoping Review 加速计在幼儿中的使用:一项方法学范围审查

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0049

Becky Breau, Hannah J. Coyle-Asbil, L. Vallis

{"title":"The Use of Accelerometers in Young Children: A Methodological Scoping Review","authors":"Becky Breau, Hannah J. Coyle-Asbil, L. Vallis","doi":"10.1123/jmpb.2021-0049","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0049","url":null,"abstract":"The purpose of this scoping review was to examine publications using accelerometers in children aged 6 months to <6 years and report on current methodologies used for data collection and analyses. We examined device make and model, device placement, sampling frequency, data collection protocol, definition of nonwear time, inclusion criteria, epoch duration, and cut points. Five online databases and three gray literature databases were searched. Studies were included if they were published in English between January 2009 and March 2021. A total of 627 articles were included for descriptive analyses. Of the reviewed articles, 75% used ActiGraph devices. The most common device placement was hip or waist. More than 80% of articles did not report a sampling frequency, and 7-day protocols during only waking hours were the most frequently reported. Fifteen-second epoch durations and the cut points developed by Pate et al. in 2006 were the most common. A total of 203 articles did not report which definition of nonwear time was used; when reported, “20 minutes of consecutive zeros” was the most frequently used. Finally, the most common inclusion criteria were “greater or equal to 10 hr/day for at least 3 days” for studies conducted in free-living environments and “greater than 50% of the school day” for studies conducted in preschool or childcare environments. Results demonstrated a major lack of reporting of methods used to analyze accelerometer data from young children. A list of recommended reporting practices was developed to encourage increased reporting of key methodological details for research in this area.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91004756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Erratum. The 7th International Conference on Ambulatory Monitoring of Physical Activity and Movement 勘误表。第七届身体活动和运动动态监测国际会议

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0040

引用次数: 0

Comparison of activPAL and Actiwatch for Estimations of Time in Bed in Free-Living Adults activPAL和Actiwatch在自由生活成人床上时间估计中的比较

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0047

Mary C. Hidde, K. Lyden, J. Broussard, Kim Henry, Julia Sharp, Elizabeth A Thomas, C. Rynders, H. Leach

{"title":"Comparison of activPAL and Actiwatch for Estimations of Time in Bed in Free-Living Adults","authors":"Mary C. Hidde, K. Lyden, J. Broussard, Kim Henry, Julia Sharp, Elizabeth A Thomas, C. Rynders, H. Leach","doi":"10.1123/jmpb.2021-0047","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0047","url":null,"abstract":"Introduction: Patterns of physical activity (PA) and time in bed (TIB) across the 24-hr cycle have important implications for many health outcomes; therefore, wearable accelerometers are often implemented in behavioral research to measure free-living PA and TIB. Two accelerometers, the activPAL and Actiwatch, are common accelerometers for measuring PA (activPAL) and TIB (Actiwatch), respectively. Both accelerometers have the capacity to measure TIB, but the degree to which these accelerometers agree is not clear. Therefore, this study compared estimates of TIB between activPAL and the Actiwatch accelerometers. Methods: Participants (mean ± SDage = 39.8 ± 7.6 years) with overweight or obesity (N = 83) wore an activPAL and Actiwatch continuously for 7 days, 24 hr per day. TIB was assessed using manufacturer-specific algorithms. Repeated-measures mixed-effect models and Bland–Altman plots were used to compare the activPAL and Actiwatch TIB estimates. Results: Statistical differences between TIB assessed by activPAL versus Actiwatch (p < .001) were observed. There was not a significant interaction between accelerometer and day of wear (p = .87). The difference in TIB between accelerometers ranged from −72.9 ± 15.7 min (Day 7) to −98.6 ± 14.5 min (Day 3), with the Actiwatch consistently estimating longer TIB compared with the activPAL. Conclusion: Data generated by the activPAL and Actiwatch accelerometers resulted in divergent estimates of TIB. Future studies should continue to explore the validity of activity monitoring accelerometers for estimating TIB.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77647077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Comparison of Wrist- Versus Hip-Worn ActiGraph Sensors for Assessing Physical Activity in Adults: A Systematic Review 用于评估成人身体活动的腕部与髋部穿戴式活动传感器的比较:一项系统综述

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0045

Nolan Gall, R. Sun, M. Smuck

{"title":"A Comparison of Wrist- Versus Hip-Worn ActiGraph Sensors for Assessing Physical Activity in Adults: A Systematic Review","authors":"Nolan Gall, R. Sun, M. Smuck","doi":"10.1123/jmpb.2021-0045","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0045","url":null,"abstract":"Introduction: Wrist-worn accelerometer has gained popularity recently in commercial and research use for physical activity tracking. Yet, no consensus exists for standardized wrist-worn data processing, and physical activity data derived from wrist-worn accelerometer cannot be directly compared with data derived from the historically used hip-worn accelerometer. In this work, through a systematic review, we aim to identify and analyze discrepancies between wrist-worn versus hip-worn ActiGraph accelerometers in measuring adult physical activity. Methods: A systematic review was conducted on studies involving free-living data comparison between hip- and wrist-worn ActiGraph accelerometers among adult users. We assessed the population, study protocols, data processing criteria (axis, epoch, wear-time correction, etc.), and outcome measures (step count, sedentary activity time, moderate-to-vigorous physical activity, etc.). Step count and activity count discrepancy were analyzed using meta-analysis, while meta-analysis was not attempted for others due to heterogeneous data processing criteria among the studies. Results: We screened 235 studies with 19 studies qualifying for inclusion in the systematic review. Through meta-analysis, the wrist-worn sensor recorded, on average, 3,537 steps/day more than the hip-worn sensor. Regarding sedentary activity time and moderate-to-vigorous physical activity estimation, the wrist sensor consistently overestimates moderate-to-vigorous physical activity time while underestimating sedentary activity time, with discrepancies ranging from a dozen minutes to several hours. Discussions: Our findings quantified the substantial discrepancies between wrist and hip sensors. It calls attention to the need for a cautious approach to interpreting data from different wear locations. These results may also serve as a reference for data comparisons among studies using different sensor locations.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"120 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85762596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Validity of the Garmin Vivofit Jr. to Measure Physical Activity During a Youth After-School Program Garmin Vivofit测量青少年课外活动的有效性

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0039

K. Peyer, Kara C. Hamilton

{"title":"Validity of the Garmin Vivofit Jr. to Measure Physical Activity During a Youth After-School Program","authors":"K. Peyer, Kara C. Hamilton","doi":"10.1123/jmpb.2021-0039","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0039","url":null,"abstract":"Purpose: The purpose of this study was to evaluate the validity of the step count and Active Minutes features of the Garmin Vivofit Jr. 2 consumer activity monitor. Methods: Participants included 35 students (age 8–11) enrolled in an after-school physical activity (PA) and nutrition program. Participants wore an ActiGraph GT3x+ monitor on their waist and the Vivofit monitor on their wrist during the PA portion of the program. Data were collected across multiple sessions, resulting in 158 unique pairs of data. Pearson correlation, mean absolute percent error, and equivalence testing were performed to compare step count and minutes of activity (Vivofit Active Minutes vs ActiGraph moderate to vigorous PA) between the two monitors. Results: Moderate correlations were found between the monitors for steps (r = .65) and minutes (r = .43). Mean absolute percent error was 26% for steps and 43% for minutes, suggesting that there were high amounts of individual error. Equivalence testing showed significant agreement between the monitors for steps (p = .046), but not for minutes (p = .98). Conclusion: The Garmin Vivofit Jr. 2 shows acceptable validity for measurement of steps at a group level in a field-based setting, although the amount of individual variability must be considered. The Vivofit Jr. 2 was not valid for measurement of minutes of activity.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76085090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of Child and Adolescent Physical Activity Levels From Open-Source Versus ActiGraph Counts 儿童和青少年体力活动水平的比较，从开源与活动图计数

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0057

Kimberly A. Clevenger, K. Mackintosh, M. McNarry, K. Pfeiffer, Alexander Montoye, J. Brønd

{"title":"Comparison of Child and Adolescent Physical Activity Levels From Open-Source Versus ActiGraph Counts","authors":"Kimberly A. Clevenger, K. Mackintosh, M. McNarry, K. Pfeiffer, Alexander Montoye, J. Brønd","doi":"10.1123/jmpb.2021-0057","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0057","url":null,"abstract":"ActiGraph counts are commonly used for characterizing physical activity intensity and energy expenditure and are among the most well-studied accelerometer metrics. Researchers have recently replicated the counts processing method using a mechanical setup, now allowing users to generate counts from raw acceleration data. Purpose: The purpose of this study was to compare ActiGraph-generated counts to open-source counts and assess the impact on free-living physical activity levels derived from cut points, machine learning, and two-regression models. Methods: Children (n = 488, 13.0 ± 1.1 years of age) wore an ActiGraph wGT3X-BT on their right hip for 7 days during waking hours. ActiGraph counts and counts generated from raw acceleration data were compared at the epoch-level and as overall means. Seven methods were used to classify overall and epoch-level activity intensity. Outcomes were compared using weighted kappa, correlations, mean absolute deviation, and two one-sided equivalence testing. Results: All outcomes were statistically equivalent between ActiGraph and open-source counts; weighted kappa was ≥.971 and epoch-level correlations were ≥.992, indicating very high agreement. Bland–Altman plots indicated differences increased with activity intensity, but overall differences between ActiGraph and open-source counts were minimal (e.g., epoch-level mean absolute difference of 23.9 vector magnitude counts per minute). Regardless of classification model, average differences translated to 1.4–2.6 min/day for moderate- to vigorous-intensity physical activity. Conclusion: Open-source counts may be used to enhance comparability of future studies, streamline data analysis, and enable researchers to use existing developed models with alternative accelerometer brands. Future studies should verify the performance of open-source counts for other outcomes, like sleep.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90801584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Calibrating the Physical Activity Vital Sign to Estimate Habitual Moderate to Vigorous Physical Activity More Accurately in Active Young Adults: A Cautionary Tale 校准体力活动生命体征以更准确地估计活跃的年轻人的习惯性中度到剧烈体力活动:一个警世故事

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0055

Liam P. Pellerine, D. Kimmerly, J. Fowles, M. O'Brien

{"title":"Calibrating the Physical Activity Vital Sign to Estimate Habitual Moderate to Vigorous Physical Activity More Accurately in Active Young Adults: A Cautionary Tale","authors":"Liam P. Pellerine, D. Kimmerly, J. Fowles, M. O'Brien","doi":"10.1123/jmpb.2021-0055","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0055","url":null,"abstract":"The Physical Activity Vital Sign (PAVS) is a two-question assessment used to estimate habitual moderate to vigorous aerobic physical activity (MVPA). Previous studies have shown active adults cannot estimate the physical activity intensity properly. The initial purpose was to investigate the criterion validity of the PAVS for quantifying habitual MVPA in young adults meeting weekly MVPA guidelines (n = 140; 21 ± 3 years). A previously validated PiezoRx waist-worn accelerometer served as the criterion measure (wear time, 6.7 ± 0.6 days). All participants completed the PAVS once before wearing the PiezoRx. Standardized activity monitor validation procedures were followed. The PAVS (201 ± 142 min/week) underestimated (p < .001) MVPA compared to the PiezoRx (381 ± 155 min/week). To correct for this large error, the sample was divided into calibration model development (n = 70; 21 ± 3 years) and criterion validation (n = 70; 21 ± 3 years) groups. The PAVS score, age, gender, and body mass index outcomes from the development group were used to construct a multiple linear regression model-based calibrated PAVS (cPAVS) equation. In the validation group, the cPAVS was similar (p = .113; 352 ± 23 min/week) compared to accelerometry. Equivalence testing demonstrated the cPAVS, but not the PAVS, was equivalent to the PiezoRx. Despite achieving most statistical criteria, the PAVS and cPAVS still had high degrees of variability, preventing their use on an individual level. Alternative strategies are needed for the PAVS in an active young adult population. These results caution using the PAVS in active young adults and identify a case where obvious variabilities in accuracy conflict with statistically congruent results.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86307171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Measurement of Physical Activity Using Accelerometry in Persons With Multiple Sclerosis 用加速度计测量多发性硬化症患者的体力活动

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0029

R. Motl

引用次数: 1