Quantification of acceleration as activity counts in ActiGraph wearable.
Quantification of acceleration as activity counts in ActiGraph wearable.
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DOI：
10.1038/s41598-022-16003-x
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发表时间：
2022-07-13
影响因子：
4.6
通讯作者：
Guo, Christine C.
中科院分区：
文献类型：
--
作者：
Neishabouri, Ali;Nguyen, Joe;Samuelsson, John;Guthrie, Tyler;Biggs, Matt;Wyatt, Jeremy;Cross, Doug;Karas, Marta;Migueles, Jairo H.;Khan, Sheraz;Guo, Christine C.
基于可穿戴设备收集的数据的数字临床测量在临床试验和医疗保健领域都有快速增长。基于可穿戴设备的广泛使用的测量是使用加速度计数据的基于时期的身体活动计数。尽管活动计数已经成为数千项临床和流行病学研究的支柱，但计算计数及其相关参数的算法存在很大的变化，其中许多算法通常由设备提供商专有。这种透明度的缺乏阻碍了使用不同器械的研究之间的可比性，并限制了其更广泛的临床适用性。二十多年来，ActiGraph设备一直是最常用的可穿戴加速度计设备。认识到数据透明性、可解释性和互操作性对研究和临床使用的重要性，我们在此描述了可追溯到第一个AM7164型号的五代ActiGraph设备的详细计数算法，并将ActiGraph的ActiLife和CentrePoint软件中的当前计数算法作为独立的Python包发布，供研究使用。我们相信，这种材料将为研究界提供有用的资源，加速数字健康科学的发展，并促进可穿戴加速度计的临床应用。
Digital clinical measures based on data collected by wearable devices have seen rapid growth in both clinical trials and healthcare. The widely-used measures based on wearables are epoch-based physical activity counts using accelerometer data. Even though activity counts have been the backbone of thousands of clinical and epidemiological studies, there are large variations of the algorithms that compute counts and their associated parameters—many of which have often been kept proprietary by device providers. This lack of transparency has hindered comparability between studies using different devices and limited their broader clinical applicability. ActiGraph devices have been the most-used wearable accelerometer devices for over two decades. Recognizing the importance of data transparency, interpretability and interoperability to both research and clinical use, we here describe the detailed counts algorithms of five generations of ActiGraph devices going back to the first AM7164 model, and publish the current counts algorithm in ActiGraph’s ActiLife and CentrePoint software as a standalone Python package for research use. We believe that this material will provide a useful resource for the research community, accelerate digital health science and facilitate clinical applications of wearable accelerometry.
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影响因子：
9.6
作者：
Nathan, Steven D.;Flaherty, Kevin. R.;Lancaster, Lisa
通讯作者：
Lancaster, Lisa
DOI：
10.1186/2052-1847-6-26
发表时间：
2014
期刊：
BMC sports science, medicine & rehabilitation
影响因子：
--
作者：
Grydeland M;Hansen BH;Ried-Larsen M;Kolle E;Anderssen SA
通讯作者：
Anderssen SA
DOI：
10.1249/mss.0b013e3182351913
发表时间：
2012-04-01
期刊：
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
影响因子：
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作者：
Feito, Yuri;Bassett, David R.;Thompson, Dixie L.
通讯作者：
Thompson, Dixie L.
影响因子：
4
作者：
Paul, David R.;Kramer, Matthew;Rumpler, William V.
通讯作者：
Rumpler, William V.
DOI：
10.3758/bf03200979
发表时间：
1985-12-01
期刊：
BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS
影响因子：
--
作者：
REDMOND, DP;HEGGE, FW
通讯作者：
HEGGE, FW