Accelerating the development of novel methods to measure 24-hr physical behavior

项目摘要/摘要 使用设备对人类行为的准确测量可以极大地促进当前关于 慢性病与体力活动、久坐行为的剂量-反应关系 行为和睡眠。这项提议的主要目标是开发有效的方法来测量24小时 身体行为，以及演示一个程序，通过它可以与这些方法进行比较 其他。我们的目标是帮助研究团体在使用设备准确地 测量成年人的身体活动类型和强度、久坐的行为和姿势以及睡眠。许多 已经提出了一些很有前途的方法来测量活动监测器的行为。不幸的是，这些 现在正在大量提出的方法通常是在少量数据上进行验证的。 因此，它们在实验室数据上可能表现良好，但在现场用于大规模流行病学或 干预研究。此外，不同方法的性能很少进行正面比较， 这给公共卫生研究人员带来了不确定性，不知道哪种药物是最好的。量化相对关系 产生相似结果测量但使用不同装置或体内装置的方法的性能 地点更是不同寻常。我们将使对体育锻炼感兴趣的研究人员更容易 测量以有意义地比较新方法之间的性能，并自信地应用 方法采用大规模监测研究和纵向干预相结合的方法。该项目有四个具体的 目标：(1)收集经过良好注释的体力活动、久坐行为和睡眠数据，(2)使用来自 目标1开发和验证产生24小时自由生活体力活动(类型、 强度)、久坐行为(类型、姿势)和睡眠(觉醒/睡眠、阶段)，(3)发展和递增 完善一套工具，研究人员可以使用这些工具轻松部署高级方法来测量物理 活动、久坐行为和睡眠，即使是大数据，以及(4)使用数据和新方法(目标1 以及3)主办四个竞赛评估模型，其中其他研究人员提交的所有参赛作品将被 直接比较、排名和改进。其目标是帮助研究人员在“黄金标准”方法上趋同。 使用常见的监视器配置以及这些设备和 可能很快就会使用的配置。

Project Summary/Abstract Accurate measurement of human behavior using devices could significantly advance current knowledge on the dose-response relationships between chronic diseases and behaviors such as physical activity, sedentary behavior, and sleep. The primary objective of this proposal is to develop valid approaches to measure 24-hour physical behavior, as well as to demonstrate a procedure via which those approaches can be compared to others. We aim to help the research community to converge on methods that use devices to accurately measure physical activity type and intensity, sedentary behavior and posture, and sleep in adults. Many promising methods have been proposed to measure behavior from activity monitors. Unfortunately, these methods – which are now being proposed in large numbers – are typically validated on small amounts of data. Thus, they may perform well on lab data, but fail when used in the field on large-scale epidemiological or intervention studies. Moreover, the performance of different methods is rarely compared head-to-head, creating uncertainty for public health researchers about which are the best to use. Quantifying the relative performance of methods that produce similar outcome measures but use different devices or on-body device locations is even more unusual. We will make it easy for researchers interested in physical activity measurement to meaningfully compare performance between new methods and confidently apply those methods to both large-scale surveillance studies and longitudinal interventions. The project has four specific aims: (1) Collect well-annotated data of physical activity, sedentary behavior, and sleep, (2) Use the data from Aim 1 to develop and validate approaches that yield 24-hour estimates of free-living physical activity (type, intensity), sedentary behavior (type, posture), and sleep (wake/sleep, stages), (3) Develop and incrementally refine a suite of tools that researchers can use to easily deploy advanced approaches to measure physical activity, sedentary behavior, and sleep, even for large data, and (4) Use the data and new approaches (Aims 1 and 3) to host four competitions evaluating models, where all entries submitted by other researchers, will be directly compared, ranked, and improved. The goal is to help researchers converge on “gold standard” methods to robustly measure physical activity using common monitor configurations, as well as those devices and configurations likely to be used soon.