Validating the CalFit Smartphone Sensor in Two Epidemiological Investigations

在两项流行病学调查中验证 CalFit 智能手机传感器

• 批准号: 8332310
• 负责人: Michael LeoBrennan Jerrett
• 金额: $ 40.48万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8332310
• 关键词: Address; Affect; Air Pollution; Area; Behavior; Bicycling; Breathing; California; Cellular Phone; Cities; Collection; Communities; Commuting; Complex; Data; Devices; Dose; Ecosystem; Enrollment; Environment; Environmental Epidemiology; Environmental Exposure; Epidemiologic Studies; Epidemiology; Europe; European; Evaluation; Exercise; Exposure to; Funding; Geographic Locations; Glosso-Sterandryl; Gold; Government; Growth; Health; Home environment; Individual; Information Systems; Investigation; Location; Measurement; Measures; Metabolic; Modeling; Monitor; Moods; Nitrogen Dioxide; Obesity; Ozone; Participant; Patient Self-Report; Pattern; Performance; Physical activity; Pollution; Population; Population Heterogeneity; Population Study; Positioning Attribute; Public Health; Reaction; Research; Research Design; Research Personnel; Running; Sampling; Services; Site; Source; Spain; Study Section; Study Subject; Surveys; System; Technology; Telephone; Testing; Text; Time; Transportation; Travel; United States; Validation; Walking; base; body sense; diaries; instrument; land use; novel; obesity risk; pollutant; self reported behavior; sensor; social; suburb; tool; trafficking; usability; validation studies

DESCRIPTION (provided by applicant): PROJECT SUMMARY/ABSTRACT We propose to assess the validity, usability, and value of a novel cell phone-based personal exposure measurement system known as "CalFit" in two existing epidemiologic studies. The CalFit system runs on commercially available Android phones, and as currently configured, we can collect data on physical activity with accelerometry, geographic location through a global positioning system (GPS), air pollution, and self- reported environments, including mood, and behaviors with ecological momentary assessment (EMA) through interactive text messages. The CalFit system has already undergone numerous controlled validation studies and is ready for evaluation in large epidemiological studies. The combined measurement of physical activity, location and mobility, exposure to air pollution, and EMA represents a major advance in sensor technology. We will evaluate the instrument in two ongoing epidemiological investigations: (1) the Healthy PLACES study in Southern California, which is examining the impact of the built environment on physical activity and obesity in a Smart Growth community and five adjacent communities; and (2) in the Transportation, Air Pollution and physical ActivitieS (TAPAS) project in Barcelona, Spain, focused on determinants of active commuting by bicycling or walking. Both studies have enrolled subjects and are actively collecting accelerometry, GPS, or travel survey data. For Aim 1, we will validate the CalFit GPS and accelerometer by comparing the integrated sensor against current gold standard instruments (the Actigraph accelerometer and the Globalsat GPS). In Aim 2, we will demonstrate the added value of the EMA texting system for understanding self-reported behavior, mood, and social and physical contexts as antecedents, concomitants, and consequences of environmental exposures. For Aim 3, we will combine commercially available sensors with circuit boards developed by our team to measure nitrogen dioxide and ozone in the field. We will merge these data with GPS and accelerometry information to infer likely inhalations of air pollution. To demonstrate value added we will compare the inhalation estimates derived against those from assigning resolved spatial estimates of exposure to the home location. We will also deploy passive sensors for the two pollutants that yield an integrated 1-week sample. These will be compared with the real-time assessments to demonstrate the value added of having the locational and physical activity information merged with the real-time air pollution data, which will allow us to assess indoor and outdoor exposures, the likely inhalation, and the geographic context of the exposures. Cell phones are currently the most ubiquitous computing platform globally, and our research will demonstrate the viability of a cell phone as an exposure characterization tool that will have widespread utility for numerous epidemiological applications.

描述（由申请人提供）：项目摘要/摘要我们建议在两项现有的流行病学研究中评估一种基于手机的新型个人暴露测量系统（称为“CalFit”）的有效性、可用性和价值。 CalFit 系统在商用 Android 手机上运行，​​根据当前配置，我们可以通过加速度测量收集身体活动数据、通过全球定位系统 (GPS) 收集地理位置、空气污染和自我报告的环境数据，包括情绪和通过交互式短信通过生态瞬时评估 (EMA) 的行为。 CalFit 系统已经进行了大量的受控验证研究，并准备在大型流行病学研究中进行评估。对身体活动、位置和移动性、空气污染暴露以及 EMA 的综合测量代表了传感器技术的重大进步。 我们将在两项正在进行的流行病学调查中评估该工具：（1）南加州的 Healthy PLACES 研究，该研究正在研究智能增长社区和五个邻近社区的建筑环境对身体活动和肥胖的影响； (2) 西班牙巴塞罗那的交通、空气污染和体力活动 (TAPAS) 项目，重点关注骑自行车或步行积极通勤的决定因素。这两项研究均已招募受试者，并正在积极收集加速测量、GPS 或旅行调查数据。 对于目标 1，我们将通过将集成传感器与当前的黄金标准仪器（Actigraph 加速计和 Globalsat GPS）进行比较来验证 CalFit GPS 和加速计。在目标 2 中，我们将展示 EMA 短信系统的附加价值，用于理解自我报告的行为、情绪以及社会和身体环境作为环境暴露的前因、伴随物和后果。对于目标 3，我们将把商用传感器与我们团队开发的电路板结合起来，在现场测量二氧化氮和臭氧。我们将这些数据与 GPS 和加速测量信息合并，以推断可能吸入空气污染的情况。为了证明附加值，我们将比较吸入估计值与通过分配暴露于家庭位置的解析空间估计值得出的吸入估计值。我们还将针对这两种污染物部署无源传感器，生成为期 1 周的综合样本。这些将与实时评估进行比较，以证明将位置和身体活动信息与实时空气污染数据合并的附加值，这将使我们能够评估室内和室外暴露、可能的吸入以及暴露的地理背景。 手机是目前全球最普遍的计算平台，我们的研究将证明手机作为暴露特征分析工具的可行性，该工具将在众多流行病学应用中具有广泛的用途。