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: 8179576
• 负责人: Michael LeoBrennan Jerrett
• 金额: $ 44.19万
• 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 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8179576
• 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. PUBLIC HEALTH RELEVANCE: PROJECT NARRATIVE Currently collection of individualized exposure data is intrusive to study participants and expensive, largely due to the need to wear multiple devices. Our research will integrate numerous data related to individual behaviors and environmental exposures using a cell phone. Because cell phones are already used extensively, our sensor offers substantial advantages for large epidemiological studies. Thus our research is highly relevant to the protection of public health because the new sensors will allow researchers to unobtrusively measure many environmental exposures in a way that is convenient to study subjects and relatively inexpensive to researchers.

描述(由申请人提供)：项目摘要/摘要我们建议在现有的两项流行病学研究中评估一种新的基于手机的个人暴露测量系统“CalFit”的有效性、可用性和价值。CalFit系统运行在市售的Android手机上，按照目前的配置，我们可以通过加速度计收集身体活动数据，通过全球定位系统(GPS)收集地理位置数据，通过互动短信收集空气污染和自我报告环境(包括情绪)的数据，以及通过生态瞬时评估(EMA)收集行为的数据。CalFit系统已经经历了许多对照验证研究，并准备在大型流行病学研究中进行评估。对体力活动、位置和机动性、暴露于空气污染和EMA的综合测量代表着传感器技术的重大进步。我们将在两个正在进行的流行病学调查中对该工具进行评估：(1)南加州的Healthy Places研究，该研究正在Smart Growth社区和邻近的五个社区中研究建筑环境对身体活动和肥胖的影响；(2)在西班牙巴塞罗那的交通、空气污染和身体活动(TAPAS)项目中，重点研究骑自行车或步行积极通勤的决定因素。这两项研究都招募了受试者，并正在积极收集加速度计、GPS或旅行调查数据。对于目标1，我们将通过将集成的传感器与当前的黄金标准仪器(Actigraph加速度计和Globalsat GPS)进行比较来验证CalFit GPS和加速度计。在目标2中，我们将展示EMA短信系统在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、伴随和后果方面的附加价值。对于目标3，我们将结合商业上可用的传感器和我们团队开发的电路板来测量现场的二氧化氮和臭氧。我们将把这些数据与GPS和加速度计信息合并，以推断可能的空气污染吸入。为了证明增加的价值，我们将把吸入量估计值与分配家庭场所暴露的已解决空间估计值的估计值进行比较。我们还将为这两种污染物部署被动传感器，以产生一个完整的1周样本。这些将与实时评估进行比较，以展示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。手机目前是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描述工具的可行性，这将在许多流行病学应用中具有广泛的实用价值。 公共卫生相关性：项目叙述目前收集的个性化暴露数据对研究参与者来说是侵入性的，而且成本高昂，主要是因为需要佩戴多种设备。我们的研究将整合与使用手机的个人行为和环境暴露相关的大量数据。由于手机已经被广泛使用，我们的传感器为大规模流行病学研究提供了实质性的优势。因此，我们的研究与保护公众健康高度相关，因为新的传感器将允许研究人员以一种便于研究对象和研究人员相对便宜的方式，不引人注意地测量许多环境暴露。