Validation of a System for Noninvasive Monitoring of Cigarette Smoking

无创吸烟监测系统的验证

基本信息

批准号：
9185296
负责人：
EDWARD S SAZONOV
金额：
$ 40.31万
依托单位：
UNIVERSITY OF ALABAMA IN TUSCALOOSA
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-02-01 至 2018-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9185296
关键词：
Address Affect Algorithms Behavior Behavioral Biological Markers Biomedical Engineering Breathing Carbon Monoxide Cellular Phone Cessation of life Characteristics Chest Cigarette Clothing Collection Computational algorithm Computer software Conscious Cotinine Country Data Detection Development Devices Economics Effectiveness Environment Event Feedback Frequencies Gender Generations Gestures Goals Grant Hand Health Individual Intervention Laboratories Lighting Location Measures Memory Methodology Methods Monitor Oral cavity Patient Self-Report Pattern Pattern Recognition Research Signal Transduction Smoke Smoker Smoking Smoking Behavior System Technology Testing Time United States Validation behavioral pharmacology cigarette smoking computerized data processing diaries improved instrument markov model new technology novel portability programs prototype public health relevance respiratory response sensor signal processing smoke inhalation smoking cessation smoking intervention trait

项目摘要

DESCRIPTION (provided by applicant): Cigarette smoking is the leading cause of preventable death in the United States. Smoking produces over 440,000 deaths each year in this country and generates an estimated $167 billion in annual health-related economic losses. Available methods of smoking assessment (e.g., self-report, portable puff-topography instruments) do not permit the collection of accurate, non-reactive measures of smoking behavior that capture real-time smoking frequency and comprehensive within-cigarette puff topography. The objective of this project is to complete development of a non-invasive wearable system (Personal Automatic Cigarette Tracker - PACT) that does not rely on any form of self-report and does not interfere with the natural smoking behavior of an individual, develop new capabilities for monitoring of smoke exposure, fully validate PACT in unconstrained settings, evaluate if PACT can detect whether the use of portable puff topography devices affect smoking behavior, compare the strength of correlation of metrics of smoke exposure measured by PACT and PTI with commonly used smoke-exposure biomarkers, and determine whether smoke exposure metrics collected in the natural environment are related to heaviness of smoking and smoking location. Methodologically, PACT relies on: 1. Wearable sensors for monitoring of breathing and hand-to-mouth gestures. Miniature sensors integrated into an elastic belt worn under regular clothing monitor the breathing and activity patterns of individuals. 2. Computer algorithms utilizing signal processing and pattern recognition methods for analysis of the sensor signals, detection of patterns uniquely identifying smoking events, and computation of smoke exposure metrics. The validation of the PACT system will be addressed in six Specific Aims: Aim 1. Perform pilot testing of the new generation of the PACT device and collect data for algorithm development. Aim 2. Improve computer algorithms to recognize individual smoke inhalations, develop algorithms for characterization of smoke exposure and investigate algorithms' accuracy as a function of users' anthropometric characteristics (gender, BMI, etc.). Aim 3. Validate PACT in unconstrained settings. Aim 4. Evaluate difference in smoking behavior metrics monitored by puff topography and PACT. Aim 5. Evaluate associations between common smoking biomarkers and smoke exposure metrics from PTI and PACT. Aim 6. Examine the extent to which smoking metrics derived from PACT are related to level of smoking and smoking location. This set of Specific Aims will build on the prototype developed in a previous R21 grant, bring the device and associated data processing methods to maturity, enable practical use of PACT in studies of smoking behavior, and facilitate novel applications allowing for real-time feedback to smokers.

描述（由申请人提供）：吸烟是美国可预防死亡的主要原因。在这个国家，吸烟每年导致超过 44 万人死亡，每年造成与健康相关的经济损失估计为 1,670 亿美元。现有的吸烟评估方法（例如，自我报告、便携式抽吸形貌仪器）不允许收集准确的、非反应性的吸烟行为测量数据，从而捕获实时吸烟频率和全面的香烟内抽吸形貌。该项目的目标是完成开发一种非侵入式可穿戴系统（个人自动香烟追踪器-PACT），该系统不依赖任何形式的自我报告，不干扰个人的自然吸烟行为，开发新的可穿戴系统。监测烟雾暴露的能力，在无约束的环境中充分验证 PACT，评估 PACT 是否可以检测便携式烟气地形测量设备的使用是否影响吸烟行为，将 PACT 和 PTI 测量的烟雾暴露指标与常用的烟雾暴露指标的相关性强度进行比较烟雾暴露生物标志物，并确定在自然环境中收集的烟雾暴露指标是否与吸烟的严重程度和吸烟地点有关。从方法上讲，PACT 依赖于： 1. 用于监测呼吸和手口手势的可穿戴传感器。集成到穿在普通衣服下的松紧带中的微型传感器可监测个人的呼吸和活动模式。 2. 利用信号的计算机算法用于分析传感器信号、检测唯一识别吸烟事件的模式以及计算烟雾暴露指标的处理和模式识别方法。 PACT 系统的验证将通过六个具体目标来解决：目标 1. 对新一代 PACT 设备进行试点测试并收集用于算法开发的数据。目标 2. 改进计算机算法以识别个人烟雾吸入情况，开发用于表征烟雾暴露的算法，并研究算法作为用户人体测量特征（性别、BMI 等）的函数的准确性。目标 3. 在不受约束的环境中验证 PACT。目标 4. 评估通过抽吸地形和 PACT 监测的吸烟行为指标的差异。目标 5. 评估常见吸烟生物标志物与 PTI 和 PACT 烟雾暴露指标之间的关联。目标 6. 检查 PACT 得出的吸烟指标与吸烟水平和吸烟地点的相关程度。这套具体目标将建立在之前 R21 拨款中开发的原型的基础上，使设备和相关的数据处理方法趋于成熟，使 PACT 在吸烟行为研究中得到实际应用，并促进新颖的应用程序，允许实时反馈吸烟者。