Feasibility of Using Wearable Technology for Just-in-Time Prediction of Smoking Lapses

拟议研究的长期目标是开发基于技术的干预措施， 通过提供及时的支持，以最大限度地减少吸烟触发导致吸烟的可能性， 到吸烟失误为了实现这一目标，我们建议使用连续的生理和环境时间- 从广泛使用的消费者可穿戴技术中嵌入的传感器获得的一系列数据， 用于检测吸烟事件的前因的预测模型（例如，压力源、吸烟线索等）。在这 项目，我们将进行一项观察性研究的吸烟者在自由吸烟期间和在 这是他们试图戒烟的时期。在观察期内，吸烟者将佩戴三种装置 能够收集生理和运动数据。我们假设消费者可穿戴技术可以 在随意吸烟期间可靠地捕获对吸烟前事件的生理反应 期间和终止期间之前失效。证明即将吸烟可能是 预测将导致开发和测试及时干预措施，可以通过 智能手机或智能手表等设备上的定制消息传递。

The long-term goal of the proposed line of research is to develop technology-based interventions that increase smoking cessation rates by delivering just-in-time support to minimize the likelihood that smoking triggers lead to smoking lapses. Towards this objective we propose to use continuous physiological and environmental time- series data obtained from sensors embedded in widely used consumer wearable technology to construct a predictive model for detecting antecedents of smoking events (e.g., stressors, smoking cues, etc). In this project, we will conduct an observational study of smokers during an ad libitum smoking period and during a period in which they attempt to quit smoking. During the observation period, smokers will wear three devices capable of collecting physiological and motion data. We hypothesize that consumer wearable technology can reliably capture physiological response to events that precede smoking during the ad libitum smoking period and precede lapse during the cessation period. Demonstrating that imminent smoking can be predicted would lead to the development and testing of just-in-time interventions that can be delivered via customized messaging on devices such as smartphones or smartwatches.