Smoking cessation is a significant challenge for many people addicted to cigarettes and tobacco. Mobile health-related research into smoking cessation is primarily focused on mobile phone data collection either using self-reporting or sensor monitoring techniques. In the past five years with the increased popularity of smartwatch devices, research has been conducted to predict smoking movements associated with smoking behaviors based on accelerometer data analyzed from the internal sensors in a user’s smartwatch. Previous smoking detection methods focused on classifying current user smoking behavior. For many users who are trying to quit smoking, this form of detection may be insufficient as the user has already relapsed. In this article, we present a smoking cessation system utilizing a smartwatch and finger sensor that is capable of detecting presmoking activities to discourage users from future smoking behavior. Presmoking activities include grabbing a pack of cigarettes or lighting a cigarette and these activities are often immediately succeeded by smoking. Therefore, through accurate detection of presmoking activities, we can alert the user before they have relapsed. Our smoking cessation system combines data from a smartwatch for gross accelerometer and gyroscope information and a wearable finger sensor for detailed finger bend-angle information. We compare the results of a smartwatch-only system with a combined smartwatch and finger sensor system to illustrate the accuracy of each system. The combined smartwatch and finger sensor system performed at an 80.6% accuracy for the classification of presmoking activities compared to 47.0% accuracy of the smartwatch-only system.

中文翻译：

---

DORA：一种用于能量平衡无线传感器网络的面向目的地的路由算法


对于许多香烟和烟草成瘾者来说，戒烟是一项重大挑战。与戒烟有关的移动健康相关研究主要集中于使用自我报告或传感器监测技术收集手机数据。在过去的五年里，随着智能手表设备的日益普及，人们进行了研究，根据从用户智能手表的内部传感器分析的加速度计数据来预测与吸烟行为相关的吸烟动作。以前的吸烟检测方法侧重于对当前用户吸烟行为进行分类。对于许多试图戒烟的用户来说，这种形式的检测可能是不够的，因为用户已经复吸了。在本文中，我们介绍了一种利用智能手表和手指传感器的戒烟系统，该系统能够检测吸烟前的活动，以阻止用户未来的吸烟行为。吸烟前的活动包括抓起一包香烟或点燃一支香烟，这些活动通常会立即被吸烟所取代。因此，通过准确检测吸烟前活动，我们可以在用户复吸之前发出警报。我们的戒烟系统结合了智能手表的总加速度计和陀螺仪信息的数据以及可穿戴手指传感器的详细手指弯曲角度信息。我们将仅智能手表系统与智能手表和手指传感器组合系统的结果进行比较，以说明每个系统的准确性。智能手表和手指传感器组合系统对吸烟前活动的分类准确度为 80.6%，而仅智能手表系统的准确度为 47.0%。