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<p>To assist with smoking cessation, wearable devices are used to detect the puff (hand-to-mouth gesture) recognition within the smoking activity in a ubiquitous manner. There is a strong assumption that smoking and wearing a smartwatch are usually with the same hand. It will certainly fail to detect smoking gesture with the opposite hand. In this work, we find an interesting phenomenon: smoking can cause a unique pattern of heart rate (HR) which is quite different from other daily activities’ effects. Based on this psychophysiological response, we propose HeartIt, a just-in-time smoking detection solution through measuring the HR by a smartwatch. HeartIt works well for the smoker wearing a smartwatch on either wrist. It can accurately distinguish smoking from other similar hand-to-mouth gestures (e.g., eating, drinking). Moreover, we design an adaptive tracker to trigger the HR sensor once the gesture of lighting a cigarette is detected by low-cost accelerometers. It is robust for different people in various postures and scenarios. Our real-world experiments show that the precision and recall rate of HeartIt reaches 96.7% and 99.8%, respectively.</p>

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HeartIt: Low-Power Smoking Detection with a Smartwatch on Either Wrist

  • 期刊论文

  • 发表日期：

    2025年3月1日

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  • Jiao Ma,
  • Tian-Zhang Xing,
  • Wei Xi,
  • Kun Zhao,
  • Jun Tan,
  • Xiao-Jiang Chen

摘要

To assist with smoking cessation, wearable devices are used to detect the puff (hand-to-mouth gesture) recognition within the smoking activity in a ubiquitous manner. There is a strong assumption that smoking and wearing a smartwatch are usually with the same hand. It will certainly fail to detect smoking gesture with the opposite hand. In this work, we find an interesting phenomenon: smoking can cause a unique pattern of heart rate (HR) which is quite different from other daily activities’ effects. Based on this psychophysiological response, we propose HeartIt, a just-in-time smoking detection solution through measuring the HR by a smartwatch. HeartIt works well for the smoker wearing a smartwatch on either wrist. It can accurately distinguish smoking from other similar hand-to-mouth gestures (e.g., eating, drinking). Moreover, we design an adaptive tracker to trigger the HR sensor once the gesture of lighting a cigarette is detected by low-cost accelerometers. It is robust for different people in various postures and scenarios. Our real-world experiments show that the precision and recall rate of HeartIt reaches 96.7% and 99.8%, respectively.