@article{Ma2025, 
author = {Jiao Ma and Tian-Zhang Xing and Wei Xi and Kun Zhao and Jun Tan and Xiao-Jiang Chen},
title = {HeartIt: Low-Power Smoking Detection with a Smartwatch on Either Wrist},
year = {2025},
journal = {Journal of Computer Science and Technology},
volume = {40},
number = {2},
pages = {552-571},
keywords = {mobile computing, smartwatch, smoking detection, heart rate sensor},
url = {https://www.sciopen.com/article/10.1007/s11390-024-2981-3},
doi = {10.1007/s11390-024-2981-3},
abstract = {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.}
}