Applied statistical methods for identifying features of heart rate that are associated with nicotine vaping
Published in The American Journal of Drug and Alcohol Abuse, 2025
📝 Abstract
This paper introduces a series of statistical methods to analyze heart rate data and identify features associated with nicotine vaping. Leveraging wearable sensor data collected during ecological momentary assessment (EMA) protocols, the study applies Kalman filtering, anomaly detection, and mixed-effects models to extract and evaluate physiological signatures of vaping events from continuous heart rate time series.
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📋 BibTeX Citation
@article{zhao2025vaping,
title = {Applied statistical methods for identifying features
of heart rate that are associated with nicotine vaping},
author = {Zhao, Puyang and Yang, James J. and Buu, Anne},
journal = {The American Journal of Drug and Alcohol Abuse},
year = {2025},
month = {feb},
doi = {10.1080/00952990.2024.2441868},
url = {https://doi.org/10.1080/00952990.2024.2441868},
publisher = {Taylor & Francis}
}🔗 Related Publications
Recommended citation: Zhao, P., Yang, J.J., & Buu, A. (2025). Applied statistical methods for identifying features of heart rate that are associated with nicotine vaping. The American Journal of Drug and Alcohol Abuse. https://doi.org/10.1080/00952990.2024.2441868
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