RESEARCH ARTICLE


Detection of Hand-to-Mouth Gestures Using a RF Operated Proximity Sensor for Monitoring Cigarette Smoking



Paulo Lopez-Meyer 1, Yogendra Patil 1, Tiffany Tiffany 2, Edward Sazonov 1, *
1 The University of Alabama, Department of Electrical and Computer Engineering, Tuscaloosa, AL, 35487, USA
2 State University of New York at Buffalo, Psychology Department, Buffalo, NY, 14260, USA


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Creative Commons License
© Lopez-Meyer et al.; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the Department of Electrical and Computer Engineering, University of Alabama, 101 Houser Hall, Tusca-loosa, AL 35487-0286, USA; Tel: (205) 348-1981; Fax: (205) 348-6959; E-mail: esazonov@eng.ua.edu


Abstract

Common methods for monitoring of cigarette smoking, such as portable puff-topography instruments or self-report questionnaires, tend to be biased due to conscious or unconscious underreporting. Additionally, these methods may change the natural smoking behavior of individuals. Our long term objective is the development of a wearable non-invasive monitoring system (Personal Automatic Cigarette Tracker – PACT) to reliably monitor cigarette smoking behavior under free living conditions. PACT monitors smoking by observing characteristic breathing patterns of smoke inhalations that follow a cigarette-to-mouth hand gesture. As envisioned, PACT does not rely on self-report or require any conscious effort from the user. A major element of the PACT is a proximity sensor that detects typical cigarette-to-mouth gesture during cigarette smoking. This study describes the design and validation of a prototype RF proximity sensor that captures hand-to-mouth gestures with a high sensitivity (0.90), and a methodology that can reject up to 68% of artifacts gestures originating from activities other than cigarette smoking.

Keywords: Hand-to-mouth gestures, cigarette smoking, puff topography, wearable sensors, proximity sensor, radio frequency sensors..