StopWatch: A smartwatch based system for passive detection of cigarette smoking

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Description: Introduction: Passive detection of cigarette smoking offers potential for considerable benefits to researchers exploring smoking behaviour and designing precision behaviour change interventions. A number of systems have been developed that either use bespoke sensing technology, or rely on connected smartphones to run analytical software. Here we present StopWatch, a system for passive detection of cigarette smoking that runs on a smartwatch and does not require additional sensing or a connected smartphone. Methods: Our system uses motion data from the accelerometer and gyroscope in an Android smartwatch to detect the signature hand movements of cigarette smoking. It uses a three-stage analytical pipeline to transform raw motion data into motion features, and in turn into individual drags and instances of smoking. This pipeline runs on the smartwatch, and does not require a smartphone. Results: We validated the system in daily smokers (n=13) in laboratory and free-living conditions running on an Android LG G-Watch. In free-living conditions, over a 24 hour period, the system achieved precision of 86% and recall of 71%. Conclusions: StopWatch is a system for passive measurement of cigarette smoking that runs entirely on a commercially available smartwatch. It runs on an Android smartwatch and requires no smartphone so the cost is low. No bespoke sensing equipment is needed, and it uses a mass-market smartwatch, so participant burden is low. Performance is currently lower than other more expensive and complex systems, though adequate for some applications. Future developments will focus on enhancing performance, and validation on a range of smartwatches.

License: CC0 1.0 Universal

This project represents an accepted preprint submitted to PsyArXiv . Learn more about how to work with preprint files. View preprint


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