Quantification of Smoking Characteristics Using Smartwatch Technology: Pilot Feasibility Study of New Technology.
BACKGROUND
While there have been many technological advances in studying the neurobiological and clinical basis of tobacco use disorder and nicotine addiction, there have been relatively minor advances in technologies for monitoring, characterizing, and intervening to prevent smoking in real time. Better understanding of real-time smoking behavior can be helpful in numerous applications without the burden and recall bias associated with self-report.


OBJECTIVE
The goal of this study was to test the validity of using a smartwatch to advance the study of temporal patterns and characteristics of smoking in a controlled laboratory setting prior to its implementation in situ. Specifically, the aim was to compare smoking characteristics recorded by Automated Smoking PerceptIon and REcording (ASPIRE) on a smartwatch with the pocket Clinical Research Support System (CReSS) topography device, using video observation as the gold standard.


METHODS
Adult smokers (N=27) engaged in a video-recorded laboratory smoking task using the pocket CReSS while also wearing a Polar M600 smartwatch. In-house software, ASPIRE, was used to record accelerometer data to identify the duration of puffs and interpuff intervals (IPIs). The recorded sessions from CReSS and ASPIRE were manually annotated to assess smoking topography. Agreement between CReSS-recorded and ASPIRE-recorded smoking behavior was compared.


RESULTS
ASPIRE produced more consistent number of puffs and IPI durations relative to CReSS, when comparing both methods to visual puff count. In addition, CReSS recordings reported many implausible measurements in the order of milliseconds. After filtering implausible data recorded from CReSS, ASPIRE and CReSS produced consistent results for puff duration (R2=.79) and IPIs (R2=.73).


CONCLUSIONS
Agreement between ASPIRE and other indicators of smoking characteristics was high, suggesting that the use of ASPIRE is a viable method of passively characterizing smoking behavior. Moreover, ASPIRE was more accurate than CReSS for measuring puffs and IPIs. Results from this study provide the foundation for future utilization of ASPIRE to passively and accurately monitor and quantify smoking behavior in situ.
['Cole|Casey Anne|CA|https://orcid.org/0000-0002-0320-6894', 'Powers|Shannon|S|https://orcid.org/0000-0001-7902-6577', 'Tomko|Rachel L|RL|https://orcid.org/0000-0002-6961-4399', 'Froeliger|Brett|B|https://orcid.org/0000-0001-9451-9900', 'Valafar|Homayoun|H|https://orcid.org/0000-0002-1581-3464']
smoking smartwatch automated ASPIRE CReSS smoking topography wearable computing wearable technology