Literature DB >> 33544083

Quantification of Smoking Characteristics Using Smartwatch Technology: Pilot Feasibility Study of New Technology.

Casey Anne Cole1, Shannon Powers2,3, Rachel L Tomko4, Brett Froeliger2,5, Homayoun Valafar1.   

Abstract

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. ©Casey Anne Cole, Shannon Powers, Rachel L Tomko, Brett Froeliger, Homayoun Valafar. Originally published in JMIR Formative Research (http://formative.jmir.org), 05.02.2021.

Entities:  

Keywords:  ASPIRE; CReSS; automated; smartwatch; smoking; smoking topography; wearable computing; wearable technology

Year:  2021        PMID: 33544083      PMCID: PMC7895644          DOI: 10.2196/20464

Source DB:  PubMed          Journal:  JMIR Form Res        ISSN: 2561-326X


  26 in total

1.  A wearable sensor system for monitoring cigarette smoking.

Authors:  Edward Sazonov; Paulo Lopez-Meyer; Stephen Tiffany
Journal:  J Stud Alcohol Drugs       Date:  2013-11       Impact factor: 2.582

2.  Comparison of methods for measurement of smoking behavior: mouthpiece-based computerized devices versus direct observation.

Authors:  Melissa D Blank; Steven Disharoon; Thomas Eissenberg
Journal:  Nicotine Tob Res       Date:  2009-06-11       Impact factor: 4.244

3.  Effect of Real-Time Monitoring and Notification of Smoking Episodes on Smoking Reduction: A Pilot Study of a Novel Smoking Cessation App.

Authors:  Reuven Dar
Journal:  Nicotine Tob Res       Date:  2018-11-15       Impact factor: 4.244

4.  Combined Smoking Cues Enhance Reactivity and Predict Immediate Subsequent Smoking.

Authors:  Cynthia A Conklin; F Joseph McClernon; Elizabeth J Vella; Christopher J Joyce; Ronald P Salkeld; Craig S Parzynski; Lee Bennett
Journal:  Nicotine Tob Res       Date:  2019-01-04       Impact factor: 4.244

Review 5.  Methods to reduce the incidence of false negative trial results in substance use treatment research.

Authors:  Rachel L Tomko; Erin A McClure; Lindsay M Squeglia; Hayley Treloar Padovano; Aimee L McRae-Clark; Nathaniel L Baker; Matthew J Carpenter; Kevin M Gray
Journal:  Curr Opin Psychol       Date:  2019-01-28

6.  Smoking topography: reliability and validity in dependent smokers.

Authors:  Eun M Lee; Jennifer L Malson; Andrew J Waters; Eric T Moolchan; Wallace B Pickworth
Journal:  Nicotine Tob Res       Date:  2003-10       Impact factor: 4.244

7.  Human cigarette smoking: effects of puff and inhalation parameters on smoke exposure.

Authors:  J P Zacny; M L Stitzer; F J Brown; J E Yingling; R R Griffiths
Journal:  J Pharmacol Exp Ther       Date:  1987-02       Impact factor: 4.030

Review 8.  Defining and Measuring Abstinence in Clinical Trials of Smoking Cessation Interventions: An Updated Review.

Authors:  Megan E Piper; Christopher Bullen; Suchitra Krishnan-Sarin; Nancy A Rigotti; Marc L Steinberg; Joanna M Streck; Anne M Joseph
Journal:  Nicotine Tob Res       Date:  2020-06-12       Impact factor: 5.825

9.  Enhancing Diabetes Self-Management Through Collection and Visualization of Data From Multiple Mobile Health Technologies: Protocol for a Development and Feasibility Trial.

Authors:  Ryan J Shaw; Angel Barnes; Dori Steinberg; Jacqueline Vaughn; Anna Diane; Erica Levine; Allison Vorderstrasse; Matthew J Crowley; Eleanor Wood; Daniel Hatch; Allison Lewinski; Meilin Jiang; Janee Stevenson; Qing Yang
Journal:  JMIR Res Protoc       Date:  2019-06-03

10.  Cigarette Smoking Detection with An Inertial Sensor and A Smart Lighter.

Authors:  Volkan Senyurek; Masudul Imtiaz; Prajakta Belsare; Stephen Tiffany; Edward Sazonov
Journal:  Sensors (Basel)       Date:  2019-01-29       Impact factor: 3.576

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