DeepPuff: Utilizing Deep Learning for Smoking Behavior Identification in Free-living Environment.

A comprehensive assessment of cigarette smoking behavior and its effect on health requires a detailed examination of smoke exposure. We propose a CNN-LSTM-based deep learning architecture named DeepPuff to quantify Respiratory Smoke Exposure Metrics (RSEM). Smoke inhalations were detected from the breathing and hand gesture sensors of the Personal Automatic Cigarette Tracker v2 (PACT 2.

Relationships Between the Nicotine Metabolite Ratio and Laboratory Assessments of Smoking Reinforcement and Craving Among Adults in a Smoking Cessation Trial.

Introduction: People who metabolize nicotine more quickly are generally less successful at quitting smoking. However, the mechanisms that link individual differences in the nicotine metabolite ratio (NMR), a phenotypic biomarker of the rate of nicotine clearance, to smoking outcomes are unclear. We tested the hypotheses that higher NMR is associated with greater smoking reinforcement, general craving, and cue-induced cigarette craving in a treatment-seeking sample.

A preliminary randomized trial of reinforcement contingencies to improve compliance with ecological momentary assessment.

Ecological Momentary Assessment (EMA) methods are increasingly used by translational scientists to study real-world behavior and experience. The ability to draw meaningful conclusions from EMA research depends upon participant compliance with assessment completion. Most EMA studies provide financial compensation for compliance, but little empirical evidence addresses the impact of reinforcement parameters on the level of compliance.

An Evaluation of the Contextual Factors Associated With the Use of Either Tobacco or Electronic Cigarettes in Individuals Who Dual Use.

Introduction: Little is known about patterns of dual use of tobacco and electronic cigarettes (e-cigarettes), especially regarding the factors that lead people to choose either product in particular situations. Identifying contextual factors that are associated with product use would enhance understanding of the maintenance of dual product use.

Methods: Individuals who dual use (N = 102) completed ecological momentary assessment surveys via text message regarding the recent use of tobacco and e-cigarettes for 2 weeks.

Evaluating Declines in Compliance With Ecological Momentary Assessment in Longitudinal Health Behavior Research: Analyses From a Clinical Trial.

Background: Ecological momentary assessment (EMA) is increasingly used to evaluate behavioral health processes over extended time periods. The validity of EMA for providing representative, real-world data with high temporal precision is threatened to the extent that EMA compliance drops over time.

Objective: This research builds on prior short-term studies by evaluating the time course of EMA compliance over 9 weeks and examines predictors of weekly compliance rates among cigarette-using adults.

An Examination of Objective and Self-Report Measures of Ad Libitum Electronic Cigarette Use: Identifying Patterns of Puffing Behavior and Evaluating Self-Report Items.

Introduction: There has been little research objectively examining use-patterns among individuals who use electronic cigarettes (e-cigarettes). The primary aim of this study was to identify patterns of e-cigarette use and categorize distinct use-groups by analyzing patterns of puff topography variables over time. The secondary aim was to identify the extent to which self-report questions about use accurately assess e-cigarette use-behavior.

Effect of Extending the Duration of Prequit Treatment With Varenicline on Smoking Abstinence: A Randomized Clinical Trial.

Importance: Even with varenicline, the leading monotherapy for tobacco dependence, smoking abstinence rates remain low. Preliminary evidence suggests that extending the duration of varenicline treatment before quitting may increase abstinence.

Objective: To test the hypotheses that, compared with standard run-in varenicline treatment (1 week before quitting), extended run-in varenicline treatment (4 weeks before quitting) reduces smoking exposure before the target quit date (TQD) and enhances abstinence, particularly among women.

Analyzing Impact of Mouthpiece-based Puff Topography Devices on Smoking Behavior using Wearable Sensors.

Detailed assessment of smoking topography (puffing and post-puffing metrics) can lead to a better understanding of factors that influence tobacco use. Research suggests that portable mouthpiece-based devices used for puff topography measurement may alter natural smoking behavior. This paper evaluated the impact of a portable puff topography device (CReSS Pocket) on puffing & post-puffing topography using a wearable system, the Personal Automatic Cigarette Tracker v2 (PACT 2.

A Psychometric Evaluation of the Stanford Expectations of Treatment Scale (SETS) in the Context of a Smoking Cessation Trial.

Introduction: Although treatment outcome expectancies (TOEs) may influence clinical outcomes, TOEs are rarely reported in the smoking cessation literature, in part because of the lack of validated measures. Therefore, we conducted a psychometric evaluation of TOEs scores with the Stanford Expectations of Treatment Scale (SETS) in the context of a smoking cessation clinical trial.

Methods: Participants were 320 adults enrolled in a randomized controlled trial of extended versus standard pre-quit varenicline treatment for smoking cessation (clinicaltrials.

Combined smoking and alcohol cues: Effects on craving, drug-seeking, and consumption.

Background: Alcohol and cigarettes are commonly used together, but little is known about their joint motivational impact. Cue reactivity studies have customarily examined alcohol and smoking cues in isolation, despite the potential for cues to elicit stronger motivational responses when combined. This study used a validated cue reactivity procedure (Choice Behavior Under Cued Conditions) systematically to disentangle the separate and joint effects of alcohol and cigarette cues on substance use motivation.

Electromyogram in Cigarette Smoking Activity Recognition.

In this study, information from surface electromyogram (sEMG) signals was used to recognize cigarette smoking. The sEMG signals collected from lower arm were used in two different ways: (1) as an individual predictor of smoking activity and (2) as an additional sensor/modality along with the inertial measurement unit (IMU) to augment recognition performance. A convolutional and a recurrent neural network were utilized to recognize smoking-related hand gestures.

The impact of three weeks of pre-quit varenicline on reinforcing value and craving for cigarettes in a laboratory choice procedure.

Rationale: Varenicline, a partial nicotinic agonist, is theorized to attenuate pre-quit smoking reinforcement and post-quit withdrawal and craving. However, the mechanisms of action have not been fully characterized, as most studies employ only retrospective self-report measures, hypothetical indices of reinforcing value, and/or nontreatment-seeking samples.

Objectives: The current research examined the impact of pre-quit varenicline (vs.

A Meta-Analysis of Cue Reactivity in Tobacco Cigarette Smokers.

Introduction: The cue reactivity paradigm allows for systematic evaluation of motivational responses to drug-related cues that may elicit drug use. The literature on this topic has grown substantially in recent decades, and the methodology used to study cue reactivity has varied widely across studies. The present research provided a meta-analytic investigation of variables that have an impact on cue reactivity effects to enhance our understanding of this key feature of tobacco use disorders.

A CNN-LSTM neural network for recognition of puffing in smoking episodes using wearable sensors.

A detailed assessment of smoking behavior under free-living conditions is a key challenge for health behavior research. A number of methods using wearable sensors and puff topography devices have been developed for smoking and individual puff detection. In this paper, we propose a novel algorithm for automatic detection of puffs in smoking episodes by using a combination of Respiratory Inductance Plethysmography and Inertial Measurement Unit sensors.

Objective Detection of Cigarette Smoking from Physiological Sensor Signals.

Cigarette smoking has severe health impacts on those who smoke and the people around them. Several wearable sensing modalities have recently been investigated to collect objective data on daily smoking, including detection of smoking episodes from breathing patterns, hand to mouth behavior, and characteristic hand gestures or cigarette lighting events. In order to provide new insight into ongoing research on the objective collection of smoking-related events, this paper proposes a novel method to identify smoking events from the associated changes in heart rate parameters specific to smoking.

A Comparison of SVM and CNN-LSTM Based Approach for Detecting Smoke Inhalations from Respiratory signal.

Wearable sensors have successfully been used in recent studies to monitor cigarette smoking events and analyze people's smoking behavior. Respiratory inductive plethysmography (RIP) has been employed to track breathing and to identify characteristic breathing pattern specific to smoking. Pattern recognition algorithms such as Support Vector Machine (SVM), Hidden Markov Model, Decision tree, or ensemble approaches have been used to identify smoke inhalations.

Computation of Cigarette Smoke Exposure Metrics From Breathing.

Traditional metrics of smoke exposure in cigarette smokers are derived either from self-report, biomarkers, or puff topography. Methods involving biomarkers measure concentrations of nicotine, nicotine metabolites, or carbon monoxide. Puff-topography methods employ portable instruments to measure puff count, puff volume, puff duration, and inter-puff interval.

Wearable Egocentric Camera as a Monitoring Tool of Free-Living Cigarette Smoking: A Feasibility Study.

Introduction: Wearable sensors may be used for the assessment of behavioral manifestations of cigarette smoking under natural conditions. This paper introduces a new camera-based sensor system to monitor smoking behavior. The goals of this study were (1) identification of the best position of sensor placement on the body and (2) feasibility evaluation of the sensor as a free-living smoking-monitoring tool.

Wearable Sensors for Monitoring of Cigarette Smoking in Free-Living: A Systematic Review.

Globally, cigarette smoking is widespread among all ages, and smokers struggle to quit. The design of effective cessation interventions requires an accurate and objective assessment of smoking frequency and smoke exposure metrics. Recently, wearable devices have emerged as a means of assessing cigarette use.

Comparing the reward value of cigarettes and food during tobacco abstinence and nonabstinence.

Background: Some addiction theories propose that nicotine dependence is characterized by an imbalance between motivation for cigarettes compared to non-drug rewards. This imbalance may become increasingly polarized during abstinence, which further potentiates smoking. The present study evaluated motivation for cigarettes and food during abstinence and nonabstinence in daily smokers.

Assessment of the Choice Behavior Under Cued Conditions (CBUCC) paradigm as a measure of motivation to smoke under laboratory conditions.

Background And Aims: The Choice Behavior under Cued Conditions (CBUCC) task uses three indices of tobacco use (consumption, money spent to access a cigarette and latency to reach for a cigarette) to assess motivation to smoke under laboratory conditions. Initial research with this procedure has shown that it can evince cue-specific craving and differential responding for smoking versus a neutral cue. This study aimed to replicate these findings and assess the interaction of cue-specific craving and behavior with abstinence prior to testing.

Assessment of dog owners' knowledge relating to the diagnosis and treatment of canine food allergies.

Canine food allergies are the result of an immune-mediated hypersensitivity reaction to dietary proteins and can manifest as a variety of dermatologic and/or gastrointestinal clinical signs. Food elimination trials followed by provocation tests are used to diagnose food allergies; however, no research has been conducted to determine whether elimination trials and provocation tests are being properly implemented by pet owners. The objectives of this study were to determine the level of knowledge of dog owners regarding food allergies, and to investigate how dog owners approach diagnosis and treatment with their veterinarians.

Smoking detection based on regularity analysis of hand to mouth gestures.

A number of studies have been introduced for the detection of smoking via a variety of features extracted from the wrist IMU data. However, none of the previous studies investigated gesture regularity as a way to detect smoking events. This study describes a novel method to detect smoking events by monitoring the regularity of hand gestures.

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

In recent years, a number of wearable approaches have been introduced for objective monitoring of cigarette smoking based on monitoring of hand gestures, breathing or cigarette lighting events. However, non-reactive, objective and accurate measurement of everyday cigarette consumption in the wild remains a challenge. This study utilizes a wearable sensor system (Personal Automatic Cigarette Tracker 2.