Detection of Smoking Events from Confounding Activities of Daily Living

Lu, Jianchao; Wang, Jiaxing; Zheng, Xi; Karmakar, Chandan; Rajasegarar, Sutharshan

doi:10.1145/3290688.3290743

Cited by 17 publications

(12 citation statements)

References 9 publications

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“…In order to track cigarette consumption, mobile applications implement two types of loggers. The first type is subjective and requires the smoker to enter the smoking of each cigarette, while the second is objective and rely on smartwatches (Cole et al 2017;Shoaib et al 2018) or proprietary wristbands (Lopez-Meyer et al 2013;Lu et al 2019) to detect the number of cigarettes and puffs. The Pivot app goes one step further and employs a breath sensor connected to the smoker's mobile device.…”

Section: Innovative Ways To Curtail Smokingmentioning

confidence: 99%

The mutagenic effect of tobacco smoke on male fertility

Omolaoye

El-Shahawy

Skosana

et al. 2021

Environ Sci Pollut Res

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Despite the association between tobacco use and the harmful effects on general health as well as male fertility parameters, smoking remains globally prevalent. The main content of tobacco smoke is nicotine and its metabolite cotinine. These compounds can pass the blood-testis barrier, which subsequently causes harm of diverse degree to the germ cells. Although controversial, smoking has been shown to cause not only a decrease in sperm motility, sperm concentration, and an increase in abnormal sperm morphology, but also genetic and epigenetic aberrations in spermatozoa. Both animal and human studies have highlighted the occurrence of sperm DNA-strand breaks (fragmentation), genome instability, genetic mutations, and the presence of aneuploids in the germline of animals and men exposed to tobacco smoke. The question to be asked at this point is, if smoking has the potential to cause all these genetic aberrations, what is the extent of damage? Hence, this review aimed to provide evidence that smoking has a mutagenic effect on sperm and how this subsequently affects male fertility. Additionally, the role of tobacco smoke as an aneugen will be explored. We furthermore aim to incorporate the epidemiological aspects of the aforementioned and provide a holistic approach to the topic.

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Section: Innovative Ways To Curtail Smokingmentioning

confidence: 99%

The mutagenic effect of tobacco smoke on male fertility

Omolaoye

El-Shahawy

Skosana

et al. 2021

Environ Sci Pollut Res

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“…Another promising direction to improve real-time simulation lies in the increasingly popular machine learning and deep learning models, which have been extensively in real-time systems to detect object location (Pan et al 2018), user activities (Lu et al 2019;Bhandari et al 2017), driver drowsiness (Zhang et al 2019), road conditions for vehicles (Zhou et al 2019;Xie et al 2018). As real-time systems are highly complex and essentially probabilistic, deep learning models can be used along with real-time simulators to improve the robustness and accuracy of simulation models.…”

Section: Resultsmentioning

confidence: 99%

Real-Time Simulation Support for Real-Time Systems

Zheng¹

2020

Handbook of Real-Time Computing

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Simulations especially real-time simulation have been widely used for the design and testing of real-time systems. The advancement of simulation tools has largely attributed to the evolution of computing technologies. With the reduced cost and improved performance, researchers and industry engineers are able to access a variety of effective and highly performing simulation tools. This chapter describes the definition and importance of real-time simulation for real-time systems. Moreover, the chapter also points out the challenges met in real-time simulation and walks through some promising research progress in addressing some of the challenges.

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“…From the 6D IMU signal seen in the work by Raiff et al [72], the authors applied an SVM-based learning method followed by an edge-detection algorithm to detect both smoking events and inter-puff-intervals. Lu et al [73] developed a Random Forest-based classifier for detecting smoking events with concurrent and confound activities. Parate et al [74] preprocessed a 9D IMU signal as a quaternion format [75] and a probabilistic model, combining the random forest and conditional random field classifier to detect both smoking events and puffs.…”

Section: Evaluation Of Sensing Methodologiesmentioning

confidence: 99%

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

Imtiaz

Ramos-Garcia

Wattal

et al. 2019

Sensors

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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. However, wearable technologies have inherent limitations, and their sensor responses are often influenced by wearers’ behavior, motion and environmental factors. This paper presents a systematic review of current and forthcoming wearable technologies, with a focus on sensing elements, body placement, detection accuracy, underlying algorithms and applications. Full-texts of 86 scientific articles were reviewed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines to address three research questions oriented to cigarette smoking, in order to: (1) Investigate the behavioral and physiological manifestations of cigarette smoking targeted by wearable sensors for smoking detection; (2) explore sensor modalities employed for detecting these manifestations; (3) evaluate underlying signal processing and pattern recognition methodologies and key performance metrics. The review identified five specific smoking manifestations targeted by sensors. The results suggested that no system reached 100% accuracy in the detection or evaluation of smoking-related features. Also, the testing of these sensors was mostly limited to laboratory settings. For a realistic evaluation of accuracy metrics, wearable devices require thorough testing under free-living conditions.

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Detection of Smoking Events from Confounding Activities of Daily Living

Cited by 17 publications

References 9 publications

The mutagenic effect of tobacco smoke on male fertility

The mutagenic effect of tobacco smoke on male fertility

Real-Time Simulation Support for Real-Time Systems

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

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