Bridging the last gap

Scholl, Philipp M.; Kücükyildiz, Nagihan; Laerhoven, Kristof Van

doi:10.1145/2494091.2494104

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Besides, acoustic sensor and breath carbon monoxide (CO) sensor were also used as a way to identify smoking by Echebarria and Valencia, respectively 27 28. In addition, less cumbersome and more naturalistic systems with smaller form factor,s such as augmented lighters and a wrist-worn RisQ system, were used for capturing smoking events 29–32. These sensors can avoid users’ subjective bias and significantly alleviate their burden through automatic detection.…”

Section: Introductionmentioning

confidence: 99%

“…From these signals, we can assess a subject’s sleep quality, mobility pattern, heart rate variability (HRV) and stress arousal quantitatively, which could help us form a more accurate picture of their psychophysiological statuses36; while on the other, smartphones often embedded with many sensors can not only record time, location, weather, ambient light and sound related to smoking events, but also trigger ecological momentary assessment (EMA) surveys at the opportunistic moments. These features will automate the acquisition of multimodal information, which, once fused, will enable researchers to infer the underlying causes and contexts of smoking 31 37 38. On the whole, combining traditional research methods with wearable and mobile technologies will empower researchers to conduct a quantified and non-biassed study of smoking habits outside laboratory settings.…”

Section: Introductionmentioning

confidence: 99%

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Ambulatory Smoking Habits Investigation based on Physiology and Context (ASSIST) using wearable sensors and mobile phones: protocol for an observational study

Zhai¹,

Schiavone

Diest

et al. 2019

BMJ Open

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IntroductionSmoking prevalence continues to be high over the world and smoking-induced diseases impose a heavy burden on the medical care system. As believed by many researchers, a promising way to promote healthcare and well-being at low cost for the large vulnerable smoking population is through eHealth solutions by providing self-help information about smoking cessation. But in the absence of first-hand knowledge about smoking habits in daily life settings, systems built on these methods often fail to deliver proactive and tailored interventions for different users and situations over time, thus resulting in low efficacy. To fill the gap, an observational study has been developed on the theme of objective and non-biased monitoring of smoking habits in a longitudinal and ambulatory mode. This paper presents the study protocol. The primary objective of the study is to reveal the contextual and physiological pattern of different smoking behaviours using wearable sensors and mobile phones. The secondary objectives are to (1) analyse cue factors and contextual situations of smoking events; (2) describe smoking types with regard to users’ characteristics and (3) compare smoking types between and within subjects.Methods and analysesThis is an observational study aimed at reaching 100 participants. Inclusion criteria are adults aged between 18 and 65 years, current smoker and office worker. The primary outcome is a collection of a diverse and inclusive data set representing the daily smoking habits of the general smoking population from similar social context. Data analysation will revolve around our primary and secondary objectives. First, linear regression and linear mixed model will be used to estimate whether a factor or pattern have consistent (p value<0.05) correlation with smoking. Furthermore, multivariate multilevel analysis will be used to examine the influence of smokers’ characteristics (sex, age, education, socioeconomic status, nicotine dependence, attitudes towards smoking, quit attempts, etc), contextual factors, and physical and emotional statuses on their smoking habits. Most recent machine learning techniques will also be explored to combine heterogeneous data for classification of smoking events and prediction of craving.Ethics and disseminationThe study was designed together by an interdisciplinary group of researchers, including psychologist, psychiatrist, engineer and user involvement coordinator. The protocol was reviewed and approved by the ethical review board of UZ Leuven on 18 April 2016, with an approval number S60078. The study will allow us to characterise the types of smokers and triggering events. These findings will be disseminated through peer-reviewed articles.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ambulatory Smoking Habits Investigation based on Physiology and Context (ASSIST) using wearable sensors and mobile phones: protocol for an observational study

Zhai¹,

Schiavone

Diest

et al. 2019

BMJ Open

View full text Add to dashboard Cite

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Connecting the things to the internet

Jewell

Costanza

Kittley-Davies

2015

Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

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The availability of low-power Wi-Fi radio modules opens up opportunities to leverage the existing prevalent Wi-Fi infrastructure for large-scale trials and deployments of Ubicomp technology. In this paper we address the challenge of supporting end-users, especially when they are not technical experts, in connecting new low-power, low-cost Wi-Fi devices with very minimal UIs to an existing, secure Wi-Fi infrastructure. We report two usability studies through which 30 participants, with no formal technical training, compared 4 alternative configuration techniques, selected based on cost and consumption constraints, and on adoption in off-the-shelf products. Through an analysis of success rate and causes of failure, our results indicate that two techniques are noticeably more usable than others. These are a web-based configuration mechanism, where users connect to an access point on the Wi-Fi device, and one that makes use of a standard audio cable to connect a smartphone to the device to be configured.

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Lessons learned from designing an instrumented lighter for assessing smoking status

Scholl

Laerhoven

2017

Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 AC

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Bridging the last gap

Cited by 3 publications

References 7 publications

Ambulatory Smoking Habits Investigation based on Physiology and Context (ASSIST) using wearable sensors and mobile phones: protocol for an observational study

Ambulatory Smoking Habits Investigation based on Physiology and Context (ASSIST) using wearable sensors and mobile phones: protocol for an observational study

Connecting the things to the internet

Lessons learned from designing an instrumented lighter for assessing smoking status

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