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Original article
Real-time data capture with electronic cigarettes for smoking cessation programme: a cloud platform for behavioural research
  1. Max W Y Lam1,
  2. Nelson W Y Leung2,
  3. Baker KK Bat1,
  4. Gary K S Leung1,
  5. Kelvin K F Tsoi1,2
  1. 1 Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong, Hong Kong
  2. 2 Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong
  1. Correspondence to Dr Kelvin K F Tsoi, Prince of Wales Hospital, Shatin, The Chinese University of Hong Kong, 4/F, School of Public Health and Primary Care, Hong Kong; kelvintsoi{at}cuhk.edu.hk

Abstract

Tobacco smoking is a major risk factor for many chronic diseases, which led to the popularity of electronic cigarette (e-cigarette) and showed to be an effective tool for tobacco smoking cessation. However, existing studies on e-cigarette use were based on users’ self-reported data. Detailed and accurate e-cigarette use records can be used to better understand e-cigarette use behaviour and design appropriate tobacco smoking cessation plan. Therefore, a platform for real-time data capture, transmission and cloud storage of e-cigarette usage is suggested to address these issues.

The application of cloud platform for data transfer, storage and analysis on medical research is still at a novel stage. In this study, a cloud-based infrastructure is established for data collection and storage of captured e-cigarette use behaviour; it consists of an e-cigarette, a smartphone, a smartphone application (APP) and a cloud server. Whenever the e-cigarette is inhaled, the time and number of puff will be transmitted to the APP through Bluetooth signal and then uploaded and stored to the cloud through the internet-connected smartphone. The flow of data transmission is performed automatically. E-cigarette smoking history can be recalled in real time and presented in the APP.

This remote cloud platform provides efficient analytical performance on a huge volume of data with high velocity of data creation. The sufficient data accuracy and completeness of e-cigarette use records help to better understand the behaviour and safety of e-cigarette usage and to plan an effective tobacco smoking cessation programme.

  • Lifestyle
  • Medical Apps
  • Remote Monitoring

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Introduction

Cigarette smoking is one of the major public health problems and a leading cause of preventable death. WHO states that tobacco kills up to half of its users at around six million people each year.1 It is a risk factor for numerous non-communicable diseases, including hypertension, stroke, chronic obstructive pulmonary disease, heart attacks and cancer.2–5 The quantity and duration of cigarette smoking are positively correlated with the risk of acquiring these diseases and rate of disease progression, which causes irreversible damage on health. According to the WHO Framework Convention on Tobacco Control, smoking abstinence is an essential key to reduce the health burden due to tobacco.6

To increase smoking cessation rate, nicotine replacement therapy is commonly used as adjunct therapy to alleviate withdrawal symptoms and reduce the motivation to smoke. Recently, electronic cigarette (e-cigarette) has been suggested as a new smoking cessation tool.7 8 It is an electronic device invented in 2003, which resembles the physical sensation of traditional tobacco smoking by allowing users to inhale and exhale the generated aerosol.9 10 Existing publications have suggested that e-cigarette is a less harmful alternative to tobacco smoking; however, studies were based on self-reported data and there are some arguments for the safety and long-term efficacy. In this study, we developed a cloud platform for e-cigarette to address these issues. Besides collecting e-cigarette usage record in a smartphone, it can upload data to the cloud and accessible by third party. As data are collected and transmitted automatically, the data accuracy and completeness are sufficient to address the true long-term efficiency and safety of e-cigarette use as a tobacco smoking reduction or cessation tool.

Cloud platform is an internet-based computing infrastructure consisting of high-performance hardware, firmware and software. The term ‘cloud’ denotes that the system is accessible anywhere over the internet. Adoption of cloud platform for centralised computing reduces the cost of local office-based computing equipment. The computational power of cloud platform is high and adjusted according to demand. The benefit of cloud platform is not limited to its flexibility and convenience; the maintenance cost of hardware and firmware and software update can be saved without sacrificing the performance.

Methodology

System architecture

A cloud-based data capturing platform documenting e-cigarette usage behaviour has been developed and the preliminary framework has been described.11 It consists of four components: (1) an e-cigarette, (2) a smartphone, (3) a smartphone application (APP) and (4) a cloud server and the framework is shown in figure 1. A commercially available e-cigarette with Bluetooth connection function and accessible application programming interface has been used. The e-cigarette will record the time and number of puff inhaled and data will be transmitted to smartphone automatically.12 Traditional tobacco smoking histories are reported by users manually. The smartphone with internet access is used for installation of smartphone APP and storing data locally. The APP transfers data received to the cloud platform and provides an overview of the smoking history. A data capturing cloud server, under the service provider Microsoft Windows Azure,13 has been developed specifically for e-cigarettes and smartphones connection. Other than storing baseline patient demographics from hospital interview and data from e-cigarette, it is also capable of analysing smoking puffing data and recognises correlations between smoking behaviour and different health endpoints. This giant technological advance has presented exciting new opportunities in healthcare data analysis.

Figure 1

Architecture of the cloud-based electronic cigarette data capturing platform.

Smartphone APP

The smartphone APP developed for the study is called Smoking Reduction APP and the user interface is shown in figure 2. It is available in both Apple iOS and Google ANDROID smartphone platforms. Every participant needs to create an account for recording and storing the frequency of usage and number of puffs produced by the e-cigarette. When the APP receives data from the e-cigarette device via Bluetooth signal, they will be stored temporarily in local device and synchronise between the APP and cloud platform regularly via the internet. Participants are required to self-report their daily history of tobacco smoking and any adverse event. Furthermore, detailed e-cigarette use report in calendar format can be reviewed with the real-time data recalled from the cloud platform. There is a button for the declaration of smoking abstinence; the expected day to quit smoking will be extrapolated according to a linear projection model.

Figure 2

Mobile application interface. APP, application.

To encourage user compliance, different medals are designed as incentive and the date required to quit smoking is estimated. For example, the gold or diamond medals represent frequent users showing significant smoking reduction or even successful smoking abstinence, respectively. All calculations are performed in the cloud server. The data flow from the e-cigarette to the data capturing platform in the cloud is shown in figure 3.

Figure 3

E-cigarette data flow. E-cigarette, electronic cigarette.

Discussion

This study suggests a cloud platform to capture smoking behaviour of using an e-cigarette. Besides collecting e-cigarette usage record in a smartphone, it can upload data to the cloud and accessible by third party. As data are collected and transmitted automatically, the sufficient data accuracy and completeness can address the true efficiency and safety of e-cigarette use as a tobacco smoking reduction or cessation tool.

Estimation of lung cancer risk

The risk reduction in lung cancer mortality is estimated based on a log link function between lung cancer mortality (Embedded Image ), smoking duration (Dk ) and intensity (Ik ).14 The model’s equation is expressed as Embedded Image where β 0k is the intercept estimate for age group k, and βDk and βIk are parameter estimates for duration and intensity of smoking, respectively. This model is independently fitted for different age groups and gender.

Application for public health research

Current available evidence suggests e-cigarette is a less harmful alternative to tobacco smoking; however, studies were based on self-reported data. The application of automatic data capturing by e-cigarette can reduce the user self-reporting bias, ensure the data completeness and better address the effectiveness and safety of e-cigarette use as a tobacco smoking cessation tool. The proposed platform aims at smoking reduction and cessation of heavy tobacco smoker, who are expected to parallelly use e-cigarette and tobacco cigarette, then gradually reduce the amount of cigarette smoking with the aid of e-cigarette until cessation of cigarette smoking. Baseline demographics of the e-cigarette users including comorbidity details, smoking history and level of nicotine dependency can be collected, encrypted and stored in the cloud.15 16 The e-cigarette use behaviour is captured automatically, while the frequency of daily cigarettes smoking can be submitted by the user manually through the smartphone APP.

The association of e-cigarette use, tobacco smoking, smoking reduction and healthcare endpoint can be analysed through the cloud platform; especially the question whether the e-cigarette is an effective tool for smoking reduction and cessation is addressed. Smokers may end up with (1) 100% e-cigarette smoker, (2) partially e-cigarette and tobacco smoker, (3) remain 100% tobacco smoker and (4) successfully quit smoking. The platform can also be used to support other clinical studies in public health, including prospective randomised controlled trials to compare e-cigarette and nicotine patch users for smoking cessation.

Future applications

Daily use of the e-cigarettes and tobacco smoking will provide a large-scale database. Data-mining approaches can be applied to observe the association of smoking behaviour and other healthcare endpoint. As smoking is a major risk factor for chronic diseases, this platform can be used to support other clinical studies in public health. In the future, the device would be potentially connected to other social functioning smartphone platforms, such as Facebook, to extend the investigation of interpersonal networking behaviour among smokers.

Conclusion

The application of automatic data capturing by e-cigarette can reduce the user self-reporting bias, ensure the data completeness and better address the effectiveness of e-cigarette use as a tobacco smoking cessation tool. An application of technology using cloud platform helps better monitoring and understanding the e-cigarette usage in practice. All data transmission is performed automatically once e-cigarette is inhaled. Smoking history can be reviewed by both participants and researchers anytime. This platform can be used to support other epidemiological studies in public health.

Acknowledgments

The devices (e-cigarettes) and consumables (e-liquid) were offered at a discounted price by Smokio and Halo, respectively.

References

View Abstract

Footnotes

  • Contributors Study concept and design, study supervision and revision of the manuscript: KKFT. Programme design and development: MWYL. Drafting of the manuscript: BB. Literature search: NWYL. Technical support and platform testing: GKSL.

  • Funding This work is partially sponsored by the Microsoft Research Asia (MSRA) Regional Seed Grant 2014.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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