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使用智能手表技术对吸烟特征进行量化:新技术的试点可行性研究

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

作者信息

Cole Casey Anne, Powers Shannon, Tomko Rachel L, Froeliger Brett, Valafar Homayoun

机构信息

Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, United States.

Department of Psychological Sciences, University of Missouri-Columbia, Columbia, MO, United States.

出版信息

JMIR Form Res. 2021 Feb 5;5(2):e20464. doi: 10.2196/20464.

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 (R=.79) and IPIs (R=.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.

摘要

背景

虽然在研究烟草使用障碍和尼古丁成瘾的神经生物学及临床基础方面已经取得了许多技术进步,但在实时监测、表征和干预以预防吸烟的技术方面进展相对较小。更好地理解实时吸烟行为在众多应用中可能会有所帮助,且不存在与自我报告相关的负担和回忆偏差。

目的

本研究的目的是在智能手表原位实施之前,在受控实验室环境中测试使用智能手表推进吸烟时间模式和特征研究的有效性。具体而言,目标是将智能手表上的自动吸烟感知与记录(ASPIRE)记录的吸烟特征与口袋临床研究支持系统(CReSS)地形设备进行比较,以视频观察作为金标准。

方法

成年吸烟者(N = 27)在使用口袋CReSS进行视频记录的实验室吸烟任务时,同时佩戴Polar M600智能手表。使用内部软件ASPIRE记录加速度计数据,以确定抽吸持续时间和抽吸间隔时间(IPI)。对CReSS和ASPIRE记录的会话进行人工注释,以评估吸烟地形。比较CReSS记录的和ASPIRE记录的吸烟行为之间的一致性。

结果

与视觉抽吸计数相比,将两种方法与视觉抽吸计数进行比较时,ASPIRE产生的抽吸次数和IPI持续时间更一致。此外,CReSS记录报告了许多以毫秒为单位的不合理测量值。在过滤掉CReSS记录的不合理数据后,ASPIRE和CReSS在抽吸持续时间(R = 0.79)和IPI(R = 0.73)方面产生了一致的结果。

结论

ASPIRE与其他吸烟特征指标之间的一致性很高,这表明使用ASPIRE是被动表征吸烟行为的一种可行方法。此外,在测量抽吸次数和IPI方面,ASPIRE比CReSS更准确。本研究结果为未来利用ASPIRE原位被动、准确地监测和量化吸烟行为奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1101/7895644/3ac2b345e6ad/formative_v5i2e20464_fig1.jpg

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