PDF(Pubmed)
Abstract：
BACKGROUND: Objective measures of screen time are necessary to better understand the complex relationship between screen time and health outcomes. However, current objective measures of screen time (e.g., passive sensing applications) are limited in identifying the user of the mobile device, a critical limitation in children\'s screen time research where devices are often shared across a family. Behavioral biometrics, a technology that uses embedded sensors on modern mobile devices to continuously authenticate users, could be used to address this limitation.
OBJECTIVE: The purpose of this scoping review was to summarize the current state of behavioral biometric authentication and synthesize these findings within the scope of applying behavioral biometric technology to screen time measurement.
METHODS: We systematically searched five databases (Web of Science Core Collection, Inspec in Engineering Village, Applied Science & Technology Source, IEEE Xplore, PubMed), with the last search in September of 2022. Eligible studies were on the authentication of the user or the detection of demographic characteristics (age, gender) using built-in sensors on mobile devices (e.g., smartphone, tablet). Studies were required to use the following methods for authentication: motion behavior, touch, keystroke dynamics, and/or behavior profiling. We extracted study characteristics (sample size, age, gender), data collection methods, data stream, model evaluation metrics, and performance of models, and additionally performed a study quality assessment. Summary characteristics were tabulated and compiled in Excel. We synthesized the extracted information using a narrative approach.
RESULTS: Of the 14,179 articles screened, 122 were included in this scoping review. Of the 122 included studies, the most highly used biometric methods were touch gestures (n = 76) and movement (n = 63), with 30 studies using keystroke dynamics and 6 studies using behavior profiling. Of the studies that reported age (47), most were performed exclusively in adult populations (n = 34). The overall study quality was low, with an average score of 5.5/14.
CONCLUSIONS: The field of behavioral biometrics is limited by the low overall quality of studies. Behavioral biometric technology has the potential to be used in a public health context to address the limitations of current measures of screen time; however, more rigorous research must be performed in child populations first.
BACKGROUND: The protocol has been pre-registered in the Open Science Framework database ( https://doi.org/10.17605/OSF.IO/92YCT ).
OBJECTIVE: The purpose of this scoping review was to summarize the current state of behavioral biometric authentication and synthesize these findings within the scope of applying behavioral biometric technology to screen time measurement.
METHODS: We systematically searched five databases (Web of Science Core Collection, Inspec in Engineering Village, Applied Science & Technology Source, IEEE Xplore, PubMed), with the last search in September of 2022. Eligible studies were on the authentication of the user or the detection of demographic characteristics (age, gender) using built-in sensors on mobile devices (e.g., smartphone, tablet). Studies were required to use the following methods for authentication: motion behavior, touch, keystroke dynamics, and/or behavior profiling. We extracted study characteristics (sample size, age, gender), data collection methods, data stream, model evaluation metrics, and performance of models, and additionally performed a study quality assessment. Summary characteristics were tabulated and compiled in Excel. We synthesized the extracted information using a narrative approach.
RESULTS: Of the 14,179 articles screened, 122 were included in this scoping review. Of the 122 included studies, the most highly used biometric methods were touch gestures (n = 76) and movement (n = 63), with 30 studies using keystroke dynamics and 6 studies using behavior profiling. Of the studies that reported age (47), most were performed exclusively in adult populations (n = 34). The overall study quality was low, with an average score of 5.5/14.
CONCLUSIONS: The field of behavioral biometrics is limited by the low overall quality of studies. Behavioral biometric technology has the potential to be used in a public health context to address the limitations of current measures of screen time; however, more rigorous research must be performed in child populations first.
BACKGROUND: The protocol has been pre-registered in the Open Science Framework database ( https://doi.org/10.17605/OSF.IO/92YCT ).
摘要：
背景：必须客观地测量屏幕时间，以更好地了解屏幕时间与健康结果之间的复杂关系。然而,屏幕时间的当前客观度量(例如，被动感测应用)在识别移动设备的用户方面受到限制，在儿童的屏幕时间研究中，设备经常在家庭中共享的一个关键限制。行为生物识别技术,一种在现代移动设备上使用嵌入式传感器来持续验证用户的技术，可以用来解决这个限制。
目的：本次范围界定综述的目的是总结行为生物识别认证的现状，并在应用行为生物识别技术筛选时间测量的范围内综合这些发现。
方法：我们系统地搜索了五个数据库(WebofScienceCoreCollection，Inspec在工程村，应用科学与技术来源，IEEEXplore,PubMed),最后一次搜索是在2022年9月。符合条件的研究是关于用户的身份验证或人口统计学特征的检测(年龄，性别)使用移动设备上的内置传感器(例如，智能手机,平板电脑)。研究需要使用以下方法进行身份验证：运动行为，触摸,按键动力学,和/或行为分析。我们提取了研究特征(样本量，年龄,性别)，数据收集方法，数据流,模型评估指标，和模型的性能，并额外进行了研究质量评估。摘要特征在Excel中制表和编译。我们使用叙事方法综合了提取的信息。
结果：在筛选的14179篇文章中，122人被包括在这次范围审查中。在纳入的122项研究中，最常用的生物识别方法是触摸手势（n=76）和移动（n=63），有30项使用击键动力学的研究和6项使用行为分析的研究。在报告年龄的研究中（47），大多数仅在成人人群中进行(n=34).总体研究质量较低，平均得分为5.5/14。
结论：行为生物识别领域受到整体研究质量低的限制。行为生物识别技术有可能在公共卫生环境中使用，以解决当前测量屏幕时间的局限性；但是，必须首先在儿童人群中进行更严格的研究。
背景：该协议已在OpenScienceFramework数据库（https://doi.org/10.17605/OSF）中预先注册。IO/92YCT）。
目的：本次范围界定综述的目的是总结行为生物识别认证的现状，并在应用行为生物识别技术筛选时间测量的范围内综合这些发现。
方法：我们系统地搜索了五个数据库(WebofScienceCoreCollection，Inspec在工程村，应用科学与技术来源，IEEEXplore,PubMed),最后一次搜索是在2022年9月。符合条件的研究是关于用户的身份验证或人口统计学特征的检测(年龄，性别)使用移动设备上的内置传感器(例如，智能手机,平板电脑)。研究需要使用以下方法进行身份验证：运动行为，触摸,按键动力学,和/或行为分析。我们提取了研究特征(样本量，年龄,性别)，数据收集方法，数据流,模型评估指标，和模型的性能，并额外进行了研究质量评估。摘要特征在Excel中制表和编译。我们使用叙事方法综合了提取的信息。
结果：在筛选的14179篇文章中，122人被包括在这次范围审查中。在纳入的122项研究中，最常用的生物识别方法是触摸手势（n=76）和移动（n=63），有30项使用击键动力学的研究和6项使用行为分析的研究。在报告年龄的研究中（47），大多数仅在成人人群中进行(n=34).总体研究质量较低，平均得分为5.5/14。
结论：行为生物识别领域受到整体研究质量低的限制。行为生物识别技术有可能在公共卫生环境中使用，以解决当前测量屏幕时间的局限性；但是，必须首先在儿童人群中进行更严格的研究。
背景：该协议已在OpenScienceFramework数据库（https://doi.org/10.17605/OSF）中预先注册。IO/92YCT）。
