Assessing Children's Screen Time with Wearable Sensor
使用可穿戴传感器评估儿童的屏幕时间
基本信息
- 批准号:10659471
- 负责人:
- 金额:$ 18.16万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-08-01 至 2024-07-31
- 项目状态:已结题
- 来源:
- 关键词:AccelerometerAgeAlgorithmsArtificial IntelligenceBehaviorBehavior TherapyCellular PhoneChildChild AdvocacyChild DevelopmentChild HealthClinicalCommunicationComputational algorithmComputer Vision SystemsComputersComputing MethodologiesDataData SetDetectionDevelopmentDevicesEngineeringEnvironmentExplosionExposure toEyeFamilyGuidelinesHealthHourHumanImageImpaired cognitionInterest GroupLabelManualsMeasurementMeasuresMethodologyMethodsMonitorNursery SchoolsObesityOwnershipParentsPatient Self-ReportPatternPsychologistPsychologyReadingReportingResearchResearch PersonnelSleep DisordersTabletsTechniquesTechnologyTestingTimeUnited StatesValidationVisionVisual AccommodationWorkWorld Health Organizationartificial intelligence algorithmbasebehavioral studydesigndigitalexperimental studyminimally invasivenovelrecruitsedentarysedentary activitysmartphone Applicationteachertemporal measurementtooltv watchingvisual trackingwearable devicewearable sensor technologyyoung adult
项目摘要
Project summary
The explosion of digital technology ownership in the past decade has led to a dramatically increased screen
exposure for children. In the United States, over 95% of families with children have a smartphone, TV, and
desktop monitors, which has raised a growing concern about the impact of screens on children's health.
Excessive screen exposure has been closely associated with increased eye problems, sleep disorders, obesity,
and cognitive impairments among children. Due to these concerns, World Health Organization (WHO) has
recently (April 2019) suggested that children between 2 and 4 should have less than 1 hour of sedentary screen
time per day. However, there is an evidence gap between actual screen time in research and parental control
and assessment from measurement tools. Existing methodologies of assessing screen exposure lack construct
validity, as they heavily rely upon self-report, smartphone applications, or research technologies (e.g. eye-
tracking glasses). Self-report is prone to reporting bias. Smartphone applications lack the capability of measuring
cumulative, concurrent screen exposure across multiple screen types and are not able to confirm the identity of
user (the same child or his/her parents). Research technologies, such as eye-tracking glasses, can be invasive
to children and are limited to the measurement of regions of selective visual focus. Currently, there is no effective
and minimally invasive tool that can be used to provide objective and accurate measurement of both sedentary
screen use and screen exposure across multiple screen types. This project seeks to develop a wearable device
and robust AI algorithms to provide objective and accurate screen time measurement for children. Aim 1 will
develop a minimally invasive device and computer vision methods to detect screen exposure patterns and
differentiate various screen type. Aim 2 will testify the design in a free-living environment on children. The
proposed work will provide an important new tool to objectively and comprehensively measure children's
cumulative and discrete free-living screen exposure in quantity and duration. We anticipate this technology will
serve as a universal screen-time measurement tool and benefit parents, preschool teachers, and interest groups
in their management and advocacy of child(ren)'s sedentary activities and media use. We also anticipate our
tools will help academic researchers, clinical psychologist, and consumer researchers via providing objective
measures in behavioral study and therapy.
项目摘要
过去十年中数字技术所有权的爆炸式增长导致屏幕急剧增加
暴露于儿童。在美国,超过95%的有孩子的家庭拥有智能手机、电视,
桌面显示器,这引起了越来越多的关注屏幕对儿童健康的影响。
过度的屏幕暴露与眼部问题、睡眠障碍、肥胖症的增加密切相关,
以及儿童认知障碍。由于这些问题,世界卫生组织(WHO)
最近(2019年4月)建议2至4岁的儿童应少于1小时的久坐屏幕
每天的时间。然而,研究中的实际屏幕时间与父母控制之间存在证据差距
和测量工具的评估。现有的评估屏幕暴露的方法缺乏结构
有效性,因为它们严重依赖于自我报告,智能手机应用程序或研究技术(例如眼睛,
跟踪眼镜)。自我报告容易产生报告偏差。智能手机应用缺乏测量能力
多个屏幕类型的累积、同时屏幕暴露,并且无法确认
用户(同一个孩子或其父母)。研究技术,如眼动追踪眼镜,可能是侵入性的
对儿童来说,仅限于测量选择性视觉焦点的区域。目前,没有有效的
和微创工具,可用于提供客观和准确的测量,
屏幕使用和屏幕曝光跨多种屏幕类型。该项目旨在开发一种可穿戴设备,
和强大的AI算法,为儿童提供客观准确的屏幕时间测量。目标1将
开发微创设备和计算机视觉方法来检测屏幕曝光模式,
区分各种屏幕类型。目标2将在一个自由的生活环境中验证儿童的设计。的
拟议的工作将提供一个重要的新工具,客观和全面地衡量儿童的
在数量和持续时间上的累积和离散的自由生活屏幕曝光。我们预计这项技术将
作为一种通用的屏幕时间测量工具,并使家长、幼儿教师和兴趣小组受益
在他们管理和倡导儿童久坐活动和媒体使用方面。我们还预计我们的
工具将帮助学术研究人员,临床心理学家和消费者研究人员通过提供客观的
行为研究和治疗的措施。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Automated player identification and indexing using two-stage deep learning network.
- DOI:10.1038/s41598-023-36657-5
- 发表时间:2023-06-20
- 期刊:
- 影响因子:4.6
- 作者:
- 通讯作者:
Non-Invasive Screen Exposure Time Assessment Using Wearable Sensor and Object Detection.
- DOI:10.1109/embc48229.2022.9871903
- 发表时间:2022-07-01
- 期刊:
- 影响因子:0
- 作者:Li, Xueshen;Holiday, Steven;Gan, Yu
- 通讯作者:Gan, Yu
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