DEVELOPMENT OF A VIDEO-BASED PERSONAL PROTECTIVE EQUIPMENT MONITORING SYSTEM
基于视频的个人防护装备监控系统的开发
基本信息
- 批准号:10644164
- 负责人:
- 金额:$ 65.72万
- 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:2022-09-01 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:Accident and Emergency departmentAddressAdherenceAdoptedAerosolsAreaCOVID-19COVID-19 pandemicCOVID-19 riskCategoriesCenters for Disease Control and Prevention (U.S.)Cessation of lifeClinicalCognitiveComplexComputer AssistedComputer Vision SystemsComputersDataDetectionEngineeringEnsureEvaluationExposure toFeedbackFoundationsFutureGeneral PopulationGoalsGuidelinesHealth PersonnelHospitalsHumanIncidenceIndividualIndustrializationInfectionIntensive Care UnitsMachine LearningMasksMedicalMethodsMonitorOperating RoomsPatientsPatients&apos RoomsPerformancePhysiciansProceduresPublic HealthRecommendationResearchResearch PersonnelResourcesResuscitationRiskSARS-CoV-2 infectionSafetySystemTestingTimeTrainingVideo RecordingVirus DiseasesVisualWorkWorkloadWorkplacebaseclinical practicecomputer human interactiondeep learning modeldesignhigh riskhuman centered designhuman-in-the-loopimprovedinfection riskinnovationmachine learning methodmultidisciplinarypandemic diseasepersonal protective equipmenttransmission processviral transmissionward
项目摘要
PROJECT SUMMARY
During the COVID-19 pandemic, healthcare workers (HCWs) have had a more than 11-fold higher infection
risk than the general population. Several risk factors for COVID-19 infection among HCWs have been
identified, including the lack of personal protective equipment (PPE) and inadequate PPE use. Among these
factors, the inadequate use of PPE has been associated with a one-third higher risk of infection. Given the high
incidence of infection, there is a critical need to address the challenges of monitoring and promoting adherence
with appropriate PPE use among HCWs. The long-term goal of this research is to reduce workplace-acquired
infections in HCWs by improving adherence to appropriate PPE use in settings at high risk of transmission.
The overall objectives of this proposal are to design, implement, and test a system (Computer-Aided PPE
Nonadherence Monitoring and Detection—CAPPED) that (1) tracks the team’s PPE adherence using computer
vision and (2) highlights episodes of potential PPE nonadherence on a video-monitoring system. Our central
hypothesis is that continuous monitoring of PPE use by multiple HCWs is a complex, cognitively demanding,
and error-prone task unaddressed by current methods for monitoring PPE adherence. The rationale for this
proposal is that enhanced recognition of PPE nonadherence is a requirement for reducing transmissible
infections in HCWs. Guided by preliminary data, the central hypothesis will be tested by pursuing two specific
aims: (1) design and implement a computer vision system (CAPPED) for recognizing PPE nonadherence in a
dynamic, team-based setting, and (2) compare human performance during simulated resuscitations using
direct observation, basic video surveillance, and computer-aided monitoring (CAPPED system). For the first
Aim, machine learning approaches will be applied to recognize the type of nonadherent PPE (headwear,
eyewear, mask, gown, gloves) and the category of nonadherence (absent or inadequate). Under the second
Aim, a visual interface will be designed and evaluated for monitoring and spotlighting PPE nonadherence with
a human-in-the-loop. The proposed research is innovative because it addresses the challenges of
simultaneously identifying nonadherence with several types of PPE used by multiple individuals in a dynamic
setting. This proposed research is significant because it is expected to reduce infection transmission to HCWs
by tracking and eventually alerting them to nonadherent PPE use. The results of this research are expected to
positively impact the workplace safety of HCWs by addressing the limitations of current approaches to PPE
monitoring.
项目总结
项目成果
期刊论文数量(0)
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{{ truncateString('RANDALL S. BURD', 18)}}的其他基金
Development of a Video-based Personal Protective Equipment Monitoring System
基于视频的个人防护装备监控系统的开发
- 批准号:
10585548 - 财政年份:2023
- 资助金额:
$ 65.72万 - 项目类别:
Automatic Workflow Capture & Analysis for Improving Trauma Resuscitation Outcomes
自动工作流程捕获
- 批准号:
8761390 - 财政年份:2014
- 资助金额:
$ 65.72万 - 项目类别:
Intention-aware Recommender System for Improving Trauma Resuscitation Outcomes
用于改善创伤复苏结果的意图感知推荐系统
- 批准号:
10629162 - 财政年份:2014
- 资助金额:
$ 65.72万 - 项目类别:
Intention-aware Recommender System for Improving Trauma Resuscitation Outcomes
用于改善创伤复苏结果的意图感知推荐系统
- 批准号:
10386911 - 财政年份:2014
- 资助金额:
$ 65.72万 - 项目类别:
Intention-aware Recommender System for Improving Trauma Resuscitation Outcomes
用于改善创伤复苏结果的意图感知推荐系统
- 批准号:
10163257 - 财政年份:2014
- 资助金额:
$ 65.72万 - 项目类别:
Automatic Workflow Capture & Analysis for Improving Trauma Resuscitation Outcomes
自动工作流程捕获
- 批准号:
8902267 - 财政年份:2014
- 资助金额:
$ 65.72万 - 项目类别:
Automatic Workflow Capture & Analysis for Improving Trauma Resuscitation Outcomes
自动工作流程捕获
- 批准号:
9113070 - 财政年份:2014
- 资助金额:
$ 65.72万 - 项目类别:
A Paper-Digital Interface for Time-Critical Information Management
用于时间关键信息管理的纸质数字接口
- 批准号:
8386105 - 财政年份:2012
- 资助金额:
$ 65.72万 - 项目类别:
Improving Pediatric Trauma Triage Using High Dimensional Data Analysis
使用高维数据分析改进儿科创伤分诊
- 批准号:
8111093 - 财政年份:2010
- 资助金额:
$ 65.72万 - 项目类别:
Improving Pediatric Trauma Triage Using High Dimensional Data Analysis
使用高维数据分析改进儿科创伤分诊
- 批准号:
7642839 - 财政年份:2010
- 资助金额:
$ 65.72万 - 项目类别:
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