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中文摘要
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项目总结/摘要 拟议SBIR项目的目标是开发、实施和演示数字化 压力损伤监测(DPIM)系统,以降低医院获得性压力损伤(HAPI)的风险。 HAPI是公共卫生的常见、昂贵和严重问题。Ocuvera的DPIM系统将使用来自 三维视频处理和定制算法,以检测和预测危险的患者行为,以及 以自动化与HAPI相关的护士记录保存。算法将被完善、测试和定制, 与HAPI发展风险相关的不同微妙患者行为。Ocuvera将创建一个用户 接口,以自动记录保存和提供智能活动报告。从终端收集反馈- Ocuvera将把原型DPIM部署到当地的一家医院,在那里,数据将在一个小型的 在短期现场试验期间的患者数量。将从使用该系统的护理人员那里收集反馈, 确定其对HAPI护理的潜在影响。本I期研究期间收集的信息将告知 优化系统,并准备Ocuvera在第二阶段进行更大规模的临床试验。如果成功,这项研究 将显示Ocuvera作为一种创新技术的潜力,能够降低HAPI的风险, 提高护理标准,这是改善患者结局的重要机会, 医院和护理人员
英文摘要
Project Summary/Abstract The goal of the proposed SBIR project is to develop, implement, and demonstrate the feasibility of a Digital Pressure Injury Monitoring (DPIM) system to reduce the risk of Hospital-Acquired Pressure Injuries (HAPIs). HAPIs are a common, costly, and serious problem for public health. Ocuvera’s DPIM system will use data from three-dimensional video processing and custom algorithms to detect and predict risky patient behaviors as well as to automate nurse record keeping related to HAPIs. Algorithms will be refined, tested, and customized to different subtle patient behaviors that are related to risk of HAPI development. Ocuvera will create a user interface to automate record keeping and provide intelligent activity reports. To garner feedback from end- users, Ocuvera will deploy the prototype DPIM to a local hospital where data will be collected on a small number of patients during a short field test. Feedback will be gathered from nursing staff using the system to determine its potential impact on HAPI care. Information gathered during this Phase I study will inform refinement of the system and prepare Ocuvera for a larger clinical trial during Phase II. If successful, this study would show Ocuvera’s potential as an innovative technology with the ability to reduce risk of HAPIs and improve the standard of care, which represents a significant opportunity to improve outcomes for patients, hospitals, and nursing staff.
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Automated Video Monitoring Algorithm Development to Reduce Falls in Hospitals from Chair Exits - I-Corps Program
  • 批准号:
    10303495
  • 项目类别:
  • 资助金额:
    $5.2万
  • 财政年份:
    2020
  • 负责人:
    Lucas Sabalka
  • 依托单位:
Automated Video Monitoring Algorithm Development to Reduce Falls in Hospitals from Chair Exits
  • 批准号:
    10081180
  • 项目类别:
  • 资助金额:
    $15.0万
  • 财政年份:
    2020
  • 负责人:
    Lucas Sabalka
  • 依托单位:
海外基金