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中文摘要
翻译
项目摘要 目前尚无非侵入性颅内压评估的临床设备。过去的尝试已经 专注于识别可非侵入性测量但几乎没有解决的与ICP相关的信号 校准问题。在没有校准的情况下,最多只能推断出ICP趋势。然而, 非侵入性校准并不是微不足道的。通用校准将失败,因为个别患者需要不同的 校准以获得准确的结果。另一方面,使用简单的回归进行个性化 校准是不可行的,因为对于一名初治患者来说,不可能从一开始就获得非侵入性的颅内压。 侵入性颅内压监测仍然是一项标准的护理,可以利用这一点来持续增长 ICP、非侵入性信号和不同校准方程的数据库,例如,每个由一对侵入性信号建立 数据库中的ICP和非侵入性信号。然后通过从一组丰富的 校准方程是初诊患者的最佳选择。在这个项目中,我们将追求三个目标 导致了一种基于经颅多普勒的精确无创颅内压系统的开发。这些目标 包括:1)实施和验证实现准确nICP所需的核心算法;2)测试是否估计 Nicp对超声探头位置的变化很敏感;3)测试所建议的 国家比较方案方法。 大规模的流行病学调查显示,只有大约58%的美国患者在进行ICP时进行了监测 指示进行监控。在欧洲患者中,这一比例较低(37%),在正在发展中的患者中,这一比例更低。 国家。建议的nicp方法不具有侵袭性cpc相关的高风险,不需要 现场神经外科专业知识,可以经济地部署和随时实践。因此,它的 潜在的影响是巨大的。
英文摘要
Project Summary No clinical device exists for noninvasive intracranial pressure (nICP) assessment. Past attempts have focused on identifying ICP-related signals that are noninvasively measureable, but have done little to address the calibration problem. Without calibration, only ICP trending can be inferred at the best. However, noninvasive calibration is not trivial. A universal calibration will fail because individual patients require different calibration to obtain accurate results. On the other hand, the use of plain regression for individualized calibration is infeasible because ICP cannot be obtained noninvasively for a de novo patient to begin with. Invasive ICP monitoring remains a standard of care and this can be leveraged to continuously grow a database of ICP, noninvasive signals, and different calibration equations, e.g., each built from a pair of invasive ICP and noninvasive signal in the database. Then nICP becomes feasible by selecting from a rich set of calibration equations the optimal choice for a de novo patient. In this project, we will pursue three aims that will lead to the development of an accurate noninvasive ICP system based on Transcranial Doppler. These aims are: 1) To implement and validate core algorithms needed for achieving accurate nICP; 2) To test if estimated nICP is sensitive to variations in ultrasound probe placement; 3) To test the generalizability of the proposed nICP approach. Large epidemiologic surveys reveal that ICP is monitored in only about 58% of US patients when ICP monitoring is indicated. It is a smaller percentage (37%) in European patients and even fewer in developing countries. The proposed nICP approach does not have the high risks associated with invasive ICP, requires no onsite neurosurgical expertise, and can be economically deployed and readily practiced. Therefore, its potential impact is enormous.
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Novel Algorithm and Data Strategies to detect and Predict atrial fibrillation for post-stroke patients (NADSP)
  • 批准号:
    10561108
  • 项目类别:
  • 资助金额:
    $70.06万
  • 财政年份:
    2023
  • 负责人:
    Xiao Hu
  • 依托单位:
Integrate Dynamic System Model and Machine Learning for Calibration-Free Noninvasive ICP
  • 批准号:
    10600239
  • 项目类别:
  • 资助金额:
    $53.16万
  • 财政年份:
    2020
  • 负责人:
    Xiao Hu
  • 依托单位:
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State Index
  • 批准号:
    10406378
  • 项目类别:
  • 资助金额:
    $62.06万
  • 财政年份:
    2020
  • 负责人:
    Xiao Hu
  • 依托单位:
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State Index
  • 批准号:
    10599717
  • 项目类别:
  • 资助金额:
    $58.03万
  • 财政年份:
    2020
  • 负责人:
    Xiao Hu
  • 依托单位:
海外基金