EAGER/Collaborative Research: Sensing, Modeling and Optimization of Postoperative Heart Health Management

EAGER/合作研究:术后心脏健康管理的传感、建模和优化

基本信息

  • 批准号:
    1646664
  • 负责人:
  • 金额:
    $ 9.98万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-09-01 至 2019-08-31
  • 项目状态:
    已结题

项目摘要

Postoperative outcomes are critical to the quality of life of many patients. However, after discharge, there are currently few sensor-based decision support systems extending to home, workplace, and community. Postoperative care primarily depends on episodic follow-up visits and rare electrocardiograms. Very little has been done to continuously monitor clinical parameters of postoperative patients, estimate clinical status, and further help optimal management of postoperative recovery. This EArly-concept Grant for Exploratory Research (EAGER) award supports fundamental research to develop a collaborative sensing, statistical modeling and decision-making strategy for optimizing postoperative management of heart health. This research will help clinicians and patients leverage the fast development of sensing and mobile technology to achieve a substantial boost in smart postoperative management. As a result, this project will provide education on heart-healthy living and raise the awareness of smart health. In addition, realizing a better postoperative care will achieve a reduction in healthcare costs. A broader impact in education will be realized through new curriculum modules, training of healthcare professionals, and recruitment of under-represented students.In current practice, ad hoc strategies are widely used for managing postoperative risks. This award will make possible a new sensor-based, patient-centered management of heart health that can overcome several limitations of existing practices. In particular, it will empower clinicians and patients to (1) quantitatively measure the quality of life before and after cardiac procedures, (2) optimize postoperative cardiac care and decrease arrhythmia recurrences, and (3) improve lifestyle modifications and positively influence general postoperative outcomes. If successful, this research will lead to new data imputation algorithms to tackle uncertainty in patient-centered sensing, extract sensor-based biomarkers of cardiac risks, model the evolving dynamics of cardiac conditions, and optimize postoperative management under uncertainty. The success of this project will invoke a new "sensing-modeling-optimization" approach to theoretically formulate relationships connecting physiological signals from postoperative patients, useful information from analytical models with smart postoperative health management. Analytical methods and tools will be generally applicable to handle data veracity, feature extraction, risk prognostics, and process optimization in sensor-based monitoring and control of cardiovascular systems.
术后结果对许多患者的生活质量至关重要。然而,在出院后,目前很少有基于传感器的决策支持系统扩展到家庭、工作场所和社区。术后护理主要依赖于偶发性随访和罕见的心电图。对术后患者临床参数的持续监测、临床状态的评估以及对术后恢复的优化管理的研究很少。这项探索性研究(EAGER)早期概念奖支持基础研究,以开发协作传感、统计建模和决策策略,以优化心脏健康的术后管理。这项研究将帮助临床医生和患者利用快速发展的传感和移动技术,实现智能术后管理的实质性推动。因此,该项目将提供心脏健康生活的教育,并提高智能健康的意识。此外,实现更好的术后护理可以降低医疗成本。通过新的课程模块、培训保健专业人员和招收代表性不足的学生,将对教育产生更广泛的影响。在目前的实践中,特别策略被广泛用于管理术后风险。该奖项将使一种新的基于传感器的、以患者为中心的心脏健康管理成为可能,这种管理可以克服现有实践的几个限制。特别是,它将使临床医生和患者能够(1)定量测量心脏手术前后的生活质量,(2)优化术后心脏护理,减少心律失常复发,(3)改善生活方式的改变,并对一般术后结果产生积极影响。如果成功,该研究将产生新的数据输入算法,以解决以患者为中心的传感中的不确定性,提取基于传感器的心脏风险生物标志物,模拟心脏状况的演变动态,并优化不确定性下的术后管理。该项目的成功将引发一种新的“感知-建模-优化”方法,从理论上制定连接术后患者生理信号的关系,从分析模型中获得有用信息,以及智能术后健康管理。分析方法和工具将普遍适用于处理基于传感器的心血管系统监测和控制中的数据准确性,特征提取,风险预测和过程优化。

项目成果

期刊论文数量(12)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Improved Heart Rate Tracking Using Multiple Wrist-type Photoplethysmography during Physical Activities
A Novel Motion Artifact Removal Method via Joint Basis Pursuit Linear Program to Accurately Monitor Heart Rate
  • DOI:
    10.1109/jsen.2019.2927994
  • 发表时间:
    2019-11-01
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Koneshloo, Amirhossein;Du, Dongping
  • 通讯作者:
    Du, Dongping
Cardiac image segmentation using generalized polynomial chaos expansion and level set function
使用广义多项式混沌展开和水平集函数进行心脏图像分割
In-Silico Modeling of the Functional Role of Reduced Sialylation in Sodium and Potassium Channel Gating of Mouse Ventricular Myocytes
Heart Rate Monitoring During Physical Exercise From Photoplethysmography Using Neural Network
  • DOI:
    10.1109/lsens.2018.2878207
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    2.8
  • 作者:
    Lianning Zhu;Chen Kan;Yuncheng Du;D. Du
  • 通讯作者:
    Lianning Zhu;Chen Kan;Yuncheng Du;D. Du
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Dongping Du其他文献

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder
用于饮食失调、抑郁症和酒精使用障碍的诊断和风险预测的机器学习模型
  • DOI:
    10.21203/rs.3.rs-3777784/v1
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Desrivières;Zuo Zhang;Lauren Robinson;R. Whelan;L. Jollans;Zijian Wang;F. Nees;Congying Chu;Marina Bobou;Dongping Du;Ilinca Cristea;T. Banaschewski;G. Barker;A. Bokde;A. Grigis;Hugh Garavan;A. Heinz;Rudiger Bruhl;J. Martinot;M;E. Artiges;D. P. Orfanos;Luise Poustka;Sarah Hohmann;Sabina Millenet;J. Fröhner;Michael N. Smolka;N. Vaidya;H. Walter;J. Winterer;M. Broulidakis;B. V. van Noort;A. Stringaris;J. Penttilä;Y. Grimmer;Corinna Insensee;Andreas Becker;Yuning Zhang;Sinead King;J. Sinclair;Gunter Schumann;Ulrike Schmidt
  • 通讯作者:
    Ulrike Schmidt
The Effects of Fluid Hydration Status on the Accuracy of Ultrasound Muscle Measurement in Hemodialysis Patients
血液透析患者液体水合状态对超声肌肉测量准确性的影响
  • DOI:
    10.1053/j.jrn.2022.04.007
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dongsheng Cheng;Haiqing Luo;Shunrong Ren;Niansong Wang;Dongping Du
  • 通讯作者:
    Dongping Du
Embracing the informative missingness and silent gene in analyzing biologically diverse samples
在分析生物多样性样本时,接受信息缺失和沉默基因。
  • DOI:
    10.1038/s41598-024-78076-0
  • 发表时间:
    2024-11-16
  • 期刊:
  • 影响因子:
    3.900
  • 作者:
    Dongping Du;Saurabh Bhardwaj;Yingzhou Lu;Yizhi Wang;Sarah J. Parker;Zhen Zhang;Jennifer E. Van Eyk;Guoqiang Yu;Robert Clarke;David M. Herrington;Yue Wang
  • 通讯作者:
    Yue Wang
ABDS: a bioinformatics tool suite for analyzing biologically diverse samples
ABDS:用于分析生物多样性样本的生物信息学工具套件
  • DOI:
    10.21203/rs.3.rs-4419408/v1
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dongping Du;Saurabh Bhardwaj;Yingzhou Lu;Yizhi Wang;Sarah J. Parker;Zhen Zhang;Jennifer E. Van Eyk;Guoqiang Yu;Robert Clarke;David M. Herrington;Yue Wang
  • 通讯作者:
    Yue Wang
A novel approach to ultrasound-guided L3-4 thoracolumbar fascia injection for chronic pain after spine surgery: a prospective pilot study
  • DOI:
    10.1186/s12871-025-03046-6
  • 发表时间:
    2025-05-15
  • 期刊:
  • 影响因子:
    2.600
  • 作者:
    Yingying Lv;Junzhen Wu;Yongming Xu;Shaofeng Pu;Chen Li;Dongping Du
  • 通讯作者:
    Dongping Du

Dongping Du的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Dongping Du', 18)}}的其他基金

I-Corps: Postoperative Risk Prediction for Heart Failure Patients
I-Corps:心力衰竭患者的术后风险预测
  • 批准号:
    2230433
  • 财政年份:
    2022
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
Collaborative Research: Personalized Modeling, Monitoring and Control for Advancing Ventricular Assist Device Therapy in End-stage Heart Failure
合作研究:个性化建模、监测和控制,以推进心室辅助装置治疗终末期心力衰竭
  • 批准号:
    1728338
  • 财政年份:
    2017
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant

相似海外基金

Collaborative Research: EAGER: IMPRESS-U: Groundwater Resilience Assessment through iNtegrated Data Exploration for Ukraine (GRANDE-U)
合作研究:EAGER:IMPRESS-U:通过乌克兰综合数据探索进行地下水恢复力评估 (GRANDE-U)
  • 批准号:
    2409395
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
EAGER/Collaborative Research: An LLM-Powered Framework for G-Code Comprehension and Retrieval
EAGER/协作研究:LLM 支持的 G 代码理解和检索框架
  • 批准号:
    2347624
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
EAGER/Collaborative Research: Revealing the Physical Mechanisms Underlying the Extraordinary Stability of Flying Insects
EAGER/合作研究:揭示飞行昆虫非凡稳定性的物理机制
  • 批准号:
    2344215
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
Collaborative Research: EAGER: Designing Nanomaterials to Reveal the Mechanism of Single Nanoparticle Photoemission Intermittency
合作研究:EAGER:设计纳米材料揭示单纳米粒子光电发射间歇性机制
  • 批准号:
    2345581
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
Collaborative Research: EAGER: Designing Nanomaterials to Reveal the Mechanism of Single Nanoparticle Photoemission Intermittency
合作研究:EAGER:设计纳米材料揭示单纳米粒子光电发射间歇性机制
  • 批准号:
    2345582
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
Collaborative Research: EAGER: Designing Nanomaterials to Reveal the Mechanism of Single Nanoparticle Photoemission Intermittency
合作研究:EAGER:设计纳米材料揭示单纳米粒子光电发射间歇性机制
  • 批准号:
    2345583
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
Collaborative Research: EAGER: The next crisis for coral reefs is how to study vanishing coral species; AUVs equipped with AI may be the only tool for the job
合作研究:EAGER:珊瑚礁的下一个危机是如何研究正在消失的珊瑚物种;
  • 批准号:
    2333604
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
Collaborative Research: EAGER: Energy for persistent sensing of carbon dioxide under near shore waves.
合作研究:EAGER:近岸波浪下持续感知二氧化碳的能量。
  • 批准号:
    2339062
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
Collaborative Research: EAGER: The next crisis for coral reefs is how to study vanishing coral species; AUVs equipped with AI may be the only tool for the job
合作研究:EAGER:珊瑚礁的下一个危机是如何研究正在消失的珊瑚物种;
  • 批准号:
    2333603
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
EAGER/Collaborative Research: An LLM-Powered Framework for G-Code Comprehension and Retrieval
EAGER/协作研究:LLM 支持的 G 代码理解和检索框架
  • 批准号:
    2347623
  • 财政年份:
    2024
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了