Research Resource for Complex Physiologic Signals

复杂生理信号的研究资源

• 批准号: 7884578
• 负责人: Ary Louis Goldberger
• 金额: $ 73.56万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7884578
• 关键词: Aging; Algorithms; Apnea; Archives; Arrhythmia; Basic Science; Biotechnology; Cardiopulmonary; Clinical; Clinical Research; Complex; Computer software; Congestive Heart Failure; Data; Data Analyses; Databases; Detection; Diagnostic; Elderly; Evaluation; Event; Gait abnormality; Infant; Libraries; Life; Medicine; Methods; Mission; Nonlinear Dynamics; Parkinson Disease; Patients; Physiological; Process; Public Health; Research; Research Project Grants; Research Support; Resources; Series; Signal Transduction; Sleep Apnea Syndromes; Students; Techniques; base; computerized data processing; digital; falls; investigator training; multidisciplinary; novel; open source; prognostic; relating to nervous system; simulation; sudden cardiac death; tool; web site

The NIH/NCRR Research Resource for Complex Physiologic Signals was established in September. 1999, in order to accelerate research progress and to stimulate new basic and clinical studies of biomedical signals. This competitive ¿enewal request proposes to enhance and expand the components of this multidisciplinary Resource, including: 3hysioBank -- a large and growing archive of well-characterized digital recordings of physiologic signals and related data currently includes about 40 databases of cardiopulmonary, neural and other biomedical signals from healthy subjects and from patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, Parkinson's disease, sleep apnea, and aging. Core and collaborative research supporting this component develop new databases and specialized software to assist in this process. hysioToolkit -- a large and growing library of open source software for physiologic signal processing and analysis, detection of physiologically significant events using both classical techniques and novel methods based on statistical shysics and nonlinear dynamics, interactive display and characterization of signals, creation of new databases, simulation of physiologic and other signals, evaluation and comparison of analysis methods, and analysis of complex . orocesses. A unifying theme of research projects that contribute software to PhysioToolkit is the extraction of hidden information from biomedical signals, information that may have diagnostic or prognostic value in medicine, or explanatory or predictive power in basic research. PhysioNet -- the Resource's web site (www.physionet.org)provides free access to PhysioBank and PhysioToolkit, and facilities for discussion and cooperative analysis of data and .algorithms. PhysioNet offers a growing set of tutorials to assist in training investigators, clinicians and students in complex signal analysis. PhysioNet also hosts a highly successful series of open challenges that focus research efforts and promote rapid progress on important basic and clinical research questions. We also propose to develop new data analysis and archival biotechnology tools in support of the missions of the NCRR's General Clinical Research Centers, and to expand our core and collaborative research directed at a wide range of basic and clinical problems, including infant apnea and sleep disordered breathing, gait disorders and falls in elders and those with Parkinson's disease, and life-threatening cardiac arrhythmias.

NIH/NCRR研究资源用于复杂的生理信号。 1999年，为了 加速研究进步，并刺激生物医学信号的新基本和临床研究。这种竞争力 Enewal请求提案，以增强和扩展该多学科资源的组成部分，包括： 3Hysiobank-一个庞大而越来越多的生理信号数字记录的档案 目前的数据包括来自健康的大约40个数据库的心肺，神经和其他生物医学信号 受试者和具有多种疾病具有重大公共卫生影响的患者，包括突然心脏 死亡，充血性心力衰竭，帕金森氏病，睡眠呼吸暂停和衰老。核心与协作研究 支持此组件开发新数据库和专业软件来协助此过程。 HysiotoolKit-一个大型且不断增长的开源软件库，用于物理信号处理和分析， 使用经典技术和基于统计的新方法检测物理上重要的事件 层次和非线性动态，信号的交互式显示和表征，创建新数据库， 生理和其他信号的模拟，分析方法的评估和比较以及复杂分析。 orcesses。研究项目的一个统一主题，将软件贡献给PhysiotoolKit的主题是提取隐藏的主题 来自生物医学信号的信息，可能具有诊断或预后价值的信息，或 基础研究中的剥夺或预测能力。 Physionet-资源的网站（www.physionet.org）可免费访问Physiobank和PhysiotoolKit，以及 讨论和合作分析数据和.algorithms的设施。 Physionet提供了越来越多的教程 协助培训调查人员，临床医生和学生进行复杂的信号分析。 Physionet还具有高度 成功的一系列开放挑战，这些挑战集中于研究工作，并在重要的基础上促进快速进步 临床研究问题。 我们还建议开发新的数据分析和档案生物技术工具，以支持任务 NCRR的一般临床研究中心，扩大我们的核心和协作研究，针对广泛 基本和临床问题的范围，包括婴儿呼吸暂停和睡眠失调，呼吸，疾病并陷入困境 长老和患有帕金森氏病的人，以及威胁生命的心律不齐。