Portable Non-Invasive Acoustic Identification of Stroke

便携式非侵入性中风声学识别

• 批准号: 6668565
• 负责人: JOHN Milton SEWELL
• 金额: $ 35.65万
• 依托单位: ACTIVE SIGNAL TECHNOLOGIES, INC.
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-30 至 2004-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6668565
• 关键词: biomedical equipment development; cerebral hemorrhage; cerebral ischemia /hypoxia; cerebrovascular disorder diagnosis; computer data analysis; computer program /software; diagnosis design /evaluation; human subject; noninvasive diagnosis; patient oriented research; portable biomedical equipment; rapid diagnosis; stroke

DESCRIPTION (provided by applicant): Active Signal Technologies, in partnership with the Brain Attack Team of the University of Maryland Medical Center, proposes to refine and test a novel portable, non-invasive system that will enable rapid identification of stroke. Approximately 750,000 people suffer a stroke each year and over 80% of these are ischemic. Yet only 1% of this number receives medical treatment such as TPA that is known to dissolve clots and promote favorable outcome if administered within 3 hours of onset. Among the many causes of this serious health and ultimately economic problem is the inability to rapidly differentiate ischemic from hemorrhagic strokes to allow intervention. The device is a small non-invasive system that measures the acoustic signature of the brain and compares it with the patient's arterial waveform. Active Signal will add code to calculate those signal features identified in Phase I as indicative of the patient's stroke condition, and the team will clinically test on 200 patients the hypotheses for stroke identification determined in Phase I. The system will be miniaturized for EMS units to use at the scene of injury. This would significantly increase the percentage of ischemic stroke patients who would receive time-sensitive therapies, reducing disability and medical costs.

描述（由申请人提供）：主动信号技术与马里兰大学医学中心的大脑攻击团队合作，建议完善和测试一种新型的便携式，无创系统，该系统将可以快速识别中风。每年大约有75万人遭受中风，其中80％以上是缺血性的。然而，该数字中只有1％接受医学治疗，例如TPA，如果在发病后3小时内进行给药，可以溶解凝块并促进良好的结果。在这种严重健康和最终经济问题的众多原因中，无法快速区分缺血与出血性中风以允许干预。该设备是一个小的非侵入性系统，可测量大脑的声学特征，并将其与患者的动脉波形进行比较。主动信号将添加代码以计算I阶段中确定的那些信号特征，以指示患者的中风状况，并且该团队将对200名患者进行临床测试。在第1阶段确定的中风识别的假设。该系统将在损伤现场使用EMS单位进行小型化。这将大大增加接受时间敏感疗法，降低残疾和医疗费用的缺血性中风患者的百分比。