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INTRAOPERATIVE NEUROLOGICAL MONITOR (INM)

INTRAOPERATIVE NEUROLOGICAL MONITOR (INM)
术中神经监护仪 (INM)
批准号:
6210204
负责人:
Ananth Natarajan
金额:
$56.71万
依托单位国家:
美国
项目类别:
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-09-30 至 2002-08-31

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DESCRIPTION: (Verbatim from the Applicant's Abstract) The NINDS solicitation for proposals recognizes the great need for a technology to rapidly and continuously assess the state of the brain during surgery and in the critical care unit. We strongly agree with this sentiment. Our collaborative group has been studying somatosensory evoked potentials (SEPs) from a basic science viewpoint for the past decade. Two years ago, we set out to reduce the results of this work into a robust, easy to use clinical device for rapid, accurate detection of neurological injury. We are pleased to report that with the aid of our Phase I contract, we exceeded our stated Specific Aims and built a working prototype Intraoperative Neurological Monitor (INM) and demonstrated it at the NIH/NINDS. The device weights less than four pounds and features a touch sensitive color screen with an intuitive user-friendly graphical user interface. Additionally, it incorporates novel noise reduction and EP signal analysis algorithms and was validated in a series of experimental studies. We are very excited to submit this Phase II application with the intent of building the clinical grad INM. Our specific aims pay special attention to performance and outcome analyses as well as ease of use and noise immunity. We will further validate the device in a series of controlled animal studies as well during a clinical trial involving craniotomies and spinal cord surgeries. The device will not only be used in the OR, but also in follow-up in the Neurocritical Care Unit (NCCU). The results will be correlated with the clinical neurological exam as well as with other conventional methods of assessing neurological status. PROPOSED COMMERCIAL APPLICATION: We are optimistic that we will succeed in our ultimate goal: to incorporate innovative signal processing techniques for interpretation of evoked electrical activity in noisy environments into a robust, easy to use clinical device for rapid accurate detection of neurological injury.
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