Emboli Classification System to Reduce Brain Injury

The brain is at risk of serious cerebrovascular insult during the 350,000 cardiopulmonary bypass superformed annually in the USA. There is strong clinical evidence that over two-thirds of the patientneuropsychologic postoperative deficits caused by emboli passing to the brain during surgery. Continultrasound equipment can detect emboli, but can not provide for classification of emboli. A broadbanultrasound device can provide improved structural information. Artificial neural network and expertperform the broadband echo classification. ORINCON is uniquely qualified to develop this system becasuccessfully applied similar technology to classification problems in biomedical diagnostics, underwdetection. Phase I research will demonstrate the feasibility of automated emboli classification. Ourdevelopment of an accurate, low cost, real-time, automated ultrasonic, carotid monitoring system forcan continuously detect and classify emboli. This effort is collaborative, involving ORINCON Corporaapplication of intelligent systems technology to acoustic signal classification and the Bowman Grayleader in emboli-related research.