SBIR-STTR Award

Alacron proposes to develop an automated low-to-moderate cost device for continuous real-time EEG monitoring. EEG monitoring is desirable in operating rooms and intensive care units for the purpose of rapid detection of changes in neurological function, thus permitting immediate intervention. EEG monitoring is also useful in the evaluation of certain patients with epilepsy and sleep disorders. Conventional paper EEG recording are excessively cumbersome and difficult for the non-electroencephalographer to interpret to be practical for use in continuous monitoring settings. Presently available EEG monitoring systems do not employ methods of EEG analysis adequate to unambiguously identifying significant EEG patterns and changes and to unambiguously distinguish them from artifact. Alacron proposed to develop an EEG monitoring system that will overcome the limitations of presently available systems by utilizing innovative computerized techniques, including parallel distributed processing (i.e., neural networks) and dedicated low cost hardware. In Phase II neural network software will be optimized and implemented on custom hardware. An extensive database of expert classified by experts will be collected and used to train the neural network

Alacron proposes to develop an automated low-to-moderate cost device for continuous real-time EEG monitoring. EEG monitoring is desirable in operating rooms and intensive care units for the purpose of rapid detection of changes in neurological function, thus permitting immediate intervention. EEG monitoring is also useful in the evaluation of certain patients with epilepsy and sleep disorders. Conventional paper EEG recording are excessively cumbersome and difficult for the non-electroencephalographer to interpret to be practical for use in continuous monitoring settings. Presently available EEG monitoring systems do not employ methods of EEG analysis adequate to unambiguously identifying significant EEG patterns and changes and to unambiguously distinguish them from artifact. Alacron proposed to develop an EEG monitoring system that will overcome the limitations of presently available systems by utilizing innovative computerized techniques, including parallel distributed processing (i.e., neural networks) and dedicated low cost hardware. In Phase II neural network software will be optimized and implemented on custom hardware. An extensive database of expert classified by experts will be collected and used to train the neural network.

Thesaurus Terms:
electroencephalography, patient monitoring device computer processing of clinical data human subject