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Method for amplifying abnormal pattern signal in observed brain activity of a subject for diagnosis or treatment

ActiveUS8538512B1Stop and abate seizureImprove detection accuracyElectroencephalographyElectrotherapySeizure detectionClinical scenario
The present invention relates to a brain dysfunction and seizure detector monitor and system, and a method of detecting brain dysfunction and/or seizure of a subject. The various embodiments of the system of the present invention were developed for the brain activity and preferably EEG monitoring of a single patient or multiple patients. Preferably, the system or monitor of the present invention also includes one or more seizure detection algorithms. The analysis method is specifically optimized to amplify abnormal brain activity and minimize normal background activity. This analysis yields a seizure index whose value is directly related to the current presence of ictal activity in the signal. In addition, a seizure probability index based on historical values of the aforementioned seizure index, is derived for diagnostic purposes. The seizure probability index quantifies the probability that the patient has exhibited abnormal brain activity since the beginning of the recording. The real-time seizure index, and the historical seizure probability index, can be used in the context of an emergency and/or clinical situation to assess the status and well being of a patient's brain, or can be used to automatically administer treatment to stop the seizure before clinical signs appear.
Owner:NEUROWAVE SYST

Chlorophyll calculating method based on remote-sensing images and water ecological model

The invention discloses a chlorophyll calculating method based on remote-sensing images and a water ecological model. The method comprises the steps of 1, based on remote-sensing image data, data preprocessing like radiometric calibration, atmospheric correction and image cropping and fusing is conducted; 2, a remote-sensing water quality inversion model is constructed, and respective inversion ofindexes like water temperature and chlorophyll concentration is achieved; 3, various index concentrations and future weather change which are obtained through inversion of the remote-sensing images are regarded as input conditions of the water ecological model, and the chlorophyll concentration dynamic change process of a water area environment is simulated within a future duration caused by change like nutritive substance conversion and algae growth and death under a future weather change condition. The chlorophyll calculating method is applicable to water environment monitoring and predicting, and has popularity and high calculation precision, chlorophyll concentration prediction and simulation of a large area of a drainage basin are achieved in real time under the condition of the limited monitoring site, and an integrated chlorophyll concentration predicting system integrating the remote-sensing images and the water ecological model can be formed.
Owner:WUHAN UNIV
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