Patent application number | Description | Published |
20090264786 | System and Method For Signal Denoising Using Independent Component Analysis and Fractal Dimension Estimation - A system and method of signal denoising using Independent Component Analysis (ICA) and fractal dimension analysis of the signal components in the ICA domain is described. The signal components with fractal dimensions higher than a pre-determined threshold are automatically attenuated or canceled in order to alleviate the noise in the signal. The denoised signal is reconstructed using inverse ICA transform of the signal components. | 10-22-2009 |
20100191139 | Method and Device for Probabilistic Objective Assessment of Brain Function - A method and apparatus for providing objective assessment of the brain state of a subject using a field portable device. The method includes placing an electrode set coupled to a handheld base unit on the subject's head, acquiring electrical brain signals from the subject through the electrode set, processing the acquired electrical brain signals using a feature extraction algorithm, classifying the extracted features into brain states, computing brain abnormality indices reflecting the probability of correct classification of brain state, and graphically displaying the classification result and the abnormality indices on the handheld base unit. | 07-29-2010 |
20110038515 | DEVELOPMENT OF FULLY-AUTOMATED CLASSIFIER BUILDERS FOR NEURODIAGNOSTIC APPLICATIONS - Methods for constructing classifiers for binary classification of quantitative brain electrical activity data is described. The classifier building methods are based on the application of one or more evolutionary algorithms. In one embodiment, the evolutionary algorithm used is a genetic algorithm. In another embodiment, the evolutionary algorithm used is a modified Random Mutation Hill Climbing algorithm. In yet another embodiment, a combination of a genetic algorithm and a modified Random Mutation Hill Climbing algorithm is used for building a classifier. The classifier building methods are fully automated, and are adapted to generate classifiers (for example, Linear Discriminant Functions) with high sensitivity, specificity and classification accuracy. | 02-17-2011 |
20110224569 | METHOD AND DEVICE FOR REMOVING EEG ARTIFACTS - Systems and methods for automatically identifying segments of EEG signals or other brain electrical activity signals that contain artifacts, and/or editing the signals to remove segments that include artifacts | 09-15-2011 |
20130109995 | METHOD OF BUILDING CLASSIFIERS FOR REAL-TIME CLASSIFICATION OF NEUROLOGICAL STATES | 05-02-2013 |
20130211224 | METHOD AND DEVICE FOR REMOVING EEG ARTIFACTS - Systems and methods for automatically identifying segments of EEG signals or other brain electrical activity signals that contain artifacts, and/or editing the signals to remove segments that include artifacts | 08-15-2013 |
20140289172 | METHOD AND DEVICE FOR MULTIMODAL NEUROLOGICAL EVALUATION - A method of building classifiers for neurological assessment is described. The method comprises the steps of extracting quantitative features from a plurality of clinical features, and selecting a subset of features from the extracted pool of features to construct binary classifiers. A device for performing point-of-care neurological assessment using clinical features is also described. | 09-25-2014 |
20160132654 | METHOD AND DEVICE FOR MULTIMODAL NEUROLOGICAL EVALUATION - A method of building classifiers for neurological assessment is described. The method comprises the steps of extracting quantitative features from a plurality of clinical features, and selecting a subset of features from the extracted pool of features to construct binary classifiers. A device for performing point-of-care neurological assessment using clinical features is also described. | 05-12-2016 |