{"search_session":{},"preferences":{"l":"es","queryLanguage":"es"},"patentId":"006-095-476-214-876","frontPageModel":{"patentViewModel":{"ref":{"entityRefType":"PATENT","entityRefId":"006-095-476-214-876"},"entityMetadata":{"linkedIds":{"empty":true},"tags":[],"collections":[{"id":10810,"type":"PATENT","title":"University of Florida - Patent Portfolio","description":"","access":"OPEN_ACCESS","displayAvatar":true,"attested":false,"itemCount":12320,"tags":[],"user":{"id":91044780,"username":"Cambialens","firstName":"","lastName":"","created":"2015-05-04T00:55:26.000Z","displayName":"Cambialens","preferences":"{\"usage\":\"public\",\"beta\":false}","accountType":"PERSONAL","isOauthOnly":false},"notes":[{"id":8273,"type":"COLLECTION","user":{"id":91044780,"username":"Cambialens","firstName":"","lastName":"","created":"2015-05-04T00:55:26.000Z","displayName":"Cambialens","preferences":"{\"usage\":\"public\",\"beta\":false}","accountType":"PERSONAL","isOauthOnly":false},"text":"
Search Applicants and Owners separately: \"Univ* Florida\"
Select more for logical variants. Add to collection. Select all patents in the collection and expand by simple families. Add to collection. Total patents: 1000+
Search Applicants and Owners separately: \"Univ* Florida\"
Select more for logical variants. Add to collection. Select all patents in the collection and expand by simple families. Add to collection. Total patents: 1000+
obtaining a plurality of electroencephalogram (EEG) signals from a plurality of sensors positioned about a scalp of a subject;\n
conditioning data from the plurality of EEG signals to remove artifacts;\n
generating a cerebral network model based at least in part upon the conditioned EEG signal data;\n
determining network features based upon the cerebral network model; and\n
determining a cerebral condition of the subject based at least in part upon the network features."],"number":1,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, further comprising determining EEG signal features from the conditioned EEG signal data, wherein the cerebral condition is base at least in part upon the EEG signal features and the network features."],"number":2,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 2, wherein the cerebral network model is generated based at least in part upon the determined EEG signal features."],"number":3,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, wherein the removed artifacts include eye movement artifacts and muscle movement artifacts."],"number":4,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, wherein the removed artifacts include sensor related artifacts."],"number":5,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, wherein generating the cerebral network model comprises:\n
generating a weighted graph based upon EEG signal features determined from the conditioned EEG signal data; and\n
converting the weighted graph to a binary graph based upon a predefined threshold."],"number":6,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, wherein determine network features comprises determining global network characteristics."],"number":7,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, wherein determine network features comprises identifying hubs of the cerebral network model."],"number":8,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, wherein determining the cerebral condition of the subject comprises determining a location of an abnormal condition."],"number":9,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 1, wherein determining the cerebral condition of the subject comprises determining a severity of an abnormal condition."],"number":10,"annotation":false,"title":false,"claim":true},{"lines":["A method for cerebral diagnosis, comprising:\n
positioning a plurality of electroencephalogram (EEG) sensors about a scalp of a subject:\n
determining a recording condition for each of the plurality of EEG sensors based upon predefined sensor criteria;\n
in response to an unacceptable recording condition for at least one of the plurality of EEG sensors based upon the predefined sensor criteria, providing an indication of the EEG sensor corresponding to the unacceptable recording condition and provide procedures to correct the unacceptable recording condition."],"number":11,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 11, further comprising in response to acceptable recording conditions for the plurality of EEG sensors based upon the predefined sensor criteria, obtaining a plurality of EEG signals from the plurality of EEG sensors."],"number":12,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 12, further comprising amplification and filtering of the obtained plurality of EEG signals."],"number":13,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 12, further comprising sampling the obtained plurality of EEG signals to obtain digital EEG data."],"number":14,"annotation":false,"title":false,"claim":true},{"lines":["The method of claim 14, wherein the digital EEG data is stored in memory."],"number":15,"annotation":false,"title":false,"claim":true},{"lines":["A system for cerebral diagnosis, comprising:\n
an electroencephalogram (EEG) recording module configured to acquire signals from a plurality of sensors positioned about a scalp of a subject;\n
a signal conditioning module configured to condition EEG signal data from the plurality of EEG signals;\n
a signal analysis module configured to determine EEG signal features and cerebral network features based at least in part upon the conditioned EEG signal data; and\n
a condition classification module configured to determine a cerebral condition of the subject based at least in part upon the determined features."],"number":16,"annotation":false,"title":false,"claim":true},{"lines":["The system of claim 16, further comprising an electrode application module configured to verify a recording condition of each of the plurality of sensors based upon predefined sensor criteria."],"number":17,"annotation":false,"title":false,"claim":true},{"lines":["The system of claim 16, wherein the signal conditioning module is configured to remove artifacts associated with movement of the subject from the EEG signal data."],"number":18,"annotation":false,"title":false,"claim":true},{"lines":["The system of claim 16, wherein the signal analysis module is configured to generate generating a cerebral network model based at least in part upon the conditioned EEG signal data."],"number":19,"annotation":false,"title":false,"claim":true},{"lines":["The system of claim 16, wherein the condition classification module is configured to identify location and severity of an abnormal condition."],"number":20,"annotation":false,"title":false,"claim":true}]}},"filters":{"npl":[],"notNpl":[],"applicant":[],"notApplicant":[],"inventor":[],"notInventor":[],"owner":[],"notOwner":[],"tags":[],"dates":[],"types":[],"notTypes":[],"j":[],"notJ":[],"fj":[],"notFj":[],"classIpcr":[],"notClassIpcr":[],"classNat":[],"notClassNat":[],"classCpc":[],"notClassCpc":[],"so":[],"notSo":[],"sat":[]},"sequenceFilters":{"s":"SEQIDNO","d":"ASCENDING","p":0,"n":10,"sp":[],"si":[],"len":[],"t":[],"loc":[]}}