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US 12,667,300 B2Granted
EEG recording and analysis
AssigneeEpitel, Inc.
InventorsMichael K. Elwood, Mitchell A. Frankel, Mark J. Lehmkuhle, Jean M. Wheeler, Robert Lingstuyl, Erin M. West, Tyler D. McGrath
Life of this patent
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Abstract
One embodiment provides a method, including: obtaining EEG data from one or more single channel EEG sensor worn by a user; classifying, using a processor, the EEG data as one of nominal and abnormal; and providing an indication associated with a classification of the EEG data. Other embodiments are described and claimed.
Claims23
A method for detecting seizures using electroencephalogram (EEG) data, the method comprising:
- obtaining EEG data collected by a plurality of discrete wireless EEG sensors positioned on a scalp of a patient being evaluated;
- segmenting the EEG data into a plurality of EEG data segments;
- identifying probabilities of occurrence of a seizure in the plurality of EEG data segments;
- automatically identifying a discrete seizure event by evaluating the identified probabilities of a temporally sequential subset of the plurality of EEG data segments against one or more thresholds, wherein the subset includes multiple temporally sequential EEG data segments, and wherein a start and stop time of the discrete seizure event is determined;
- automatically creating a plurality of EEG channels from the EEG data, the plurality of EEG channels including a channel from each discrete wireless EEG sensor of the plurality of discrete wireless EEG sensors and additional channels determined by, for each discrete wireless EEG sensor, subtracting its corresponding EEG data from a corresponding EEG data of the remaining discrete wireless EEG sensors;
- and
- automatically annotating the EEG data with a graphical indicator that denotes the discrete seizure event,
- wherein the method is performed under control of at least one processor.
5 more elements
At least one non-transitory computer readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to:
- obtain electroencephalogram (EEG) data collected by a plurality of discrete wireless EEG sensors positioned on a scalp of a patient being evaluated;
- segment the EEG data into a plurality of EEG data segments;
- identify probabilities of occurrence of a seizure in the plurality of EEG data segments;
- automatically identify a discrete seizure event by evaluating the identified probabilities of a temporally sequential subset of the plurality of EEG data segments against one or more thresholds, wherein the subset includes multiple temporally sequential EEG data segments, and wherein a start and stop time of the discrete seizure event is determined;
- automatically create a plurality of EEG channels from the EEG data, the plurality of EEG channels including a channel from each discrete wireless EEG sensor of the plurality of discrete wireless EEG sensors and additional channels determined by, for each discrete wireless EEG sensor, subtracting its corresponding EEG data from a corresponding EEG data of the remaining discrete wireless EEG sensors;
- and
- automatically annotate the EEG data with a graphical indicator that denotes the discrete seizure event.
4 more elements
A system for detecting seizures using electroencephalogram (EEG) data, the system comprising:
- a plurality of discrete wireless EEG sensors configured to be positioned on a scalp of a patient being evaluated;
- and
- at least one non-transitory computer readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to:
- obtain EEG data collected by the plurality of discrete wireless EEG sensors;
- segment the EEG data into a plurality of EEG data segments;
- identify probabilities of occurrence of a seizure in the plurality of EEG data segments;
- automatically identify a discrete seizure event by evaluating the identified probabilities of a temporally sequential subset of the plurality of EEG data segments against one or more thresholds, wherein the subset includes multiple temporally sequential EEG data segments, and wherein a start and stop time of the discrete seizure event is determined;
- automatically create a plurality of EEG channels from the EEG data, the plurality of EEG channels including a channel from each discrete wireless EEG sensor of the plurality of discrete wireless EEG sensors and additional channels determined by, for each discrete wireless EEG sensor, subtracting its corresponding EEG data from a corresponding EEG data of the remaining discrete wireless EEG sensors;
- and
- automatically annotate the EEG data with a graphical indicator that denotes the discrete seizure event.
7 more elements
Dependencies are inferred from the claim text.