Methods for modeling neurological development and diagnosing a neurological impairment of a patient
AssigneeEmotiv Inc.
InventorsTan Le, Geoffrey Ross Mackellar
Life of this patent
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Abstract
One variation of a method for modeling neurological development includes: aggregating electroencephalography (EEG) data that comprise multiple EEG signals of each user in a set of users, EEG signals of each user recorded on multiple distinct dates, the set of users comprising a plurality of users of various known neurological statuses; identifying a synchronization pattern trend within the EEG data of the set of users; and correlating the synchronization pattern trend with neurological development within the set of users.
Claims21
A method for determining a predicted neurological development outcome of a first user, the method comprising:
- for each of a set of multiple users in a user base:
- at each of a set of discrete time points, at a neuroheadset of the user, recording a set of EEG signals;
- for each of the set of EEG signals, determining a synchronization pattern based on the EEG signal;
- determining a synchronization pattern trend based on the set of synchronization patterns;
- for the set of multiple users:
- organizing the set of synchronization pattern trends into a set of groups;
- assigning a tag to each of set of groups, the tag associated with a neurological development outcome;
- and
- determining a neurological development model for each of the set of groups, wherein the neurological development model is configured to determine a predicted neurological development outcome;
- for the first user:
- recording a second set of EEG signals at a second set of discrete time points, the second set of discrete points occurring after the first set of discrete time points, wherein each of the second set of EEG signals is recorded at a neuroheadset of the first user;
- determining a first user synchronization pattern trend based on the set of EEG signals;
- comparing the first user synchronization pattern trend with the set of neurological development models;
- determining a set of correlations based on comparing the first user synchronization pattern trend with the set of neurological development models;
- determining the predicted neurological development outcome based on the set of correlations;
- providing a notification to the first user at an application executing on a user device associated with the first user;
- receiving an input from the first user at the application;
- adding the first user synchronization pattern trend to a first group of the set of groups based on the input.
A method for determining a predicted neurological development outcome of a first user, the method comprising:
- for each of a set of multiple users in a user base:
- at each of a set of discrete time points, at a neuroheadset of the user, recording a set of EEG signals;
- for each of the set of EEG signals, determining a synchronization pattern based on the EEG signal;
- determining a synchronization pattern trend based on the set of synchronization patterns;
- for the set of multiple users:
- organizing the set of synchronization pattern trends into a set of groups;
- assigning a tag to each of set of groups, the tag associated with a neurological development outcome;
- and
- determining a neurological development model for each of the set of groups, wherein the neurological development model is configured to determine a predicted neurological development outcome;
- for the first user:
- recording a second set of EEG signals at a second set of discrete time points, the second set of discrete points occurring after the first set of discrete time points, wherein each of the second set of EEG signals is recorded at a neuroheadset of the first user;
- determining a first user synchronization pattern trend based on the set of EEG signals;
- comparing the first user synchronization pattern trend with the set of neurological development models;
- determining a set of correlations based on comparing the first user synchronization pattern trend with the set of neurological development models;
- determining the predicted neurological development outcome based on the set of correlations.
Dependencies are inferred from the claim text.