System and method for providing and aggregating biosignals and action data

Abstract

A method and system for providing and aggregating bioelectrical signal data comprising: providing a stimulus configured to prompt an action in both a first user and a second user; at a first biosignal detector and a second biosignal detector, automatically collecting a first bioelectrical signal dataset from the first user as the first user performs the action and a second bioelectrical signal dataset from the second user as the second user performs the action; generating a first anonymized bioelectrical signal dataset from the first bioelectrical signal dataset and a second anonymized bioelectrical signal dataset from the second bioelectrical signal dataset; coupling the first and the second anonymized bioelectrical signal datasets with an action tag characterizing the action; and generating an analysis based upon the first the second anonymized bioelectrical signal datasets. An embodiment of the system comprises a biosignal detector and a processor configured to implement an embodiment of the method.

We claim: 
     
         1 . A system, comprising:
 a set of electroencephalogram (EEG) systems, each EEG system comprising a set of electrodes and an optical sensor, wherein each of the EEG systems is configured to sample a bioelectrical signal and an optical signal for a user in a set of users;   a processing system configured to:
 for each of the set of EEG systems:
 receive an optical signal and a bioelectrical signal from the EEG system; and 
 predict an action identifier based on the optical signal using machine learning techniques; and 
 
 generate a set of analyses for the set of users based on the action identifiers and the bioelectrical signals; and 
   a control system configured to modify a stimulus for the set of users based on the set of analyses.   
     
     
         2 . The system of  claim 1 , wherein the optical signals comprise motion signals. 
     
     
         3 . The system of  claim 2 , wherein the motion signals comprise at least one of body movement or eye movement. 
     
     
         4 . The system of  claim 1 , wherein, for each of the set of EEG systems, the optical signal comprises visual information, wherein the action identifier is predicted based on objects isolated in the corresponding visual information using the machine learning techniques. 
     
     
         5 . The system of  claim 1 , wherein the set of analyses for the set of users comprises a trend analysis. 
     
     
         6 . The system of  claim 1 , wherein the processing system further comprises a data storage system configured to aggregate and store the bioelectrical signals, wherein the set of analyses is generated based on the aggregated bioelectrical signals. 
     
     
         7 . The system of  claim 6 , wherein, for each of the set of EEG systems, the action identifier is associated with a time window, wherein the bioelectrical signal is sampled within the time window. 
     
     
         8 . The system of  claim 6 , wherein the set of analyses is based on anonymized aggregated bioelectrical signal datasets. 
     
     
         9 . The system of  claim 1 , wherein the control system is configured to, for each of the set of EEG systems, provide a stimulus configured to prompt a user action, wherein the action identifier is associated with the user action. 
     
     
         10 . The system of  claim 1 , wherein each EEG system further comprises a microphone configured to sample an audio signal, wherein, for each of the set of EEG systems, the action identifier is further based on an audio signal received from the corresponding EEG system. 
     
     
         11 . A system, comprising:
 a set of electroencephalogram (EEG) systems, each EEG system comprising a set of electrodes and an optical sensor, wherein each of the EEG systems is configured to sample a bioelectrical signal and an optical signal for a user in a set of users; and   a processing system configured to:
 for each of the set of users:
 provide a stimulus configured to prompt a user action; 
 receive a bioelectrical signal and an optical signal from the corresponding EEG system; and 
 determine an action identifier associated with the user action based on the optical signal; and 
 
 generate a set of analyses for the set of users based on the action identifiers and bioelectrical signals, wherein the set of analyses is used to determine a modified stimulus for a target user. 
   
     
     
         12 . The system of  claim 11 , wherein the set of users are associated with a demographic, wherein the set of analyses comprises a characterization of the demographic, wherein the target user is associated with the demographic. 
     
     
         13 . The system of  claim 12 , wherein the characterization of the demographic comprises comparisons between the set of users. 
     
     
         14 . The system of  claim 11 , wherein generating the set of analyses comprises determining subsets of the set of users based on the action identifiers and the bioelectrical signals. 
     
     
         15 . The system of  claim 11 , wherein the set of analyses comprises a comparison between the bioelectrical signals for the set of users and a bioelectrical signal received from an EEG system associated with the target user. 
     
     
         16 . The system of  claim 11 , wherein, for each of the set of users, the stimulus comprises marketing content. 
     
     
         17 . The system of  claim 11 , wherein, for each of the set of users, a timestamp for the bioelectrical signal is associated with the stimulus. 
     
     
         18 . The system of  claim 11 , wherein the processing system further comprises a data storage system configured to aggregate and store the bioelectrical signals, wherein the set of analyses is generated based on the aggregated bioelectrical signals. 
     
     
         19 . The system of  claim 18 , wherein, for each of the set of users, the action identifier is associated with a time window, wherein the bioelectrical signal is sampled within the time window. 
     
     
         20 . The system of  claim 18 , wherein the set of analyses is based on anonymized bioelectrical signal datasets.