Systems and methods for collecting, analyzing, and sharing bio-signal and non-bio-signal data

A non-transitory computer readable medium storing machine executable instructions to configure a processor to execute a brainwave monitoring process comprising:

• receiving time-coded bio-signal data from each of a plurality of client computing devices capturing the bio-signal data for a plurality of users, the time-coded bio-signal data associated with a plurality of user identifiers for the plurality of users, each of the plurality of client computing devices in communication with at least one bio-signal sensor, wherein the plurality of client computing devices comprises a first client computing device capturing bio-signal data from a first user and a second client computing device capturing bio-signal data from a second user, wherein each of the plurality of client computing devices is executing a respective application of a plurality of applications, wherein the plurality of applications comprises a first application and a second application, wherein the first client computing device is executing the first application, and wherein the second client computing device is executing the second application;
• acquiring time-coded feature event data;
• extracting feature events from the time coded feature event data at feature event time codes, each feature event being a set of variables and corresponding values at one or more feature event time codes;
• automatically searching the feature events to identify patterns that are statistically significant, each pattern linked to a feature event time code of the one or more feature event time codes, the pattern representing user response associated with the feature event data at the feature event time code;
• using the feature event time codes linked to the patterns identified in the feature-events to label segments in the time-coded bio-signal data having bio-signal time-codes during a same time segment as the feature event time codes linked to the patterns;
• updating or creating pipelines associated with the plurality of applications using bio-signal features extracted from labelled segments of the time-coded bio-signal data from each of the plurality of client computing devices, the pipelines defined by pipeline parameters for predicting brain states, wherein the updating or creating pipelines comprises updating or creating the pipeline associated with the second application and the second user using bio-signal features extracted from labelled segments of the time-coded bio-signal data from the first user;
• determining and outputting a response classification of segments of time-coded bio-signal data from at least one user using a respective pipeline defined by the pipeline parameters, the response classification being an automatic prediction of a brain state at the bio-signal time codes, wherein the respective pipeline is associated with the at least one user and a respective application of the at least one user, wherein the determining and outputting the response classification of segments of time-coded bio-signal data from at least one user comprises determining and outputting a response classification of segments of time-coded bio-signal data from the second user using a respective pipeline defined by the pipeline parameters, wherein the respective pipeline is associated with the second application and the second user;
• providing the real-time biofeedback output as a visual indication of the response classification on a display device.

A brainwave monitoring server comprising:

• at least one computer processor in communication with a plurality of client computing devices capturing bio-signal data for a plurality of users over a communications network, each of the plurality of client computing devices in communication with at least one bio-signal sensor, wherein the plurality of client computing devices comprises a first client computing device capturing bio-signal data from a first user, and a second client computing device capturing bio-signal data from a second user, wherein each of the plurality of client computing devices is executing a respective application of a plurality of applications, wherein the plurality of applications comprises a first application and a second application, wherein the first client computing device is executing the first application, and wherein the second client computing device is executing the second application, the at least one computer processor configured to:
• receive time-coded bio-signal data from each of the plurality of client computing devices, the time-coded bio-signal data associated with a plurality of user identifiers for the plurality of users;
• acquire time-coded feature event data;
• extract feature events from the time coded feature event data at feature event time codes, each feature event being a set of variables and corresponding values at one or more feature event time codes;
• automatically search the feature events to identify patterns that are statistically significant, each pattern linked to a feature event time code of the one or more feature event time codes, the pattern representing user response associated with the feature event data at the feature event time code;
• using the feature event time codes linked to the patterns identified in the feature-events, label segments in the time-coded bio-signal data having bio-signal time-codes during a same time segment as the feature event time codes linked to the patterns;
• update or create pipelines associated with the plurality of applications using bio-signal features extracted from labelled segments of the time-coded bio-signal data from each of the plurality of client computing devices, the pipelines defined by parameters for predicting brain states, wherein the update or create pipelines comprises updating or creating the pipeline associated with the second application and the second user using bio-signal features extracted from labelled segments of the time-coded bio-signal data from the first user;
• determine and output a response classification of segments of time-coded bio-signal data from at least one user using a respective pipeline defined by the pipeline parameters, the response classification being an automatic prediction of a brain state at the bio-signal time codes, wherein the respective pipeline is associated with at least one user and a respective application of the at least one user, wherein the determine and output the response classification of segments of time-coded bio-signal data from at least one user comprises determining and outputting a response classification of segments of time-coded bio-signal data from the second user using a respective pipeline defined by the pipeline parameters, wherein the respective pipeline is associated with the second application and the second user;
• provide the real-time biofeedback output as an indication of the response classification.