Abstract: Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.

Abstract: Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.

Abstract: A computer implemented method for providing a graphical user interface for editing a design is described. A selection of a plurality of the design elements is received and a subset of the selected design elements is determined. Edit operations for the selected design elements are automatically selected based on the determined subset of the selected design elements. The design may be a table or include a table and the subset of selected design elements may be a category of borders forming the table.

Abstract: A wearable device has a flexible and extendable body configured to encircle a portion of a body of a user, an electronics module with a concave space between two ends, each end attachable to the flexible and extendable body with a flexible retention mount to allow rotation of the flexible and extendable body relative to the electronics module and to transfer tension force from the flexible and extendable body to the electronics module, and a bio-signal sensor disposed on the flexible and extendable body to contact at least part of the body of the user and to receive bio-signals from the user.

Abstract: Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.