Abstract: Techniques are disclosed for controlling a device's operation based on an inferred state. More specifically, at each of a set of time points, execution of an application at an electronic device is detected. For each detected execution, an application-usage variable is determined. One or more aggregated metrics are generated based on aggregation of at least some of the application-usage variables. Based on the one or more aggregated metrics, a state identifier is identified that corresponds to an inferred state of a user of the electronic device. A device-operation identifier is retrieved that is associated with the state identifier. A device operation is performed associated with the device-operation identifier.

Abstract: A digital platform for aggregating ad campaign data relating to one or more ad campaigns that is configured to allow users to generate customized data sets and perform user-customized operations on those data sets. The platform enables users to create and perform these operations on data from various sources through use of standardized data formats that is applied to the data retrieved from such sources.

Abstract: Techniques are disclosed for controlling a device's operation based on an inferred state. More specifically, at each of a set of time points, execution of an application at an electronic device is detected. For each detected execution, an application-usage variable is determined. One or more aggregated metrics are generated based on aggregation of at least some of the application-usage variables. Based on the one or more aggregated metrics, a state identifier is identified that corresponds to an inferred state of a user of the electronic device. A device-operation identifier is retrieved that is associated with the state identifier. A device operation is performed associated with the device-operation identifier.

Abstract: Provided is an implantable medical device for predicting and treating electrical disturbances in tissue. The medical device includes an implantable telemetry unit (ITU), and an implantable leads assembly including a first and a second electrode implanted in the tissue. A processor of the ITU is configured to perform training by receiving electrical signals input to the electrode circuit, parsing the electrical signals into dynamic event states using Bayesian Non-Parametric Markov Switching, and modeling each event state as a multi-dimensional probability distribution. The processor of the ITU is further configured to perform analysis of the electrical signals and therapy to the tissue by applying other electrical signals to the multi-dimensional distribution to predict future electrical disturbances in the tissue, and controlling the electrode circuit to apply an electrical therapy signal to the first and second electrodes to mitigate effects of the future electrical disturbances in the tissue.

Abstract: Provided is an implantable medical device for predicting and treating electrical disturbances in tissue. The medical device includes an implantable telemetry unit (ITU), and an implantable leads assembly including a first and a second electrode implanted in the tissue. A processor of the ITU is configured to perform training by receiving electrical signals input to the electrode circuit, parsing the electrical signals into dynamic event states using Bayesian Non-Parametric Markov Switching, and modeling each event state as a multi-dimensional probability distribution. The processor of the ITU is further configured to perform analysis of the electrical signals and therapy to the tissue by applying other electrical signals to the multi-dimensional distribution to predict future electrical disturbances in the tissue, and controlling the electrode circuit to apply an electrical therapy signal to the first and second electrodes to mitigate effects of the future electrical disturbances in the tissue.