Abstract: A method of using a sensor platform of a garment of a wearer in order to interact with a remote networked device using a plurality of sensed biometric data, the method comprising: receiving from the sensors a set of the plurality of biometric data; comparing the set to a data model including a plurality of model data parameters; determining whether said comparing indicates a need for a command to be sent to the remote networked device in order to effect a change in an operational characteristic of the networked device; sending the command to the networked device; receiving a further set of the plurality of biometric data; further comparing the further set to the data model; and determining whether said further comparing indicates a need for a further command to be sent to the remote networked device in order to further effect a change in an operational characteristic of the networked device.

Abstract: A method of using a sensor platform of a garment of a wearer in order to interact with a remote networked device using a plurality of sensed biometric data, the method comprising: receiving from the sensors a set of the plurality of biometric data; comparing the set to a data model including a plurality of model data parameters; determining whether said comparing indicates a need for a command to be sent to the remote networked device in order to effect a change in an operational characteristic of the networked device; sending the command to the networked device; receiving a further set of the plurality of biometric data; further comparing the further set to the data model; and determining whether said further comparing indicates a need for a further command to be sent to the remote networked device in order to further effect a change in an operational characteristic of the networked device.

Abstract: A method of determining data model for use in predicting a state of a user based on collected biometric data collected via a sensor platform, the method comprising receiving from sensors of the sensor platform a plurality of the biometric data; extracting a plurality of representative features from the plurality of biometric data; receiving a plurality of user affect parameters associated with the plurality of representative features; correlating the plurality of user affect parameters with the plurality of representative features to determine a set of representative feature-affect pairings for the data model as a plurality of model data parameters; and storing the data model for subsequent use in determining the real time state of the user.

Abstract: Systems, methods and devices for recognizing user activity using data from accelerometer or other sensors. “Feature-based” approach and “model-based” approaches are described. In a feature-based approach, various values are extracted from input signals and projected onto a space that is selected to facilitate better segregation of data points. Classifiers identify the regions in this projected space in which the data points fall to distinguish between the different activity types. In a “model-based” approach, a generative model is trained for each activity type. Different activity types can be distinguished by identifying similarities between the input data with the generative models.

Abstract: Systems, methods and devices that facilitate determination of enhanced exercise or physical activity metrics by considering multiple types of data. Metrics are computable by pre-processing, and in some cases segmenting, a variety of input signals, such as acceleration signals, electromyography signals or other signals from a wearable device.

Abstract: A system, method and device are described for biometric analysis using a wearable device. The device can be removeably securable to a user's skin surface and can include a plurality of electrodes positioned to acquire electrical signals from the skin surface. The device can also include an electromyography acquisition module and skin impedance acquisition module. A processing unit can use the electrodes to capture a plurality of electrical signals including at least one electromyography signal. The processing unit can generate calibration data based on a subset of the captured electrical signals and process the electromyography signals using the calibration data to determine a biometric for the user.