SYSTEMS AND METHODS MAKING RECOMMENDATIONS BASED ON DATA FROM WEARABLE DEVICES
The methods and systems described herein may involve determining at least one lifeotype of at least one individual, analyzing the at least one lifeotype, and delivering content to at least one individual based on the analysis. The methods and systems described herein may involve providing a game, determining at least one lifeotype of at least one player of the game, analyzing the at least one lifeotype, and affecting the game play based on the analysis. The methods and systems described herein may involve providing an interactive space, determining at least one lifeotype of at least one individual in the space, analyzing the at least one lifeotype, and modifying at least one attribute of the space based on the analysis.
1 . A computer-system-implemented method, the computer system having at least one programmed processor to implement the method, the method comprising:
continuously collecting physiological data components with respect to an individual from a wearable sensor device;
the computer system—
(i) obtaining context information for the individual based at least in part on output from a contextual sensor; and
(ii) based on a determination that the context of the individual is in a social environment and the physiological data collected from the wearable sensor device, determining a recommendation.
2 . The method of claim 1 , wherein the context is also determined at least in part based on the output of a plurality of sensors of the wearable sensor device.
3 . The method of claim 1 , wherein said physiological data collected from the wearable sensor device is selected from the group consisting of: derived data, continuous data, discrete data, time series data, event data, raw data, processed data, metadata, third party data, physiological state data, sensed data, continuously monitored data, and real-time data.
4 . The method of claim 1 , wherein at least one data component collected from a wearable sensor device is a data component that is derived from a plurality of sensors that is distinct from the output of any single sensor. The method of claim 1 , wherein the environment is a gym.
5 . The method of claim 1 , wherein the social environment comprises information about the types of individuals present.
6 . The method of claim 1 , wherein the social environment comprises information about the types of devices present.
7 . The method of claim 1 , wherein the recommendation comprises at least one of a restaurant recommendation, a sporting activity recommendation, a bar recommendation, a recommendation of other individuals for a group social activity and a recommendation for a social gathering.