Abstract: Computerized methods and systems, including computer programs encoded on a computer storage medium, may adaptively predict expression of emotions based on collected biometric data. For example, a computing system may receive first data indicative of a first time-evolving movement of a portion of a body during a collection period, and may obtain second data identifying predictive models that correlate default emotions with second feature values that characterize body movements during prior collection periods. Based on an outcome of the application of the least one pattern recognition algorithm or machine learning algorithm to portions of the first and second data, the system may determine a corresponding one of the default emotions represented by the first time-evolving movement, and may transmit data indicative of the corresponding one of the default emotions to the communications device for presentation to a user.

Abstract: Computerized methods and systems, including computer programs encoded on a computer storage medium, may adaptively predict expression of emotions based on collected biometric data. For example, a computing system may receive first data indicative of a first time-evolving movement of a portion of a body during a collection period, and may obtain second data identifying predictive models that correlate default emotions with second feature values that characterize body movements during prior collection periods. Based on an outcome of the application of the least one pattern recognition algorithm or machine learning algorithm to portions of the first and second data, the system may determine a corresponding one of the default emotions represented by the first time-evolving movement, and may transmit data indicative of the corresponding one of the default emotions to the communications device for presentation to a user.

Abstract: Computerized methods and systems, including computer programs encoded on a computer storage medium, may adaptively predict expression of emotions based on collected biometric data. For example, a computing system may receive first data indicative of a first time-evolving movement of a portion of a body during a collection period, and may obtain second data identifying predictive models that correlate default emotions with second feature values that characterize body movements during prior collection periods. Based on an outcome of the application of the least one pattern recognition algorithm or machine learning algorithm to portions of the first and second data, the system may determine a corresponding one of the default emotions represented by the first time-evolving movement, and may transmit data indicative of the corresponding one of the default emotions to the communications device for presentation to a user.