Abstract: Introduced here are approaches to dynamically verifying the identity of an individual and assessing the health of the individual through objective, algorithmic characterizations of voice features derived from audio recordings created by the individual. These voice features may be paralinguistic features, non-linguistic features, or linguistic features. By characterizing these voice features, insights can be gleaned into how events represented in the audio recordings should be emotionally characterized. For example, for each audio recording created by the individual, a health management platform may calculate a valence measure that is based on the voice features established for that audio recording. These valence measures can be documented, for example, in a profile maintained for the individual, such that changes in health can be detected in a more reliable, quantitative manner.

Abstract: Introduced here are health management platforms able to infer the health state of a subject based on behavioral changes reflected in the digital activities performed by a subject. A health management platform can initially acquire contextual data pertaining to digital activities performed by the subject. The health management platform can identify the target(s) of the digital activities by parsing the contextual data, and then compile the digital activities and corresponding activities into a personalized valence index. Thereafter, the health management platform can compare digital activities performed by the subject to the entries included in the personalized valence index. If a matching entry is not discovered, the health management platform can identify an instance of behavior change. These instances of behavior change may be indicative of changes in the subject's health state.

Abstract: Introduced here are health management platforms able to infer the health state of a subject based on behavioral changes reflected in the digital activities performed by a subject. A health management platform can initially acquire contextual data pertaining to digital activities performed by the subject. The health management platform can identify the target(s) of the digital activities by parsing the contextual data, and then compile the digital activities and corresponding activities into a personalized valence index. Thereafter, the health management platform can compare digital activities performed by the subject to the entries included in the personalized valence index. If a matching entry is not discovered, the health management platform can identify an instance of behavior change. These instances of behavior change may be indicative of changes in the subject's health state.