Affective Software, Inc.

Yuriy Gulak

Vladimir Brayman

John Gottman

Rafael Lisitsa

Connor Eaton

Robert W Bergstrom

The current document is directed to computationally efficient, robust, and accurate methods and systems that determine the heartbeat rate of human subjects, patients, and/or participants monitored by a video-recording-capable device or system by analyzing video recordings of human subjects, patients, and/or participants, either in real time or following video recording. The currently disclosed methods and systems employ face-recognition methods to identify adaptive regions of interest corresponding to facial-skin areas. Spatial averages of the intensities of light components with different frequencies reflected from the identified adaptive regions of interest are extracted from the video recording as intensity signals. The intensity signals are then analyzed to extract detrended, band-pass-filtered oscillating light-intensity signals that are processed by spectral and peak-finding methods that each produces a determined heartbeat rate for each of multiple time intervals.

Methods and systems that determine heartbeat rate from video recordings

The current document is directed to a methods and systems that use observational data collected by various devices and sensors to generate electronic-data representations of human conversations. The implementations of these methods and systems, disclosed in the current document, provide a highly extensible and generic platform for converting observational data into affect-annotated-timeline outputs that provide both a textual transcription of a conversation and a parallel set of affect annotations to the conversation. The affect-annotated-timeline outputs may be useful to researchers and developers, but also serve as inputs to any of a wide variety of downstream analytical processes and analysis systems that are, in turn, incorporated into many different types of special-purpose analysis and control systems.

Automated systems and methods that generate affect-annotated timelines

The current document is directed to methods and systems that provide an emotional compass that reflects the emotional states of human beings, dynamics of the emotional states over time periods, emotional synchronization between humans and between humans and automated interactive systems, and the degree to which the emotional state of one human is influenced or affected by the emotional state of another human or by an automated interactive system. The emotional compass can be used for continuous or intermittent emotional orientation by both automated systems and human analysts. The emotional awareness provided by the emotional compass facilitates continuous or intermittent strategy selection for achieving various different types of emotion-related results.

Automated methods and systems that infer, track, store, and report emotional states and emotional dynamics to render computational systems emotionally aware

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Highland Park, NJ, United States of America

Yuriy Gulak