Vital-Data Avatar Rendering for Accurate User State Estimation

The patent transforms the avatar configuration from using simple mental state or facial expression parameters to using multiple physiological parameters (heart rate, respiration rate, skin conductance, temperature) and behavioral parameters (facial expressions, head movements, body posture). This parameter expansion enables realistic reflection of complex user states including mental state, physical state, and emotional state simultaneously.

The patent combines multiple types of data (physiological data from sensors, facial expression data from cameras, head movement data from accelerometers) to create a composite avatar representation. This composite approach integrates diverse data sources to achieve a comprehensive and realistic depiction of user state that surpasses any single data type.

The patent divides the complex data processing system into distinct functional modules: a data acquisition module that collects physiological and behavioral data, a data processing module that analyzes the collected data, and an avatar generation module that creates the visual representation. This segmentation allows each module to handle specific tasks independently, managing overall system complexity while maintaining high estimation accuracy.

The patent introduces an intermediary processing layer between raw data collection and avatar generation. This intermediary module integrates multiple data sources, correlates physiological data with behavioral observations, and transforms complex multi-dimensional data into meaningful user state estimates that drive avatar animation and expression.

The patent implements periodic sampling of physiological data at optimized intervals rather than continuous monitoring. The system collects vital data at regular time intervals, processes these periodic samples to estimate user state, and updates the avatar accordingly. This periodic approach maintains real-time responsiveness while significantly reducing computational burden compared to continuous processing.

The patent applies partial processing by focusing computational resources on the most informative data subsets. Rather than processing all available data with equal depth, the system identifies and prioritizes key physiological and behavioral indicators that most strongly correlate with user state, processing these selectively to achieve accurate real-time estimation with reduced time requirements.