Behavioral Biometric Payments for Uninterrupted XR Transactions

The patent replaces traditional mechanical authentication systems (keyboards, mice, pop-up windows) with behavioral biometric authentication that operates through sensors tracking user behavior patterns. This substitution eliminates the need for users to exit or interrupt their immersive XR experience to provide authentication credentials, as the system continuously or periodically collects behavioral data (eye movements, head gestures, voice patterns) and processes it to verify identity and authorize transactions in the background.

The system implements self-service authentication by automatically collecting behavioral biometric data from users during their natural XR interactions without requiring explicit user actions for authentication. The system autonomously processes this data to identify users, verify their identities, and authorize transactions, eliminating the need for manual authentication steps and allowing users to maintain their immersive experience uninterrupted.

The patent implements preliminary authentication by collecting and processing behavioral biometric data before transactions are initiated. The system continuously monitors user behavior patterns and pre-verify user identity during the XR session, so that when a transaction is requested, the authentication is already complete or can be rapidly finalized. This eliminates the need for time-consuming authentication steps at the point of transaction.

The system maintains continuous authentication by periodically collecting behavioral biometric data throughout the XR session rather than requiring discrete authentication events. This continuous verification process ensures security is maintained while allowing transactions to be authorized immediately when needed, as the system already has current behavioral data to verify user identity without interruption or delay.

The patent implements periodic sampling of behavioral biometric data rather than continuous monitoring. The system collects behavioral data at strategically selected intervals during the XR session, analyzing patterns such as eye movements, head gestures, and voice characteristics at these periodic points. This approach maintains sufficient authentication accuracy by capturing enough behavioral samples to verify identity while significantly reducing the computational burden and energy consumption compared to truly continuous analysis.

The system applies partial action by collecting only the specific behavioral biometric data types needed for authentication (such as eye tracking, head movement, or voice patterns) rather than analyzing all possible user behaviors. This selective collection of relevant behavioral markers maintains authentication accuracy while minimizing resource consumption by focusing processing power only on the most discriminative and necessary behavioral features.