Generating Multi-Sensory Content based on User State

Smart overview of the Invention

A method for generating personalized multi-sensory content is designed to respond to a user's physiological and emotional states. By receiving input information that reflects these states, the technique creates prompt information that outlines the guidance objective. This information is then processed using a pattern completion component, which translates it into output information containing instructions for an output system to deliver the desired content.

Therapeutic Goals and User Input

The generated guidance can target various therapeutic goals, such as stress reduction, meditation, sleep induction, or enhancing focus. Users can also self-report their emotional states, allowing for a more tailored experience. The physiological data may include vital signs, brain activity, body movements, and other characteristics that provide insight into the user's current condition.

Machine-Trained Models

The technique employs machine-trained models to map input to output information. These models can be transformer-based and utilize attention mechanisms to effectively process text-based data. Output instructions may encompass various formats, including commands for controlling sensing devices or delivering audio and visual content aimed at achieving the therapeutic goals.

Output Systems and Sensory Integration

The output system can include multiple modalities such as audio, visual, lighting, scent, and haptic feedback. For instance, audio content may consist of narratives that support the guidance objectives. Additionally, synthesized visual content can be integrated with other sensory experiences to create a cohesive multi-sensory environment for the user.

Flexibility and User Engagement

This approach offers a flexible solution adaptable to diverse training objectives without requiring extensive resources for each specific case. Users can easily set up the system by articulating their goals and emotional states. The technique also incorporates contextual information from various sources to enhance user engagement and effectiveness during training sessions.