Invention Title:

SYSTEM AND METHOD FOR ENHANCING CONTENT USING BRAIN-STATE DATA

Publication number:

US20240388759

Publication date:
Section:

Electricity

Class:

H04N21/42201

Inventors:

Applicant:

Smart overview of the Invention

The innovation involves a computer system that adjusts digital content presentation based on an individual's brainwave data. This system can modify how content is displayed on devices by following specific rules or user inputs. Additionally, it allows sharing of content alongside related brain state information, enhancing the interaction between users and digital platforms.

Technical Background

Bio-signals, such as those from the human brain, are measurable through devices like electroencephalograms (EEG). These signals, often in analog form, can be converted to digital for analysis. Applications of such bio-signals include brain-computer interfaces that enable control over devices using brainwave patterns. The invention aims to utilize these signals to improve engagement with digital content.

System Components

The system comprises a computing device connected to bio-signal sensors and user input devices. It displays digital content and adjusts it based on received brainwave data, user commands, and predefined rules. User profiles, which may include historical bio-signal data and preferences, help tailor the content presentation to individual users. Modifications can range from altering audio-visual elements to sharing content with others.

Content Modification

Digital content can be modified in various ways, including prioritizing or filtering information. Modifications can be either destructive or non-destructive to the original content. The system may control applications based on brain states, such as starting a video recording when a specific emotional threshold is met. Content presentations can also synchronize with time-coded bio-signal data for precise interaction.

Applications and Features

The system includes a content analyzer that identifies features of digital content and correlates them with user brain states. A recommendation engine uses this data to suggest content that aligns with user preferences. Additionally, during communication sessions over networks, users' brain states can be tracked and shared, potentially matching users with similar brain states in social media contexts.