Composite Neuro-physiological State Calculation for Audio-Video Control
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Solution Overview
Problem
Current communication technologies, including electronic devices and games, struggle to effectively sense and respond to emotional signals, leading to misunderstandings and a lack of engagement, especially in electronic communication and gaming environments where emotional cues are diminished or absent.
Innovation Solution
The development of a method to calculate a Composite Neuro-physiological State (CNS) using biometric sensors such as EEG, GSR, and fMRI data, which correlates to a user's emotional state, allowing for real-time adjustments in communication and game interactions to enhance engagement and understanding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If biometric sensors and CNS calculation are integrated into electronic communication devices, then emotional signaling accuracy is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple biometric sensors (EEG, GSR, fEMG, EKG, fNIR, fMRI) into a single electronic communication device to comprehensively detect neuro-physiological states. This merging of sensing capabilities enables accurate emotional signaling detection while integrating multiple functions into one device platform.
Solution Approach 2:
The electronic communication device is designed to perform multiple functions: traditional communication tasks plus neuro-physiological state detection and emotional signaling analysis. This multi-functionality allows the device to serve as both a communication tool and an emotional sensing instrument, improving emotional signaling accuracy without requiring separate dedicated equipment.
2Measurement precision
If multiple biometric sensors are used to detect neuro-physiological state, then emotional detection accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically detects and processes neuro-physiological states without requiring user intervention. The biometric sensors continuously monitor emotional states, and the CNS calculation is performed automatically by the processor, eliminating the need for users to manually input or adjust settings while maintaining high detection accuracy.
Solution Approach 2:
The system provides real-time feedback by analyzing CNS values and adjusting communication or game interactions accordingly. This automated feedback loop allows the system to respond dynamically to detected emotional states without requiring complex user input or manual calibration.
3Productivity
If real-time CNS monitoring is implemented in games, then user engagement is improved, but use of energy increases
Solution Approach 1:
The system implements periodic sampling of biometric data rather than continuous monitoring at maximum rate. The processor calculates CNS values at intervals based on game events or time periods, reducing overall energy consumption while maintaining sufficient engagement detection capability for meaningful game interactions.
Solution Approach 2:
The monitoring intensity is dynamically adjusted based on game context and detected engagement levels. The system increases sampling rates during critical game moments to maintain engagement while reducing rates during less critical periods, optimizing energy usage while preserving user engagement quality.
4Measurement precision
If lie detection capabilities are added to communication devices, then deception detection accuracy is improved, but object-affected harmful factors increase
Solution Approach 1:
The system uses neuro-physiological measurements as an intermediary to detect deception indirectly, rather than directly monitoring deceptive intent. The biometric sensors detect physiological arousal and stress indicators that correlate with deception, providing detection capability while minimizing direct intrusion into user privacy and behavior.
Data Source
AI summary
Provided is a system for controlling progress of audio-video content based on sensor data of multiple users, composite neuro-physiological state (CNS) and/or content engagement power (CEP). Sensor data is received from sensors positioned on an electronic device of a first user to sense neuro-physiological responses of the first user and second users that are in field-of-view (FOV) of the sensors. Based on the sensor data and at least one of a CNS value for social interaction application and a CEP value for immersive content, recommendations of action items for first user are predicted. Content of a feedback loop, created based on sensor data, CNS value, CEP value, and predicted recommendations, is rendered on output unit of electronic device during play of the at least one of social interaction application and immersive content experience. Progress of social interaction and immersive content experience is controlled by first user based on predicted recommendations.