Dynamic Game Difficulty Adjustment via Physiological Feedback
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Solution Overview
Problem
Existing computer game platforms face inefficiencies and reliability issues due to users aborting games with unsuitable difficulty modes and restarting with different modes, leading to significant computational burdens, as they lack dynamic adjustment of game difficulty based on individual user physiological states.
Innovation Solution
The system dynamically determines game difficulty by receiving physiological evaluation data from sensors during user interactions, calculating physiological difficulty levels, and adjusting program control parameters to generate user interface data that adapts the in-game experience, incorporating both physiological and performance-based metrics to ensure optimal challenge and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If game difficulty is fixed and not dynamically adjusted, then the game platform operates with simple control logic, but users abort games with unsuitable difficulty modes leading to computational waste and reduced reliability
Solution Approach 1:
The patent implements dynamic difficulty adjustment by continuously monitoring user performance metrics and physiological data during gameplay. The system automatically modifies game parameters such as enemy speed, resource spawn rates, and task complexity in real-time based on user capability assessments, transforming the static difficulty into a dynamic adaptive system that maintains optimal challenge levels without requiring user intervention or system restarts
Solution Approach 2:
The system establishes a closed-loop feedback mechanism where user performance data and physiological measurements are continuously collected, processed, and fed back to adjust difficulty parameters. This feedback loop enables the game to respond to user state changes automatically, preventing aborts by maintaining suitable challenge levels throughout the gameplay session
2Loss of time
If game difficulty is manually selected by users, then the system requires minimal processing overhead, but users must restart games to find suitable difficulty levels causing loss of time and computational resources
Solution Approach 1:
The system performs preliminary assessment of user capability before gameplay begins by analyzing initial performance metrics and physiological baseline data. This preliminary action enables the system to pre-configured appropriate difficulty parameters, eliminating the need for users to manually select difficulty levels or restart games to find suitable settings
Solution Approach 2:
The game system automatically determines and adjusts difficulty levels without requiring user input or manual selection. The system serves itself by autonomously monitoring user performance and physiological states, then self-adjusting game parameters to maintain optimal challenge levels, thereby eliminating time loss from difficulty selection and restarts
3Adaptability or versatility
If physiological sensors are integrated for real-time difficulty adjustment, then user engagement and learning retention are enhanced, but the device complexity and computational burden increase significantly
Solution Approach 1:
The system integrates multiple physiological sensors (heart rate monitors, galvanic skin response detectors, eye tracking cameras) into a unified multi-functional platform that serves both gameplay enhancement and difficulty adjustment purposes. This universal system processes diverse physiological data streams through a common analysis engine, reducing overall system complexity while maintaining comprehensive adaptability to user states
Data Source
AI summary
There is a need to dynamically determine one or more levels of difficulty for a computer program associated with one or more levels of difficulty for a computer program associated with one or more dynamic difficulty tasks. In one example, embodiments comprise, during a user interaction session with a computer program, receiving a physiological evaluation data object. One or more physiological difficulty levels may be determined based at least in part on the physiological evaluation data object. One or more program control parameter values for one or more program control parameters may be determined based at least in part on the one or more physiological difficulty levels. User interface data for the computer program may be generated to enable rendering of an in-program experience of the computer program as adjusted by the one or more program control parameter values.