Multimodal Tracking System for Visual-Physical Coordination Gaps
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Solution Overview
Problem
Current methods for tracking eye and body movements during activities or sports do not adequately identify deficiencies in visual tracking and coordination, such as in hitting a baseball, as they fail to provide comprehensive data on correlations between eye movements, body movements, and physiological responses.
Innovation Solution
Systems and methods for simultaneously tracking and analyzing eye movements, body movements, and physiological data during activities or sports, using various data collection techniques like eye tracking systems, body tracking systems, and physiological sensors, to identify correlations and improve performance by highlighting delays or gaps in task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only eye movement tracking is used, then visual tracking data can be collected, but comprehensive deficiencies in coordination and task execution cannot be identified
Solution Approach 1:
The patent combines multiple tracking systems (eye movement tracking, body movement tracking, and physiological data collection) into an integrated system. This merging allows simultaneous collection of visual tracking data, body position data, and physiological responses, enabling comprehensive analysis of coordination deficiencies that cannot be detected by eye tracking alone.
Solution Approach 2:
The tracking system is designed to perform multiple functions: tracking eye movements, tracking body movements, collecting physiological data, and analyzing correlations between these different data types. This multi-functional approach allows the system to identify various aspects of performance including visual tracking accuracy, coordination patterns, and physiological responses within a single integrated framework.
2Loss of information
If multiple data types (eye movement, body movement, physiological data) are collected and correlated, then comprehensive performance analysis is achieved, but system complexity increases
Solution Approach 1:
The system divides the complex tracking task into separate functional modules: an eye movement tracking component, a body movement tracking component, and a physiological data collection component. Each module independently collects its specific data type, and then a correlation analysis component integrates these segmented data streams. This segmentation reduces the complexity of any single component while maintaining comprehensive data collection capabilities.
Solution Approach 2:
The patent introduces a data correlation and analysis component that acts as an intermediary between the various tracking systems. This intermediary component receives data from multiple sources (eye tracking, body tracking, physiological sensors), synchronizes the data streams, and performs correlation analysis to identify patterns and deficiencies. This mediator simplifies the integration process by providing a standardized interface for combining diverse data types.
Data Source
AI summary
The eye movement, body movement, and/or physiological performance of a subject may tracked while the subject performs a task, such as participating in an activity or sport. The collected data may then be used to identify correlations between the subject's eyesight and the subject's body movement exists and/or physiology. Such a correlation may be analyzed (e.g., over time) to determine any delays or gaps in the subject's ability to track an object, such as a ball, while participating in a sport or other activity. Further, a subject's performance may be compared to data collected from other individuals. The eye movement, body movement, and/or physiological performance data may be used to test and/or train the visual and cognitive abilities of an individual.