Sensor-Driven Training System for Expert Knowledge Variations
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Solution Overview
Problem
Existing technologies for integrating performance sensors with training systems primarily focus on reporting human activity outcomes rather than analyzing the manner in which the activity is performed, providing only superficial assessments of human performance.
Innovation Solution
A computer-implemented method that configures local performance monitoring hardware to enable users to select and download content related to specific skills, including sensor configuration data, state engine data, and user interface data, allowing for the identification of expert-specific attributes and coaching advice based on data from motion sensor units, such as accelerometers, magnetometers, and gyroscopes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If performance sensors are integrated with training systems to monitor human activity, then activity outcome reporting is improved, but analysis of the manner in which activity is performed deteriorates
Solution Approach 1:
The system segments performance analysis into multiple dimensions: outcome metrics (distance, speed, time) and manner metrics (movement patterns, technique quality, body positioning). Sensors are configured to collect both types of data independently, allowing comprehensive analysis without compromising either aspect.
Solution Approach 2:
The patent adds temporal and spatial dimensions to performance monitoring. Instead of only measuring outcome metrics, the system captures motion trajectories, acceleration patterns, and positional data over time, enabling analysis of how activities are performed rather than just what results were achieved.
2Ease of operation
If training content is standardized for multiple skills, then ease of operation is improved, but adaptability to different expert knowledge variations deteriorates
Solution Approach 1:
The training content delivery system is designed to be dynamic rather than static. It automatically adapts content based on detected performance attributes, user progress, and selected expert knowledge variations. The system transitions from pre-defined fixed content to adaptive content that evolves based on real-time performance data and user interactions.
Solution Approach 2:
The system allows modification of training content parameters such as difficulty level, feedback frequency, and instructional focus based on performance attributes. Different expert knowledge variations introduce different parameter settings for the same skill, enabling users to access multiple perspectives without requiring separate training programs.
3Measurement precision
If performance monitoring hardware is configured for detailed skill analysis, then measurement precision is improved, but device complexity deteriorates
Solution Approach 1:
The performance monitoring hardware is designed with multi-functionality, using a core set of sensors (accelerometers, gyroscopes, magnetometers) that can serve multiple analysis purposes. The same sensor suite supports both outcome tracking and manner analysis across different skills, reducing the need for specialized equipment for each skill type.
Solution Approach 2:
The patent introduces a processing layer that acts as an intermediary between raw sensor data and detailed skill analysis. This layer includes algorithms and models that translate complex sensor outputs into meaningful performance attributes, reducing the complexity burden on the hardware while maintaining high measurement precision.
Data Source
AI summary
The present invention relates to delivery of content that is driven by input from one or more performance sensor units, such as performance sensor units configured to monitor motion-based performances and/or audio-based performances. Embodiments of the invention include software and hardware, and associated methodologies, associated with the generation, distribution, and execution of such content. Particular attention is paid to technologies that enable the delivery of skills training content that provides for expert knowledge variations in training content for various skills.