Athletic Signature Generation via Force-Time Data Normalization
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Solution Overview
Problem
There is no systematic way to analyze sensor data from athletes during athletic movements to improve performance effectively.
Innovation Solution
A method involving the storage of force-time data, normalization of data based on a population's values, and generation of athletic signatures using concentric net vertical impulse, average eccentric rate of force development, and average vertical concentric force, which are used to profile athletes and improve performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If sensor data is collected during athletic movements, then data availability for analysis is improved, but lack of systematic analysis method reduces performance improvement effectiveness
Solution Approach 1:
The patent transforms raw sensor data into meaningful athletic profiles by changing parameters through normalization against population data. Key parameters including concentric net vertical impulse (CON-IMP), average eccentric rate of force development (ECC-RFD), and average vertical concentric force (CON-VF) are calculated and normalized to create comparable athletic signatures that enable systematic performance analysis
Solution Approach 2:
The patent introduces an intermediary processing system that acts as a mediator between raw sensor data and performance insights. The systematic analysis method including data normalization, parameter calculation, and profile generation serves as the intermediary that transforms unavailable systematic analysis into actionable performance improvement guidance
2Measurement precision
If force-time data is stored and normalized for population comparison, then measurement precision and systematic analysis are improved, but data processing complexity increases
Solution Approach 1:
The patent segments the force-time data into distinct parameters for analysis: concentric net vertical impulse (CON-IMP), average eccentric rate of force development (ECC-RFD), and average vertical concentric force (CON-VF). This segmentation allows precise measurement of different aspects of athletic performance while organizing complex data into manageable, interpretable components
Solution Approach 2:
The patent performs preliminary normalization of force-time data against population values before detailed analysis. By pre-calculating normalized parameters and storing them as part of the athletic signature, the system reduces processing complexity for subsequent performance comparisons and eliminates the need for complex real-time population comparisons
Data Source
AI summary
A method for profiling an athlete is discloses. The method comprises storing force-time data for a population of athletes; wherein said force-time data is generated by a sensor system in respect of each of said plurality of athletes in response to the said athlete performing an athletic movement, and comprises values for a concentric net vertical impulse (CON-IMP), an average eccentric rate of force development (ECC-RFD), and an average vertical concentric force (CON-VF); performing a normalization of the force-time data for each athlete based on values of the force-time data within the population of athletes; and generating a profile comprising an athletic signature for each athlete in the population, wherein said profile comprises the normalized values for the concentric net vertical impulse (CON-IMP), the average eccentric rate of force development (ECC-RFD), and the average vertical concentric force (CON-VF) for the athlete.