Helmet Impact Monitoring for Personalized Contact Sport Training
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Solution Overview
Problem
Existing systems fail to accurately assess the severity and frequency of head impacts in contact sports, particularly for individual players, and do not provide personalized coaching and training opportunities based on player-specific data.
Innovation Solution
A system with in-helmet sensors that monitor physiological parameters, generate alerts for individual and cumulative impact thresholds, and provide post-activity analysis through a graphical user interface, allowing for personalized coaching and training opportunities based on player-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in-helmet sensors and data analysis platform are implemented, then head impact monitoring capability is improved, but device complexity increases
Solution Approach 1:
The system divides the monitoring function into separate components: in-helmet sensors for data collection, wireless communication module for data transmission, and external computing devices for analysis. This segmentation allows each component to be optimized independently while reducing the complexity burden on any single element.
Solution Approach 2:
The patent introduces wireless communication as an intermediary between the in-helmet sensors and external analysis systems. This mediator enables data transfer without requiring complex wired connections or processing within the helmet itself, simplifying the in-helmet device while maintaining monitoring capability.
2Loss of information
If post-activity analysis with historical data comparison is provided, then coaching effectiveness is improved, but loss of time increases
Solution Approach 1:
The system pre-processes and stores historical impact data in structured databases before coaching sessions. By having reference data ready in advance, the system can quickly compare current player performance against historical benchmarks during post-activity analysis, reducing processing time while maintaining comprehensive analysis capability.
Solution Approach 2:
The patent replaces manual coaching analysis with automated computational algorithms that process impact data. This substitution of mechanical/manual processes with electronic computation significantly reduces the time required for post-activity analysis while providing more comprehensive insights.
3Reliability
If real-time impact threshold alerts are generated, then player safety monitoring is improved, but use of energy increases
Solution Approach 1:
The system uses periodic sampling of impact data rather than continuous monitoring. Sensors take measurements at regular intervals and only trigger alerts when threshold values are exceeded, significantly reducing energy consumption while maintaining effective safety monitoring capability.
Solution Approach 2:
The in-helmet device autonomously processes impact data locally and generates alerts only when necessary. This self-service approach eliminates the need for constant external system intervention and reduces overall energy consumption by performing critical functions at the source.
Data Source
AI summary
The present disclosure provides systems and methods for providing training opportunities based on data collected from monitoring a physiological parameter of persons engaged in physical activity. The physical activity can be a sporting activity, such as a contact sport (e.g., football, hockey, lacrosse) or a recreational activity or sport (e.g., biking, hiking, skiing, snowboarding, motorsports). The system is configured with select components that perform a method of (i) recording data related to a physiological parameter of a person engaged in a physical activity (e.g., an impact received by a player engaged in a contact sport), (ii) analyzing the recorded data related to the physiological parameter while the person is engaged in a physical activity (e.g., is the received impact greater than a predetermined threshold), and (iii) providing post-physical activity analysis of the recorded data to make suggested changes in how the person engages in the physical activity.