Equestrian Helmet STAR Rating for Multi-Impact Concussion Risk
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Solution Overview
Problem
Current equestrian helmet evaluation standards fail to account for both linear and angular acceleration during head impacts, are limited in scope, and do not accurately assess a helmet's ability to reduce head injuries, as they are pass/fail and only test at a single energy level, failing to differentiate between helmets.
Innovation Solution
The STAR method evaluates helmet performance by combining impact testing with injury risk functions and exposure data, measuring linear and angular acceleration at multiple locations and energy levels, using a dummy headform and neck configuration, and generating a rating system based on weighted risk values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current equestrian helmet evaluation standards are used, then helmet safety is maintained at basic level, but the ability to differentiate between helmets and accurately assess head injury reduction capability is lost
Solution Approach 1:
The evaluation system is segmented into multiple independent impact configurations (front, side, rear impacts at different velocities), allowing each component to be tested separately. This segmentation enables precise measurement of helmet performance at different locations and energy levels without requiring a single complex test procedure.
Solution Approach 2:
The system transitions from single-energy-level testing to multi-energy-level testing by incorporating impacts at both 5.0 m/s and 6.3 m/s. This adds an energy dimension to the evaluation, enabling accurate differentiation between helmets based on their performance across varying impact conditions.
2Measurement precision
If only linear acceleration is tested, then the evaluation process remains simple, but the ability to assess rotational head acceleration and differentiate helmet performance is compromised
Solution Approach 1:
The evaluation separates linear and angular acceleration measurements into distinct data streams from the sensor package. Linear acceleration is measured along the impact direction while angular acceleration is measured about the impact point, allowing both to be evaluated independently and then combined for comprehensive helmet performance assessment.
Solution Approach 2:
A sensor package acts as an intermediary device that simultaneously measures both linear and angular acceleration during impact. This sensor package includes accelerometers and angular rate sensors that capture the complete biomechanical response, enabling accurate differentiation between helmets based on their rotational and translational protection capabilities.
3Adaptability or versatility
If single energy level testing is used, then the testing process remains straightforward, but the comprehensive assessment of helmet performance across various impact conditions is impossible
Solution Approach 1:
The impact testing system is designed with multi-functionality by incorporating multiple impact configurations (front, side, rear) at multiple velocity levels (5.0 m/s and 6.3 m/s). This universal testing apparatus can evaluate helmet performance across diverse impact scenarios, making the evaluation comprehensive and adaptable to various equestrian fall conditions.
Solution Approach 2:
The evaluation system dynamically adjusts impact parameters including velocity and impact location to simulate different equestrian fall scenarios. By varying these parameters across multiple test configurations, the system comprehensively assesses helmet performance under different energy levels and impact conditions without requiring separate specialized tests for each scenario.
Data Source
AI summary
Various embodiments relating to methods for evaluating injury mitigation performance of helmets that are used for sports (e.g., equestrian sports) are described. In one embodiment, a method for evaluating injury mitigation performance of an equestrian helmet includes applying a first impact configuration to a first and a second helmet of the same model and applying a second impact configuration to a third and a fourth helmet that are both of the same model as the first and the second helmet. The method further includes generating acceleration data based on impacts that occur as part of the first impact configuration and the second impact configuration. The method further includes determining concussion risk values based on the generated acceleration data. The method also includes determining a concussion risk metric based on the concussion risk values and exposure values.