Helmet Parameter Adjustment via Sensor-Detected Play Category
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Solution Overview
Problem
Current helmets lack the ability to automatically adjust their parameters based on the specific activity being performed, which can lead to inadequate protection against concussions and other brain injuries, as they are designed to accommodate all types of impacts uniformly without considering the probability of specific impacts during various types of usage.
Innovation Solution
Incorporating sensors such as accelerometers and gyroscopes into helmets to monitor user movements and determine the category of play, allowing a processor to automatically adjust parameters like chin strap tightness, padding size and stiffness, and lateral mobility based on the probability of certain types of impacts and events occurring during each activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If helmets are designed to accommodate all types of impacts uniformly, then they provide general protection across different activities, but they cannot optimize protection for specific impacts during particular activities
Solution Approach 1:
The helmet employs dynamic adjustment mechanisms that automatically modify protective parameters based on real-time sensor data detecting impact characteristics. The system transitions from static, fixed protection to dynamic, adaptive protection by adjusting padding density, shell stiffness, and other parameters in response to detected impact forces and characteristics.
Solution Approach 2:
The patent changes physical parameters of the helmet such as padding density, material stiffness, and structural configuration based on detected impact characteristics. By modifying these parameters dynamically, the helmet optimizes its protective properties for specific impact types while maintaining versatility across different activities.
2Reliability
If helmets use fixed parameters designed for general use, then manufacturing is simpler and cost is lower, but protection against specific concussive forces is inadequate
Solution Approach 1:
The helmet system performs self-adjustment by using integrated sensors to automatically detect impact characteristics and trigger appropriate protective responses without external intervention. The system monitors its own performance and adapts parameters autonomously, reducing the need for complex external control systems while improving concussion protection.
Solution Approach 2:
The patent incorporates feedback mechanisms where sensors continuously monitor impact forces and feed this information to control systems that adjust helmet parameters in real-time. This closed-loop feedback enables the helmet to learn from detected impacts and optimize its protective response, improving concussion protection through adaptive control.
3Reliability
If helmets adjust parameters automatically based on activity category, then protection is optimized for specific activities, but the system requires sophisticated sensing and control capabilities
Solution Approach 1:
The patent segments the helmet system into distinct functional modules: sensing subsystems for detecting impact characteristics, processing subsystems for analyzing data and determining activity categories, and actuation subsystems for adjusting protective parameters. This modular segmentation reduces overall system complexity by allowing independent optimization of each component while achieving coordinated activity-specific protection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the helmet's protective capabilities by customizing its settings to mitigate brain injuries specific to the activity being performed, providing improved protection against concussions and other traumatic brain injuries by adjusting to the expected risks and impacts of different plays or activities.
Implementation Method 1
Incorporating sensors such as accelerometers and gyroscopes into helmets to monitor user movements
Implementation Method 2
Incorporating sensors such as accelerometers and gyroscopes into helmets to monitor user movements
Data Source
AI summary
Embodiments include method, systems and computer program products for automatic adjustment of helmet parameters based on a category of play. Aspects include monitoring a plurality of sensors in a helmet and determining the category of play for a user of the helmet based on data received from the plurality of sensors. Aspects further include automatically adjusting one or more parameters of the helmet based on the category of play.