Concussion Sensor With Sensor Fusion for Real-Time Impact Detection
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Solution Overview
Problem
Current impact sensors lack the ability to accurately capture both linear acceleration and rotational motion while maintaining real-time connectivity with mobile applications and cloud-based analytics for immediate concussion detection.
Innovation Solution
A concussion sensor system integrating high-G accelerometers, IMU gyroscopes, real-time clock timestamping, and wireless communication, utilizing Bluetooth Low Energy for data transmission, with onboard data storage and machine learning for precise impact detection and risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors (accelerometers and gyroscopes) are integrated to capture both linear acceleration and rotational motion, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (accelerometers and gyroscopes) into a single integrated unit that captures both linear acceleration and rotational motion. This merging of sensing functions into one compact device achieves comprehensive impact detection while managing the complexity through unified hardware architecture and synchronized data processing.
Solution Approach 2:
The sensor system is designed with multi-functionality, where the same integrated unit performs multiple measurement tasks (linear acceleration, rotational motion, impact detection) simultaneously. This universal design allows a single device to replace multiple separate sensors, improving measurement precision without proportionally increasing device complexity.
2Loss of time
If real-time wireless data transmission is implemented for immediate concussion detection, then response time is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic wireless data transmission rather than continuous transmission. Data is transmitted in intervals or triggered by specific events (such as detected impacts), which significantly reduces energy consumption while maintaining real-time monitoring capability. This periodic action allows the system to respond quickly to concussions when needed without constantly consuming power.
Solution Approach 2:
The system uses onboard processing capabilities to pre-analyze data locally before transmission, allowing the device to self-determine when transmission is necessary. This self-service approach optimizes energy usage by transmitting only when impactful events occur or at scheduled intervals, rather than continuously, thus reducing power consumption while maintaining timely concussion detection.
3Measurement precision
If high-G accelerometers and IMU gyroscopes are integrated for comprehensive impact detection, then measurement precision is improved, but manufacturing complexity increases
Solution Approach 1:
The patent segments the sensor system into distinct functional modules (accelerometer module, gyroscope module, processing module, wireless module) that can be manufactured and tested separately before final integration. This segmentation simplifies the manufacturing process by allowing specialized fabrication of each component type and facilitates quality control, while still achieving comprehensive impact detection through the integrated design.
Solution Approach 2:
The system employs a nested architecture where smaller sensor components are integrated within a unified housing structure. The accelerometers and gyroscopes are positioned and secured within the device body, with connection cables and processing circuits nested within the same enclosure. This nesting approach streamlines manufacturing by reducing the number of separate assembly steps and simplifies calibration by providing a controlled environment for all sensors.
4Reliability
If onboard data storage is implemented for backup when wireless transmission fails, then data reliability is improved, but device complexity increases
Solution Approach 1:
The patent introduces onboard data storage as an intermediary system between the sensors and external wireless transmission. When wireless transmission is available, data flows to the cloud; when transmission fails, the same data is automatically stored locally as a backup. This intermediary storage layer ensures data reliability without requiring complex decision-making logic, as the system automatically utilizes both transmission and storage pathways based on availability.
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
Enables accurate detection and analysis of head impacts, providing real-time data to mobile apps and cloud platforms for immediate medical intervention and long-term monitoring.
Implementation Method 1
an accelerometer that measures linear acceleration
Implementation Method 2
a gyroscope that measures rotational motion
Data Source
AI summary
The present invention is a wearable concussion detection and monitoring system that captures and analyzes head impact data in real time. It integrates an accelerometer, a gyroscope, and a microcontroller with Bluetooth Low Energy (BLE) for wireless communication. When an impact exceeds a threshold, the system records linear and rotational acceleration, applies sensor fusion algorithms (e.g., Madgwick filter) to remove gravitational noise, and timestamps the event. Data is stored onboard and transmitted to a mobile application and cloud platform for further analysis. Machine learning models assess concussion risk, providing real-time alerts and long-term impact tracking for athletes, trainers, and medical professionals. The system enhances concussion assessment and injury prevention across sports, military, and other high-impact activities, offering an objective, data-driven approach to head injury monitoring.