Motion Sensor Avatar for Epilepsy Seizure Detection
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Solution Overview
Problem
Current methods for diagnosing and monitoring epilepsy are subjective and invasive, relying on patient recall and prolonged hospital-based video capturing, which limits their effectiveness and practicality for everyday life.
Innovation Solution
A method utilizing multiple motion sensors installed on the body to collect and record data for extended periods, combining sensor data to visualize movements through an avatar, allowing for real-time monitoring and differentiation of seizure patterns from daily activities, using three-axis accelerometers, gyroscopes, and other medical sensors, with data fusion and pattern recognition for precise analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple motion sensors are installed on the body for continuous monitoring, then measurement precision and reliability are improved, but device complexity increases
Solution Approach 1:
The system divides the monitoring task into multiple independent sensor units distributed across different body parts (head, torso, limbs). Each sensor independently captures motion data from its local position, and the central system integrates these segmented measurements to achieve comprehensive seizure detection with high precision while maintaining manageable complexity through modular architecture.
Solution Approach 2:
Multiple sensors measuring different physical quantities (acceleration, gyroscope, magnetometer) are merged into a unified sensor system. The data from all sensors are combined and processed together to detect seizure patterns, leveraging the complementary information from each sensor type to improve overall measurement precision and reliability.
2Reliability
If data is collected for extended periods (at least 24 hours), then reliability of seizure detection is improved, but loss of time and patient burden increase
Solution Approach 1:
The system performs preliminary processing and filtering of sensor data in real-time during the monitoring period. Motion patterns are pre-analyzed and segmented, with potential seizure events flagged for detailed review. This preliminary action prepares the data in advance, making the actual diagnosis process faster and reducing the time burden on patients and physicians.
Solution Approach 2:
Instead of continuous intensive processing, the system employs periodic analysis intervals where sensor data is collected continuously but evaluated at specific intervals or when threshold events occur. This periodic action maintains high reliability for detecting seizures that may happen infrequently while reducing overall processing time and patient burden during normal monitoring periods.
3Measurement precision
If multiple sensors are used for comprehensive monitoring, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The sensor units are designed as universal, multi-functional components that can be attached to various body parts (head, torso, limbs) and perform multiple measurement functions (acceleration, rotation, magnetic field sensing). This universality simplifies installation and operation, as the same sensor type can be deployed anywhere on the body without requiring different specialized devices, while still achieving comprehensive motion recognition precision.
4Measurement precision
If video capturing is used to observe seizures, then measurement precision is improved, but device complexity and patient burden increase
Solution Approach 1:
The system replaces the mechanical video capturing approach with motion sensors that directly measure physical movement parameters. Instead of recording visual images that require complex processing and interpretation, the sensors directly detect the characteristic motion patterns of seizures through acceleration and rotation measurements, simplifying the overall system while maintaining or improving measurement precision for seizure detection.
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 effective, non-invasive, and continuous monitoring of movements, allowing for accurate detection of seizures and treatment evaluation with minimal disruption to daily life, providing valuable data for medical professionals to diagnose and assess epilepsy and other neurological diseases.
Implementation Method 1
the sensors are each three-axis motion sensors, in other words, accelerometer sensors, which detect an orientation as well as a change in velocity, thus an acceleration
Implementation Method 2
In addition, the sensor can comprise a gyroscope
Data Source
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Figure 3
AI summary
The present invention relates to a method for retrieving sensor data for medical motion recognition, wherein the method comprises retrieving and recording data from multiple motion sensors on a person for a period of time of at least 24 hours, and wherein the method further comprises displaying at least time segments of the retrieved and recorded data in the form of an avatar for visualizing movements of the person within the time segment.