Injury Indicator from Acceleration Data via Time-Frequency Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting injuries, such as concussions, using acceleration sensors are limited in their ability to accurately assess the presence and severity of anatomical structure injuries, particularly in the brain, due to the complexity of interpreting acceleration data.
Innovation Solution
The method involves acquiring and analyzing acceleration data from multiple sensors attached to the head using joint time-frequency analysis, determining energy levels, correlations between signals, and relationships between frequency ranges, with machine learning algorithms optimizing parameters to indicate the presence or probability of an injury like a concussion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acceleration data is analyzed using traditional methods, then the analysis process is simple, but the measurement precision of injury detection is insufficient
Solution Approach 1:
The patent applies segmentation by dividing the acceleration signal analysis into multiple frequency bands (e.g., low frequency band 0-5Hz, mid frequency band 5-15Hz, high frequency band 15-30Hz). This allows different aspects of the signal to be analyzed separately, improving measurement precision while managing complexity through structured processing of divided components.
Solution Approach 2:
The patent transitions from traditional time-domain analysis to joint time-frequency analysis, adding a frequency dimension to the analysis. This dimensional change enables the detection of injury indicators that are not visible in time-domain alone, significantly improving measurement precision through spectral analysis and frequency-based feature extraction.
2Reliability
If multiple analysis parameters are considered, then the reliability of injury indication is improved, but the device complexity increases
Solution Approach 1:
The patent merges multiple analysis parameters (overall energy level, correlation between signals, energy relationships across frequency ranges) into a unified injury indicator through a standardized scoring system. This combination approach improves reliability by considering multiple factors simultaneously while managing complexity through an integrated evaluation framework that synthesizes these parameters into a coherent assessment.
Solution Approach 2:
The patent creates a universal analysis framework that can process multiple types of sensor data (acceleration signals from different sensors) and produce a standardized injury indicator. This multi-functional approach improves reliability across different injury scenarios and sensor configurations while maintaining consistent processing complexity through a generalizable methodology.
3Measurement precision
If joint time-frequency analysis is applied, then the measurement precision of acceleration data analysis is improved, but the loss of time in processing increases
Solution Approach 1:
The patent applies preliminary action by pre-defining frequency bands, energy calculation methods, and correlation analysis parameters before actual signal processing. This preparation of analysis frameworks and thresholds in advance reduces the computational burden during real-time processing, improving measurement precision while minimizing processing time loss through optimized ready-to-use analysis templates.
Data Source
AI summary
Disclosed is a medical data processing method for determining an indicator relating to an injury of an anatomical structure (1) of a patient, wherein the method comprises executing, on at least one processor (5) of at least one computer (3), steps of:a) acquiring (S1) acceleration data describing an energy of a set of one or more signals in dependence on both time and frequency, the set of signals acquired by measuring the acceleration of the anatomical structure (1) over time;b) acquiring (S2) analysis data describing an analysis rule for determining at least one ofb1) an overall energy level of at least one signal of the set of signals,b2) a correlation between at least two signals of the set of signals in the frequency domain, the at least two signals respectively measured at at least two different respective regions of the anatomical structure (1), orb3) a relationship between energies given for at least two different frequency ranges of at least one signal of the set of signals;c) determining (S3) indicator data describing the indicator based on the acceleration data and the analysis data.