Heart Rate-Dependent ST Deviation Thresholds for Ischemia Detection
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Solution Overview
Problem
Current systems for detecting acute myocardial infarction (AMI) lack effective patient-specific thresholds for cardiac event detection, relying on absolute or relative ST segment deviation thresholds that do not adequately account for individual variations in heart rate and ischemia conditions.
Innovation Solution
A heart monitor with an analog-to-digital converter and processor that generates an ST deviation time series using a recursive exponential average filter, computes heart rate-dependent ischemia detection thresholds based on the statistical distribution of ST deviations, and stores data in histogram format to determine normal ranges and set patient-specific thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If absolute or relative ST segment deviation thresholds are used for AMI detection, then the detection system can identify cardiac events, but the system produces false alarms and lacks patient-specific accuracy due to not accounting for individual variations in heart rate and ischemia conditions
Solution Approach 1:
The patent transforms fixed absolute or relative thresholds into dynamic, patient-specific thresholds by incorporating heart rate as a variable parameter. The system estimates normal ST segment voltage ranges based on the patient's current heart rate and computes detection thresholds as deviations from this personalized baseline, thereby adapting the detection criteria to individual physiological variations and reducing false alarms
Solution Approach 2:
The system performs preliminary estimation of the patient's normal ST segment voltage range and baseline characteristics during a monitoring period before using these established parameters for acute ischemia detection. This preliminary characterization of individual norms enables subsequent detection to be compared against personalized rather than population-based thresholds
2Measurement precision
If patient-specific thresholds based on statistical distribution analysis are implemented, then detection accuracy improves, but system complexity increases due to histogram generation and threshold computation requirements
Solution Approach 1:
The patent introduces histogram data structures as an intermediary mechanism to organize ST segment voltage measurements by heart rate bins. This intermediary representation simplifies the complex task of finding patient-specific thresholds by providing a structured summary of voltage distributions across different heart rates, making the threshold computation process more manageable and systematic
Solution Approach 2:
The system segments the continuous heart rate range into discrete bins and creates separate histogram representations for each bin. This segmentation allows the system to handle the complexity of heart rate-dependent ST segment variations by treating each heart rate range independently, simplifying the overall threshold determination process through divided analysis
Data Source
AI summary
A method for detecting acute ischemia is disclosed. The method comprises the steps of determining ST segment deviations and storing the results in heart rate based histograms. The histogram data is periodically analyzed to estimate a true range of ST deviation for a particular heart rate range. A current threshold for a heart rate range is set by estimating the true range of ST deviations within that bin, determining the median value of ST deviations within the range, and basing thresholds on the range and median value. The true range for a particular heart rate bin is estimated by locating ST deviation values between which reside a predetermined percentage of all ST deviation values collected for that bin.