ECG Signal Artifact Detection and Q-T Segment Measurement
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Solution Overview
Problem
Existing ECG signal analysis systems face challenges in accurately detecting and rejecting artifact signals, leading to false arrhythmia alarms and reduced precision in heart rate calculation and beat classification due to noise contamination.
Innovation Solution
An apparatus with processors programmed to select sample points, extract features, and apply transformations to detect artifact signals and identify systolic segments in ECG signals, using algorithms to enhance accuracy and reduce false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ECG signal analysis algorithms are used, then the system is simple and easy to implement, but artifact signals cause false arrhythmia alarms and reduce measurement precision
Solution Approach 1:
The patent segments the ECG signal analysis into distinct components: artifact detection module, artifact classification module (physiological vs. non-physiological), and systolic segment identification module. This segmentation allows each module to specialize in specific tasks, improving overall accuracy while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary artifact detection and classification system between the raw ECG signal and the systolic segment identification algorithm. This intermediary layer filters and characterizes artifacts before they can interfere with QRS complex detection, thereby improving measurement precision without requiring complete redesign of the core detection algorithms.
2Reliability
If artifact detection and rejection algorithms are implemented, then false alarms are reduced, but the processing time and computational load increase
Solution Approach 1:
The patent performs preliminary artifact detection and classification before systolic segment identification. By detecting and characterizing artifacts in advance, the system can adjust its analysis parameters or exclude contaminated segments, reducing false alarms while maintaining efficient real-time processing of clean signals.
Solution Approach 2:
The patent applies artifact detection selectively rather than uniformly to all signal segments. The system identifies regions with high artifact probability and applies enhanced detection algorithms only to those segments, while using faster algorithms for clean segments, thereby reducing overall processing time while maintaining high reliability.
3Measurement precision
If comprehensive artifact detection is performed, then measurement accuracy improves, but the device complexity and computational requirements increase
Solution Approach 1:
The patent applies different detection strategies and algorithmic approaches to different signal segments based on local artifact characteristics. Rather than using a single complex algorithm throughout, the system adapts its processing approach to match the local signal quality and artifact type, improving precision while managing overall system complexity.
Data Source
AI summary
A method of processing of electrocardiogram (“ECG”) signals from at least one ECG lead connected to a patient includes computing an average beat from a plurality of beats occurring during a predetermined averaging interval. An R-point, an onset point and a J-point of the average beat is computed to establish a Q-T segment of the average beat. The R-point, onset point and the J-point of the average beat are used to determine a Q-T segment for each beat of the averaging interval, and the average of the Q-T segments of each beat is computed and averaged with the Q-T segment of the average beat.