ECG Data Processing Server Variable Window Segmentation
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Solution Overview
Problem
The analysis of long-term electrocardiogram signals is time-consuming due to large data volumes and includes sections with noise, necessitating efficient methods to identify required analysis sections.
Innovation Solution
An electrocardiogram data processing server segments signals into variable window sizes, adjusting window size based on analysis requirements, using decision models and algorithms to classify sections as requiring analysis or not, and employing machine learning for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all recorded electrocardiogram signals are analyzed, then comprehensive diagnostic accuracy is improved, but analysis time and computational resources increase significantly
Solution Approach 1:
The patent divides the continuous electrocardiogram signal into discrete signal segments with variable window sizes. By segmenting the signal, the system can selectively analyze only certain segments rather than processing the entire continuous signal, thereby reducing analysis time while maintaining diagnostic accuracy through strategic selection of analyzable segments.
Solution Approach 2:
The patent extracts and identifies specific signal segments that contain diagnostically valuable information while excluding segments with noise or artifacts. This extraction process allows the system to focus computational resources only on relevant portions of the electrocardiogram signal, reducing overall analysis time without compromising diagnostic reliability.
2Ease of manufacture
If fixed window size is used for signal segmentation, then processing simplicity is improved, but adaptability to different signal conditions deteriorates
Solution Approach 1:
The patent implements variable window sizes for signal segmentation instead of fixed window sizes. The window size dynamically adjusts based on the characteristics of each signal segment, allowing the system to adapt to different signal conditions such as varying heart rates, noise levels, and rhythm patterns. This dynamic approach maintains processing simplicity while significantly improving adaptability.
3Adaptability or versatility
If variable window sizes are used for segmentation, then adaptability to different signal conditions is improved, but processing complexity increases
Solution Approach 1:
The patent changes the parameter of window size from fixed to variable based on signal characteristics. By adjusting this single parameter dynamically, the system achieves adaptability to different signal conditions without introducing complex multi-parameter control mechanisms. This approach balances adaptability improvement with controlled processing complexity.
4Quantity of substance
If noise sections are included in analysis, then complete data coverage is improved, but analysis quality deteriorates due to noise interference
Solution Approach 1:
The patent converts the harmful effect of noise into a beneficial selection criterion. By identifying segments with noise or artifacts, the system uses these problematic segments as indicators to exclude from detailed analysis. This approach transforms noise from a quality-degrading factor into a useful filter that improves overall analysis quality while maintaining comprehensive data coverage through selective processing.
Data Source
AI summary
The embodiments disclosed herein provide an electrocardiogram data processing server, an electrocardiogram data processing method, and a computer program. The embodiments disclosed herein further provide an electrocardiogram data processing server, an electrocardiogram data processing method, and a computer program, the electrocardiogram data processing server configured to determine whether analysis is required while segmenting an electrocardiogram signal into signal segments with variable window sizes, for instance, by changing a window size of a signal segment according to whether analysis of a previous signal segment is required.


