ECG Event Data Segmentation for Diagnostic Report Generation
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Solution Overview
Problem
ECG monitoring generates a large amount of data, making it challenging to extract the most representative and high-quality data segments that accurately reflect ECG events for generating effective diagnostic reports.
Innovation Solution
A method that automatically identifies typical sample segments from ECG event data by evaluating signal quality, determining segment interception parameters, and generating report data to ensure the event heartbeat is centered within the segment, thereby producing comprehensive and accurate detection report data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all ECG monitoring data are processed and analyzed, then complete diagnostic information is obtained, but the data processing time and computational resources increase significantly
Solution Approach 1:
The patent extracts only the most representative and typical ECG event segments from the large volume of monitoring data. By identifying and selecting key event segments that contain the most diagnostic information, the system avoids processing all raw data while maintaining diagnostic completeness, thus resolving the contradiction between information completeness and processing time.
Solution Approach 2:
The patent creates simplified representations (copies) of ECG events by generating typical sample segments that capture the essential characteristics of each event type. These representative copies serve as sufficient diagnostic evidence without requiring analysis of the entire raw dataset, reducing processing time while preserving diagnostic reliability.
2Productivity
If representative ECG event segments are selected to reduce data volume, then processing efficiency improves, but the risk of losing important diagnostic information increases
Solution Approach 1:
The patent applies different selection criteria and quality evaluation standards to different types of ECG events. Each event type is evaluated based on its specific characteristics and diagnostic importance, ensuring that the most representative segments are selected for each category. This localized quality assessment maintains diagnostic accuracy while enabling efficient processing.
Solution Approach 2:
The patent changes the evaluation parameters dynamically based on event type and diagnostic requirements. By adjusting selection thresholds, segment lengths, and quality criteria according to specific event characteristics, the system optimizes the balance between processing efficiency and diagnostic reliability for different clinical scenarios.
3Measurement precision
If signal quality evaluation is performed on all ECG data segments, then data quality improves, but the processing complexity and time consumption increase
Solution Approach 1:
The patent divides the ECG monitoring data into discrete event segments and applies quality evaluation only to these segmented regions of interest. By evaluating quality at the segment level rather than continuously across all data, the system achieves comprehensive quality assessment with reduced computational complexity and processing time.
Data Source
AI summary
A detection report data generation method including acquiring event type information of an electrocardiogram event corresponding to electrocardiogram event data, wherein the event data has one or more pieces of event type information; screening the event data according to signal quality evaluation indexes so as to obtain report conclusion data and report entry data; carrying out quality assessment on an event segment included in the event data according to the signal quality evaluation indexes, and determining a pre-selected sample segment according to a quality assessment result; determining position information of an event heart beat in the pre-selected sample segment, and determining segment interception parameters; carrying out interception processing on the pre-selected sample segment according to the segment interception parameters so as to obtain a typical data segment; generating report graphic data according to the typical data segment; and outputting the entry data, the graphic data and the conclusion data.