Context-Aware Electrocardiogram Evaluation for Accurate Differentiation
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Solution Overview
Problem
Existing electrocardiogram evaluation methods struggle to accurately differentiate between normal and anomalous waveforms due to similarities in electrocardiograms of healthy individuals and patients with diseases like myocardial infarction or subarachnoid hemorrhage.
Innovation Solution
An electrocardiogram evaluation method that acquires electrocardiogram data and circumstance data, such as measurement location and events, to evaluate the data based on these circumstances, using models tailored to the individual's condition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrocardiogram evaluation is performed using only waveform analysis, then the evaluation process is simple and fast, but the accuracy of differentiation between normal and anomalous states is insufficient
Solution Approach 1:
The patent transitions from two-dimensional waveform analysis to three-dimensional evaluation by incorporating circumstance data (measurement location, measurement event, patient condition) as an additional dimension. This allows the system to differentiate between normal and anomalous electrocardiograms more accurately by considering not just the waveform shape but also the contextual information in which the measurement was taken.
Solution Approach 2:
The patent segments the evaluation process into distinct components: waveform analysis, circumstance data acquisition, and integrated evaluation. By separating the evaluation into these modular components, the system can process information systematically without overwhelming complexity, handling each aspect (waveform features, measurement context, patient conditions) independently before integrating them for final diagnosis.
2Measurement precision
If circumstance data is incorporated into the evaluation, then the differentiation accuracy between healthy and diseased states improves, but the data acquisition and processing complexity increases
Solution Approach 1:
The patent creates a universal evaluation framework that can handle multiple types of data (waveform data, circumstance data, patient condition data) within a single integrated system. The evaluation apparatus is designed to accommodate various data sources and measurement contexts, making it versatile enough to handle different scenarios (routine checkups, emergency situations, specific measurement locations) without requiring separate specialized systems for each.
Data Source
AI summary
An electrocardiogram evaluation apparatus of the present invention includes: an electrocardiogram acquiring unit that acquires electrocardiogram data measured from a person; a circumstance acquiring unit that acquires circumstance data representing a circumstance in which the electrocardiogram data has been measured; and an evaluating unit that evaluates the electrocardiogram data based on the circumstance data.