Heartbeat Interval Correction Using Outlier Level Parameters
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Solution Overview
Problem
Existing bioinformation acquisition systems face challenges in accurately correcting heartbeat intervals due to outliers, which can lead to incomplete or inaccurate analysis, especially when outliers are not appropriately removed or when interpolation methods fail to provide continuous data.
Innovation Solution
A bioinformation acquiring apparatus that includes a processor to acquire and correct heartbeat intervals by calculating outlier level parameters, selecting between correction procedures based on these parameters, and applying either correction terms or interpolation methods to ensure accurate and continuous data acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If step interpolation is used to correct outliers in heartbeat intervals, then the data continuity is improved, but the accuracy deteriorates when outliers are not appropriately removed first
Solution Approach 1:
The patent segments the correction process into two distinct stages: first removing outliers using statistical criteria (IQR method), then applying step interpolation to fill gaps. This segmentation ensures that interpolation operates on clean data, resolving the contradiction between continuity and accuracy.
Solution Approach 2:
The patent performs outlier removal as a preliminary action before applying interpolation. By identifying and removing outliers first using the interquartile range method, the system ensures that subsequent interpolation operates on valid data, thereby maintaining both continuity and accuracy.
2Measurement precision
If outlier removal is performed before interpolation, then the accuracy of corrected values is improved, but the complexity of the correction procedure increases
Solution Approach 1:
The patent divides the correction procedure into two clear segments: outlier removal using statistical criteria, followed by interpolation. This segmentation makes the complex procedure more manageable and systematic, reducing operational complexity while maintaining accuracy.
Solution Approach 2:
The patent uses parameter-based outlier detection (IQR method with thresholds of 1.5 and 3.0) to automatically identify and remove outliers. This parameter-driven approach simplifies the correction procedure by providing clear, objective criteria for outlier removal before interpolation.
3Device complexity
If a fixed interpolation method is used for all cases, then the device complexity is reduced, but the adaptability to different outlier scenarios deteriorates
Solution Approach 1:
The patent employs parameter-based outlier detection using the interquartile range method with configurable thresholds (1.5 for mild outliers, 3.0 for extreme outliers). This parameter-driven approach provides adaptability to different scenarios while maintaining a relatively simple fixed interpolation procedure for filling gaps.
Solution Approach 2:
The patent uses statistical feedback (IQR calculations and outlier detection) to determine which data points require correction. This feedback mechanism allows the system to adaptively identify outliers in different scenarios while using a consistent interpolation method to fill gaps, balancing simplicity and versatility.
Data Source
AI summary
A bioinformation acquiring apparatus includes at least one processor; and a memory configured to store a program to be executed in the processor. The processor acquires bioinformation in a chronological order; derives outlier level parameters, the outlier level parameter indicating a level of inclusion of outliers of the bioinformation in pieces of bioinformation acquired within a first duration; derives correction terms based on the bioinformation after removal of the outliers of the bioinformation from pieces of bioinformation acquired within a second duration that is longer than the first duration; selects one or both of a first correction procedure and a second correction procedure based on the outlier level parameters, as a correction procedure, the first correction procedure using the correction terms, the second correction procedure involving interpolation irrelevant to the correction terms; and corrects the outliers of the bioinformation within the first duration by the selected correction procedure.