Biometric Data Evaluation Server Lorenz Plot Aggregation
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Solution Overview
Problem
Existing biometric data evaluation systems struggle to quantify the occurrence of arrhythmia-like abnormal values when beat-to-beat interval data is partially missing or irregularly measured, especially during non-resting states such as driving, due to poor measurement states or communication failures.
Innovation Solution
A biometric data evaluation server that includes a processor and memory, equipped with a data collection module for receiving beat-to-beat interval data and a Lorenz plot generation module to calculate and aggregate Lorenz plots, enabling the evaluation of arrhythmia-like abnormal values even with missing data by using a feature extraction model and chronic occurrence discrimination model to assess the reliability of autonomic nerve function indices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If beat-to-beat interval data is collected during work periods (non-resting states), then the applicability of biometric evaluation to real-world driving conditions is improved, but data quality deteriorates due to poor measurement states and communication failures
Solution Approach 1:
The patent applies partial action by processing only the valid, non-missing portions of beat-to-beat interval data. When data is missing due to poor measurement states or communication failures, the system selectively processes the available data segments rather than requiring complete data sets, enabling evaluation during work periods while accommodating data quality issues
Solution Approach 2:
The patent segments the beat-to-beat interval data into multiple time periods and processes each segment independently to generate separate Lorenz plots. This segmentation allows the system to handle missing data in specific segments without compromising the overall evaluation, as each segment can be analyzed separately and aggregated into a comprehensive result
2Measurement precision
If traditional arrhythmia detection methods are used on incomplete data, then measurement precision is maintained for complete data sets, but the ability to quantify arrhythmia occurrence deteriorates when data is missing
Solution Approach 1:
The patent transitions from traditional time-domain arrhythmia detection to a phase-space representation using Lorenz plots. This dimensional transformation allows the system to visualize and quantify arrhythmia-like patterns by plotting beat-to-beat intervals against subsequent intervals, creating a two-dimensional phase portrait that reveals patterns not apparent in one-dimensional time series, especially useful when data is incomplete
Solution Approach 2:
The patent performs preliminary aggregation of Lorenz plots from multiple time periods before conducting final arrhythmia quantification. By pre-processing the data to create aggregated Lorenz plots that combine information from multiple segments, the system prepares the data in advance to handle missing information, ensuring that arrhythmia occurrence can be quantified even when individual segments have data gaps
3Adaptability or versatility
If beat-to-beat interval data is measured during work periods, then the usefulness of biometric evaluation for driver fitness assessment is improved, but data completeness deteriorates due to measurement and communication issues
Solution Approach 1:
The patent merges Lorenz plots from multiple time periods into an aggregated Lorenz plot that combines information from all available segments. This merging process consolidates the partial information from each segment into a comprehensive representation, allowing the system to achieve useful driver fitness assessment results even when individual segments have incomplete data due to measurement or communication issues
Data Source
AI summary
It is provided a biometric data evaluation server including a processor and memory for evaluating biometric data, the biometric data evaluation server comprising: a data collection module configured to receive beat-to-beat interval equivalent data from the biometric data on a subject; and a Lorenz plot generation module configured to calculate a Lorenz plot from the beat-to-beat interval equivalent data at a predetermined period, and output the obtained Lorenz plots as an aggregate Lorenz plot.