Glucose Waveform Alignment for Preserving Clinically Significant Features
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Solution Overview
Problem
Existing medical devices for diabetes management, such as continuous glucose monitors, struggle to accurately identify long-term trends and patterns in glucose levels due to idiosyncratic variations caused by events like eating and exercising, which can be obscured by temporal averaging, leading to loss of critical information.
Innovation Solution
A system that uses signal processing techniques, such as dynamic time warping, to realign and remap glucose data, ensuring clinically significant features are aligned across different periods, allowing for better identification of trends and patterns without losing critical information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If temporal averaging is used to smooth glucose data across multiple periods, then noise is reduced and general trends are visible, but critical information is lost due to obscuring of idiosyncratic variations
Solution Approach 1:
The patent segments the glucose data analysis into two distinct components: (1) temporally averaged data for identifying general trends and patterns, and (2) individually aligned waveforms for preserving critical information. This segmentation allows both objectives to be achieved simultaneously without information loss.
Solution Approach 2:
The patent merges the results of temporal averaging with the preserved individual waveform data to create a comprehensive analysis system. The aligned waveforms are overlaid and compared while maintaining their unique characteristics, combining the benefits of both approaches.
2Loss of information
If glucose data from different periods are directly compared without alignment, then idiosyncratic variations are preserved, but temporal misalignment obscures clinically significant patterns
Solution Approach 1:
The patent applies dynamic time warping, a dynamic programming technique, to flexibly align waveforms that may have temporal distortions. This dynamic approach adjusts the timing of features within each waveform to achieve optimal alignment while preserving the underlying glucose patterns.
Solution Approach 2:
The patent changes the temporal parameters of individual waveforms through alignment transformations, adjusting their timing characteristics to match reference waveforms. This allows for accurate comparison while maintaining the unique glucose response patterns of each period.
3Measurement precision
If signal processing techniques are applied to align glucose waveforms, then clinically significant features are temporally aligned for better comparison, but computational complexity increases
Solution Approach 1:
The patent creates aligned copies of the original glucose waveforms through digital signal processing. Instead of modifying the original data, it generates transformed copies that are temporally aligned, allowing for accurate comparison while preserving the source data integrity.
Solution Approach 2:
The patent replaces manual or mechanical data comparison methods with automated digital signal processing techniques. The use of algorithms such as dynamic time warping automates the alignment process, reducing the need for manual intervention and complex mechanical systems.
Data Source
AI summary
A system includes an implantable medical device configured to measure blood-glucose concentration based on cardiac activity. The system further includes processing circuitry configured to generate, based on the plurality of periods, a plurality of waveforms representative of the blood-glucose concentration. The processing circuitry is further configured to identify at least one clinically significant feature that is present in each waveform. The processing circuitry is further configured to modify one or more of the plurality of waveforms such that the at least one feature is temporally aligned across the plurality of waveforms.