Phase Variance Analysis Map for Rotating Excitation Wave Tracking
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Solution Overview
Problem
Existing methods struggle to accurately analyze the appearance, disappearance, and shift of the rotation center of the rotating excitation wave in biological tissues over time, as these centers dynamically change and require a comprehensive analysis map for effective monitoring.
Innovation Solution
An analysis map generating device and program that calculate phase variance values based on phase maps of excitation waves in biological tissues, generating time-series analysis maps to identify and track the rotation center, using phase variance values greater than a reference value to specify current and potential rotation centers, and employing time accumulation and binarization to analyze retention and shifts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phase variance values are calculated based on phase maps to identify rotation centers, then the ability to detect rotation centers is improved, but the ability to track dynamic changes (appearance, disappearance, shift) of rotation centers over time deteriorates
Solution Approach 1:
The system performs preliminary calculation of phase variance values at each time point before final rotation center identification. By pre-calculating these variance values across the time series, the system prepares the data structure needed to track dynamic changes, allowing both precise detection and temporal analysis without reprocessing
Solution Approach 2:
The patent transitions from analyzing single time-point phase maps to analyzing phase variance values across the time dimension. By introducing temporal dimension to the phase variance calculation, the system can track how rotation centers appear, disappear, and shift over time, converting a static detection problem into a dynamic tracking solution
2Measurement precision
If a reference value threshold is used to specify rotation centers, then the clarity of rotation center identification is improved, but the ability to detect potential or former rotation centers deteriorates
Solution Approach 1:
The patent segments the phase variance values into different categories based on their relationship with the reference value: values exceeding the threshold indicate current rotation centers, while values close to but not exceeding the threshold indicate potential or former rotation centers. This segmentation allows the system to preserve information about different states of rotation centers simultaneously
Solution Approach 2:
The system uses parameter changes in the phase variance values relative to the reference value to distinguish between different rotation center states. By monitoring how the variance parameter changes over time and compares to the reference threshold, the system can identify transitions between current, potential, and former rotation centers, preserving temporal evolution information
3Measurement precision
If time series of phase variance values are used to generate analysis maps, then the ability to analyze dynamic changes is improved, but the computational complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for rotation center analysis by calculating phase variance values and comparing them against a reference threshold. Rather than processing entire phase maps or all possible features, the system extracts the variance metric which directly indicates rotation center presence, reducing computational burden while maintaining analytical capability
Solution Approach 2:
The system creates simplified representations (analysis maps) that copy the essential temporal evolution of rotation centers from the complex time series of phase variance values. By generating visual analysis maps that represent the temporal patterns, the system reduces complex computational data into interpretable formats without losing the dynamic change information
Data Source
AI summary
An aspect of the present disclosure calculates a phase variance value indicating a degree of variance of a phase in a surrounding of each position in a biological tissue, based on phase values of excitation wave at respective positions in the biological tissue that acts in response to excitation caused by propagation of the excitation wave in the tissue, and generates an analysis map, based on a time series of at least part of the phase variance values at the respective positions. Since the phase variance value indicates the degree of variance of the phase in the surrounding, a position having a large degree of variance of the phase in the surrounding may be specified as a rotation center of rotating excitation wave.