Autoregulation Data Determination via Coherence Analysis
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Solution Overview
Problem
Existing methods for monitoring autoregulation in mammals fail to account for factors that can confound autoregulation determination or measurement, leading to inadequate perfusion and ischemia in organs due to varying vascular reactivity responses.
Innovation Solution
A method and apparatus using continuous sensing of tissue oxygenation parameters and blood pressure levels, employing frequency domain transformations to determine coherence values indicative of autoregulation state, with separate recent and historical profiles displayed for comprehensive analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional autoregulation monitoring methods are used, then the monitoring process is simple, but the measurement precision is insufficient due to failing to account for confounding factors
Solution Approach 1:
The patent segments the monitoring system into multiple independent measurement components: tissue oximetry sensing, blood pressure sensing, and confounding factor sensing (respiratory rate, end-tidal CO2, temperature). Each component measures a specific parameter, and their combined data provides comprehensive autoregulation assessment, resolving the contradiction between measurement precision and device complexity by breaking down the complex measurement task into manageable segments
Solution Approach 2:
The patent introduces coherence analysis as an intermediary computational method that processes the raw data from multiple sensors. By calculating the coherence between tissue oxygenation variations and blood pressure variations while accounting for confounding factors through spectral analysis, the system achieves precise autoregulation measurement without requiring direct complex hardware integration
2Adaptability or versatility
If static autoregulation assessment is used, then the device complexity is low, but the adaptability is insufficient due to inability to capture individual variations and historical trends
Solution Approach 1:
The patent performs preliminary data processing by continuously collecting and storing historical autoregulation data, respiratory rate, end-tidal CO2, and temperature measurements before clinical decision-making is needed. This preliminary accumulation of individual-specific baseline data enables the system to adapt to individual variations and provide personalized autoregulation profiles, resolving the contradiction between adaptability and processing complexity by preparing data in advance
Solution Approach 2:
The patent implements dynamic autoregulation monitoring that continuously updates coherence values and autoregulation profiles in real-time as new data becomes available. The system transitions from static assessment to dynamic tracking, allowing the autoregulation profile to adapt to changing physiological conditions and individual variations, thereby achieving versatility without excessive processing complexity through continuous incremental updates
3Reliability
If comprehensive continuous monitoring is implemented, then the reliability of autoregulation determination is improved, but the loss of time for data processing increases
Solution Approach 1:
The patent implements periodic coherence analysis where the system continuously monitors physiological parameters but performs comprehensive coherence calculations and autoregulation assessments at predetermined time intervals or when specific triggers occur. This periodic processing approach maintains reliable autoregulation determination by regularly updating assessments while minimizing continuous heavy computation, thereby reducing data processing time loss
Solution Approach 2:
The patent prioritizes processing of critical data by rushing through essential coherence calculations when autoregulation status changes or clinical events occur, while skipping or deferring less critical processing tasks. This selective processing approach maintains high reliability for critical autoregulation determination while reducing overall data processing time by focusing computational resources on the most important measurements
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides accurate and dynamic monitoring of autoregulation, accounting for individual variations and historical trends, thereby preventing organ perfusion issues by enhancing the understanding of vascular reactivity.
Implementation Method 1
a near infra-red spectroscopy (NIRS) tissue oximeter
Data Source
Figure 1~2
Figure 3~4A
Figure 4B~5
AI summary
A method for providing autoregulation function information is provided. The method includes: a) continuously sensing a tissue region with a tissue oximeter during a period of time, the sensing producing first signals representative of at least one tissue oxygenation parameter; b) continuously measuring a blood pressure level during the period of time using a blood pressure sensing device, the measuring producing second signals representative of the blood pressure level of the subject; c) evaluating the at least one tissue oxygenation parameter using the first signals and the blood pressure level using the second signals, relative to one another; d) producing a recent profile of autoregulation data using the first and second signals from a recent portion of the period of time; e) producing a historical profile of autoregulation data using the first and second signals from a historical portion of the period of time.