Capnogram Construction from Physiological Waveforms
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Solution Overview
Problem
Current methods for monitoring respiration in critical care situations require multiple specific equipment and sensors, which can be burdensome for patients and congest medical facilities. Additionally, traditional capnography methods involve direct measurement of CO2 levels, which may not be feasible in all situations.
Innovation Solution
A computational method to construct a capnogram from a physiological waveform using a medical monitoring system that includes a sensor and a computational processing system. This method involves obtaining a physiological waveform, filtering it to yield a respiration waveform, and constructing a capnogram based on the respiration waveform. The capnogram can be constructed using mathematical bases selected from a database, and the process can be repeated for each respiration cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional capnography methods are used to directly measure CO2 levels, then measurement precision of respiration is improved, but device complexity and facility congestion increase due to requiring multiple specific equipment and sensors
Solution Approach 1:
The patent applies universality by enabling existing physiological sensors (designed for other measurements) to serve dual purposes - their original function plus respiration monitoring through capnogram construction. The computational processing system extracts respiratory information from general physiological waveforms, making the monitoring system multi-functional and eliminating the need for dedicated CO2 sensors.
Solution Approach 2:
The patent creates a computational copy of the traditional capnogram waveform by processing existing physiological signals through filtering and mathematical transformations. Instead of directly measuring CO2, the system reconstructs the capnogram shape and characteristics from alternative physiological data, providing an indirect but accurate representation of respiratory status.
2Measurement precision
If multiple specific equipment and sensors are deployed for comprehensive physiological monitoring, then measurement precision of various parameters is improved, but ease of operation deteriorates due to burden on patients and congestion in medical facilities
Solution Approach 1:
The system enables existing physiological monitoring equipment to perform multiple functions simultaneously - measuring their primary parameters while also extracting respiratory information through the computational processing system. This eliminates the need for separate dedicated sensors and reduces overall equipment requirements.
Solution Approach 2:
The patent merges the respiration monitoring function with existing physiological monitoring systems by integrating the computational processing system that can extract respiratory waveforms from general physiological signals. This consolidation combines multiple monitoring capabilities into a unified system, reducing equipment count and simplifying operation.
3Reliability
If direct CO2 measurement is performed using gas analyzers, then reliability of capnogram data is improved, but device complexity increases due to requiring mainstream or sidestream CO2 sensors
Solution Approach 1:
The system creates a computational replica of the true capnogram waveform by processing physiological signals through filtering and mathematical transformations. This reconstructed waveform copies the essential characteristics and phases of actual CO2 measurement without requiring physical CO2 sensing equipment.
Solution Approach 2:
The computational processing system acts as an intermediary that translates existing physiological signal data into capnogram-formatted output. Instead of directly measuring CO2, the system uses mathematical processing to bridge between available physiological signals and the desired capnogram representation.
Data Source
AI summary
Systems and methods identify respiration signals in a patient, which can be important for monitoring respiratory health. A respiration signal can be extracted based on data within a physiological waveform, such as a blood pressure waveform, a blood flow waveform, an electrocardiogram, or a plethysmogram. The physiological waveform can be filtered to identify and extract the respiration signal, which can be utilized to construct a capnogram waveform. A respiration rate can be calculated from the respiration signal or from the constructed capnogram waveform.