Optical Air Bubble Detection in Dialysis Tubing
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Solution Overview
Problem
Hemodialysis induces fluid balance imbalances due to rapid blood volume changes, leading to complications like hypotension, and existing optical air bubble detection methods are affected by factors such as blood hematocrit concentration, oxygenation level, tubing discoloration, and saline delivery, making it challenging to accurately detect air bubbles using single light wavelength absorbance.
Innovation Solution
The use of a normalized ratio of absorbance intensity from two light wavelengths to eliminate common mode factors, allowing for robust and reliable detection of air bubbles by canceling out effects of medium color, tubing color, and temperature, thereby improving the sensitivity and accuracy of air bubble detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single light wavelength absorbance is used for air bubble detection, then the detection method is simple, but the detection accuracy is reduced due to interference from blood hematocrit concentration, oxygenation level, tubing discoloration, and saline delivery
Solution Approach 1:
The detection method is segmented into two separate wavelength measurements (first wavelength and second wavelength) that are performed simultaneously or sequentially. Each wavelength provides independent absorbance data that, when combined through ratio calculation, eliminates interference from common sources such as hematocrit concentration, oxygenation level, tubing discoloration, and saline delivery. This segmentation allows the system to maintain simplicity while achieving high detection accuracy.
Solution Approach 2:
The system changes the parameter of light wavelength by using two distinct wavelengths instead of a single wavelength. This parameter change enables the detection system to differentiate between absorbance caused by air bubbles and absorbance caused by other factors. By measuring at multiple wavelengths and calculating their ratio, the system achieves accurate air bubble detection while compensating for variations in blood properties and tubing characteristics.
2Measurement precision
If multiple factors affecting absorbance are considered, then detection accuracy improves, but the complexity of the detection system increases
Solution Approach 1:
The invention extracts and isolates the specific signal component related to air bubbles by using ratio calculation of absorbance at two different wavelengths. Common mode factors such as hematocrit concentration, oxygenation level, tubing discoloration, and saline delivery affect both wavelengths similarly and are effectively canceled out in the ratio. This extraction approach allows the system to focus on air bubble detection while automatically compensating for other interfering factors, maintaining system simplicity.
Solution Approach 2:
The ratio of absorbance intensities at two wavelengths serves as an intermediary parameter that mediates between the raw absorbance measurements and the final air bubble detection decision. This intermediary ratio calculation transforms complex multi-factor absorbance data into a simplified metric that directly indicates the presence of air bubbles, reducing system complexity while improving detection accuracy.
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
This method effectively reduces false alarms and enhances the reliability of air bubble detection, preventing arterial occlusion and ensuring safer hemodialysis by accurately identifying air bubbles and avoiding further complications from negative pressure.
Implementation Method 1
determining a normalized ratio of light absorbance intensity of the two light wavelengths in the blood flow path
Data Source
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Figure 2
Figure 2A
AI summary
Embodiments of the disclosure provide a system and method for detection of a transient air bubble in an arterial blood flow path during dialysis (e.g., hemodialysis). The system uses measurements from an optical sensor to remove one or more effects of common factors affecting the absorbance of the light incident on the arterial tubing. These factors include color of medium within the arterial tubing, tubing color, angle of illumination, and temperature of the optical detector. A variance of the measurements from the optical sensor are used to determine whether an air bubble is present.