Ventilator Disconnection Detection via Adaptive Flow Thresholds
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Solution Overview
Problem
Current medical ventilation systems face challenges in reliably detecting disconnections in the patient interface system, leading to inadequate ventilation and high false alarm rates due to insensitive alarm threshold settings.
Innovation Solution
An apparatus that monitors the time curve of respiratory gas flow using sensors and data evaluation to trigger alarms, with adjustable limit values and automatic adaptation based on patient interface data, reducing false alarms and improving detection reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed detection thresholds are used for alarm triggering, then the alarm system is simple to operate, but the false alarm rate increases and detection reliability decreases
Solution Approach 1:
The alarm threshold is transformed from a fixed value to a dynamically adaptive threshold that automatically adjusts based on real-time respiratory flow measurements. The system continuously learns the patient's normal respiratory patterns and adapts the threshold accordingly, eliminating the need for manual fixed threshold settings while reducing false alarms and improving detection reliability.
Solution Approach 2:
The alarm system performs self-calibration by automatically adapting its detection threshold based on measured respiratory flow data. The system serves itself by continuously monitoring and adjusting the threshold without external intervention, thereby eliminating the trade-off between ease of operation and detection reliability.
2Loss of time
If sensitive alarm thresholds are set to trigger alarms in good time, then detection timeliness improves, but the false alarm rate increases
Solution Approach 1:
The system implements continuous feedback by monitoring respiratory flow patterns over time and using this information to dynamically adjust the alarm threshold. The feedback mechanism allows the system to distinguish between genuine disconnections and normal variations in respiratory flow, enabling timely detection while minimizing false alarms.
Solution Approach 2:
The system performs preliminary adaptation during a calibration period before normal operation, establishing a baseline of the patient's respiratory patterns. This preliminary action enables the system to set appropriate detection thresholds in advance, allowing timely alarm triggering without increasing false alarm rates during subsequent operation.
3Reliability
If additional components such as filters or connection tubes are added to the patient interface system, then the system becomes more robust, but the complexity of the system increases
Solution Approach 1:
The respiratory flow sensor serves multiple functions: it monitors for disconnections, tracks ventilation patterns, and enables adaptive threshold adjustment. This multi-functionality eliminates the need for additional specialized components, maintaining system robustness while avoiding increased complexity.
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
The solution effectively distinguishes between disconnections and ventilation curves, reducing false alarms and ensuring timely and reliable alarm triggering, thereby enhancing patient safety and ventilator performance.
Implementation Method 1
The detection can be carried out by way of a pressure or flow measurement
Implementation Method 2
The detection can be carried out by way of a pressure or flow measurement
Implementation Method 3
this CO2 sensor detects the end tidal carbon dioxide (etCO2) or the CO2 content by way of a transcutaneous measurement
Data Source
AI summary
Disclosed are an apparatus and a method for monitoring the disconnection of a patient interface system during the ventilation, in which values which are indicative for the time curve of the respiratory gas flow are established and subjected to data evaluation, and wherein an alarm is triggered on the basis of the data evaluation if at least one value which is indicative for the time curve of the respiratory gas flow deviates from a specific limit value for a specific period of time.