AI-Driven Adaptive Cuff Inflation for Non-Invasive Blood Pressure Monitoring
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Solution Overview
Problem
Current noninvasive blood pressure monitoring systems often miss changes in blood pressure between scheduled measurements, and frequent cuff inflation can be uncomfortable and unnecessary for patients with stable blood pressure.
Innovation Solution
A noninvasive blood pressure monitoring system that uses a trained artificial intelligence model to analyze data from patient sensors, predicting changes in blood pressure and triggering the NIBP sensor only when such changes are likely, thereby reducing unnecessary cuff inflations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cuff inflation is performed at scheduled intervals, then blood pressure measurements can be obtained, but patient comfort deteriorates due to frequent unnecessary inflations
Solution Approach 1:
The system continuously monitors blood pressure and uses feedback from the monitoring data to dynamically adjust the timing of subsequent cuff inflations. When blood pressure is stable, the system extends the interval between measurements, reducing unnecessary inflations and improving patient comfort while maintaining measurement accuracy when needed.
Solution Approach 2:
The system transitions from a static scheduled measurement approach to a dynamic adaptive scheduling approach. The measurement interval is continuously adjusted based on real-time blood pressure variability and clinical context, allowing the system to optimize between measurement frequency and patient comfort dynamically.
2Ease of operation
If cuff inflation frequency is reduced, then patient comfort improves, but detection of rapid blood pressure changes may be delayed
Solution Approach 1:
The system uses continuous feedback from blood pressure monitoring to automatically increase the frequency of cuff inflations when rapid changes are detected. This feedback mechanism ensures that measurement frequency adapts to clinical needs, maintaining reliable detection of rapid changes while avoiding unnecessary inflations during stable periods.
Solution Approach 2:
The system performs preliminary continuous non-invasive monitoring to detect trends and predict potential rapid blood pressure changes. When changes are anticipated, the system proactively increases measurement frequency before critical events occur, ensuring timely detection while maintaining comfort during stable periods.
Data Source
AI summary
A noninvasive blood pressure sensor may be activated based on data from one or more patient sensors, such as a pulse oximetry sensor. In an embodiment, when the sensor data is determined to be characteristic of or associated with a likely change in blood pressure, the noninvasive blood pressure sensor is activated to acquire a blood pressure measurement. A trained model may be used to determine a likelihood od the sensor dating being characteristic of or associated with the change in blood pressure.