Blood Flow Control Device Error Detection via Sensor Feedback
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Solution Overview
Problem
Medical devices, such as balloon catheters, are prone to errors due to damage during shipment or use, leading to potential life-threatening consequences, and existing automated systems lack effective error detection and response mechanisms.
Innovation Solution
A blood flow control system with sensors and controllers that monitor physiologic conditions and pressures, identifying errors and transitioning to a manual mode or inhibiting functions to prevent unsafe operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated blood flow control systems are used, then productivity and precision are improved, but reliability deteriorates due to undetected errors from damage or wear
Solution Approach 1:
The system performs preliminary error detection by comparing current sensor data against target data before automated actions are executed. This advance checking mechanism identifies potential errors from damage or wear beforehand, preventing unreliable automated operations while maintaining productivity.
Solution Approach 2:
The system implements continuous feedback loops where sensors monitor physiologic conditions and pressures, controllers compare data against targets, and error conditions trigger automatic mode transitions. This feedback mechanism ensures reliability by constantly verifying system state while allowing automated operation to proceed when conditions are normal.
2Reliability
If error detection mechanisms are added to automated systems, then reliability is improved, but device complexity increases
Solution Approach 1:
The error detection system uses the existing sensor infrastructure for dual purposes: normal operation monitoring and error detection. The same sensors that measure physiologic conditions during treatment also detect errors by comparing data against targets, eliminating the need for separate detection hardware and reducing overall system complexity.
Solution Approach 2:
The system performs self-diagnosis by automatically comparing its own sensor data against target values and identifying errors without external intervention. This self-monitoring capability provides reliable error detection while minimizing additional complexity, as the system serves its own diagnostic needs using existing components.
3Measurement precision
If continuous monitoring of physiologic conditions is performed, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system performs monitoring and data comparison at periodic intervals rather than continuously, achieving sufficient measurement precision for clinical decision-making while reducing energy consumption. The controllers compare sensor data against targets at scheduled times, maintaining accuracy where needed while conserving battery power during portable operation.
Data Source
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AI summary
Systems and methods for blood flow control are described herein. In some variations, a blood flow control system may comprise a blood flow control device. The blood flow control device may be placed within a body of a patient and may comprise an expandable member and a sensor. The sensor may be configured to measure at least one of a physiologic condition of the patient and a pressure associated with the expandable member. The blood flow control system may include at least one controller communicably coupled to the sensor to: receive data indicative of at least one of the physiologic condition of the patient and the pressure associated with the expandable member from the sensor, compare the received data with target data, identify at least one error based on the comparison, and in response to identifying the error, inhibit at least one function of the blood flow control system.