AI IV Infiltration Detection with Multi-Sensor Monitoring
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Solution Overview
Problem
Conventional IV therapy methods rely heavily on subjective assessments and manual monitoring, leading to delayed detection of complications such as infiltration, extravasation, occlusions, and air embolisms, which can cause significant patient harm and increase healthcare costs.
Innovation Solution
An apparatus and method utilizing real-time monitoring and AI-driven analysis to detect IV infiltration through sensors that measure pressure, flow rate, and temperature, with automated control of fluid delivery parameters, including clamps and syringe mechanisms, to provide precise and proactive management of IV therapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time monitoring with sensors and AI-driven analysis is implemented, then detection precision and response time improve, but device complexity increases
Solution Approach 1:
The monitoring system is divided into separate functional modules: pressure sensors, flow rate sensors, temperature sensors, AI analysis unit, and control mechanisms. Each module performs a specific function, allowing the complex system to be managed through modular components that can be independently optimized and maintained.
Solution Approach 2:
An AI-driven analysis unit serves as an intermediary between the raw sensor data and the clinical decision-making process. This intermediary processes and interprets multiple sensor inputs, transforming complex data streams into actionable insights about IV infiltration, thereby simplifying the overall system architecture while maintaining high detection precision.
2Productivity
If automated control of fluid delivery parameters is implemented, then productivity and safety improve, but device complexity increases
Solution Approach 1:
The system incorporates automated control mechanisms that adjust fluid delivery parameters based on real-time sensor feedback without requiring constant manual intervention. The apparatus monitors IV therapy parameters continuously and automatically responds to detected anomalies, enabling the system to serve itself and reducing the burden on healthcare providers.
Solution Approach 2:
The system implements closed-loop feedback control where sensors continuously monitor fluid delivery parameters and patient response, and the control mechanisms automatically adjust delivery based on this feedback. This ensures optimal therapy delivery while maintaining simplicity through automated regulation rather than manual adjustment.
3Reliability
If multiple sensors monitoring pressure, flow rate, and temperature are used, then reliability of detection improves, but device complexity increases
Solution Approach 1:
Multiple sensor types (pressure, flow rate, temperature) are integrated into a unified monitoring system with a common data processing and analysis platform. The sensors work together synergistically, with their combined data fed into the AI analysis unit that correlates inputs from all sensors to detect IV infiltration more reliably than any single sensor could alone.
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
Enhances patient safety by enabling early detection and proactive management of IV complications, reducing the risk of tissue damage and improving clinical efficiency through accurate and timely intervention.
Implementation Method 1
monitoring at least one of pressure, temperature, or flow rate with sensors of the first device
Implementation Method 2
monitoring at least one of pressure, temperature, or flow rate with sensors of the first device
Implementation Method 3
monitoring at least one of pressure, temperature, or flow rate with sensors of the first device
Data Source
AI summary
An apparatus and method for detecting intravenous (IV) infiltration and managing fluid delivery in an IV setup are disclosed. The apparatus includes a controller with an artificial intelligence (AI) engine to process real-time and historical IV parameters, a communication module for remote monitoring and control, and a sensing arm with sensors to monitor parameters like pressure, flow rate, temperature, acoustic signals, and air bubbles within the IV line. A first clamp and a second clamp are attachable to the IV line to selectively occlude fluid flow. Syringe holders connected to the IV line via an aggregation tube or Luer lock include a plunger control mechanism for adjustable injection timing, pressure, and volume. Monitored parameters are analyzed to detect IV infiltration, blockages, or abnormalities, and alerts are transmitted to medical professionals via the communication module or displayed on an integrated user interface, enabling real-time detection and dynamic adjustments.