Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Anesthesiology

Background:

• Continuous anesthetic drug monitoring is crucial for personalized dosing and patient safety.
• Existing methods for propofol detection lack in-situ, continuous measurement capabilities and rely on bulky equipment.
• There is a need for portable, real-time monitoring solutions in clinical anesthesia.

Purpose of the Study:

• To develop and present a novel electronic system for continuous, in-situ monitoring of propofol in human serum.
• To create a compact, wireless, and low-power device for real-time anesthetic drug analysis.
• To validate the performance of the developed system in clinically relevant conditions.

Main Methods:

• Development of a pen-shaped device integrating a needle-shaped electrochemical sensor.
• Implementation of a quasi-digital front-end and machine learning-based data processing.
• Wireless, battery-operated system with Bluetooth Low Energy (BLE) communication for data transfer.
• Characterization and testing in undiluted human serum at 37°C.

Main Results:

• The system achieved a limit of detection of 3.8 μM for propofol, meeting application requirements.
• The electronic system is 59% smaller and 81% more power-efficient than current state-of-the-art solutions.
• Machine learning classification enabled reliable data processing for up to twenty continuous measurements.

Conclusions:

• The novel pen-shaped device offers a significant advancement in continuous propofol monitoring.
• This technology enables real-time, in-situ drug level assessment, facilitating personalized anesthesia.
• The system's compact size, low power consumption, and wireless capabilities make it suitable for clinical application.