Onboard tagging for smart medical devices

Area of Science:

• Biomedical Engineering
• Medical Device Technology
• Signal Processing

Background:

• Traditional medical devices often function passively, lacking the ability to make operational decisions based on acquired data.
• The limitations of 'dumb' devices necessitate advancements towards 'smart' devices capable of real-time data interpretation and adaptive functionality.

Purpose of the Study:

• To introduce and describe a novel onboard tagging system for medical devices.
• To enhance medical device intelligence by enabling data-driven operational decision-making.
• To demonstrate the practical application of onboard tagging in improving device performance and data integrity.

Main Methods:

• Development of three distinct types of onboard tags: Type I (device hardware), Type II (signal statistics), and Type III (signal viability).
• Implementation of a custom wireless pulse oximeter as a use-case for demonstrating the tagging system.
• Calculation and embedding of photoplethysmogram (PPG) statistics and usability specifiers as Type II and Type III tags.

Main Results:

• The proposed onboard tagging system allows devices to embed contextual information about themselves and their data.
• Type II and Type III tags were successfully calculated and embedded into the data stream of a wireless pulse oximeter.
• The integration of onboard tags did not degrade the performance of the wireless pulse oximeter.

Conclusions:

• Onboard tagging represents a significant step towards developing 'smart' medical devices with enhanced decision-making capabilities.
• This technology can prevent the transmission of corrupt data and optimize device operations, such as reducing unnecessary wireless transmissions.
• The successful implementation in a pulse oximeter demonstrates the feasibility and effectiveness of onboard tagging for real-world medical applications.