BioStream: a system architecture for real-time processing of physiological signals

Area of Science:

• Biomedical Engineering
• Computer Science
• Data Science

Background:

• Continuous physiological monitoring can significantly improve chronic disease patient outcomes.
• Advancements in sensor technology facilitate real-time data acquisition.
• Managing and analyzing continuous physiological data streams presents significant computational challenges.

Purpose of the Study:

• To introduce BioStream, a novel software solution for real-time management of physiological sensor streams.
• To present a scalable, operator-based architecture for processing and analyzing physiological data.
• To demonstrate the application of BioStream in multipatient, real-time physiological monitoring.

Main Methods:

• Developed BioStream on a general-purpose stream processing software architecture.
• Utilized plug-in analysis components composed via a graphical programming environment.
• Implemented a scalable architecture supporting distributed environments from desktops to server farms.

Main Results:

• BioStream provides real-time response and data persistence in a distributed setting.
• The system successfully handles multipatient, real-time physiological signal monitoring.
• Enabled efficient analysis, indexing, and visualization of physiological data streams.

Conclusions:

• BioStream offers a robust and scalable solution for managing complex physiological data.
• The software architecture facilitates real-time analysis and visualization for improved patient monitoring.
• This approach has the potential to enhance the quality of life for individuals with chronic conditions.