Streaminghub - A Realtime Biosignal Processing Framework for Lab Scale Experimentation

Yasith Jayawardana

Abstract: In human subjects research, biosignals such as eye movements, heart rate, and brain activity, are often collected and analyzed to find patterns with tangible real-world implications. Modern advancements in technology have sparked interest towards analyzing biosignals in realtime. When developing such algorithms, one may expect to find free, open-source tools that provide easy access to live, recorded, and simulated data streams. Yet, biosignal interfaces are often vendor-specific, making cross-vendor biosignal streaming non-trivial. Likewise, reading biosignal datasets is also non-trivial, as their content may be arranged quite differently. To combat this divide, we provide the scientific community with a realtime biosignal processing framework, Streaminghub, which decouples data access from science. Streaminghub provides simple APIs to stream biosignal data and is extensible to new devices and data formats. It consists of three key components: (1) DFDS – JSON schema to describe data sources by the streams they generate, (2) Curator – a web application to create DFDS-enriched streamable datasets, and (3) DataMux – an API to define and run pipelines on biosignal data streams with less code. Through user studies, we establish the need for Streaminghub, and find Streaminghub to generate clear, reusable code, and provide excellent usability for realtime biosignal analysis. Through case studies, we show that Streaminghub simplifies realtime biosignal processing. Through performance tests, we show that Streaminghub yields stable performance across different biosignals and runtimes.