Friday November 12 9:00 – Friday November 12 9:35 in Auditorium

Biosensor Machine Learning with Julia

Matthijs Cox

Prior knowledge:
No previous knowledge expected

Summary

Biosensors allow you to perform data science on your own bio signals, like brainwaves, heartrates and electrical muscle signals. How cool is that?! In this talk I'll briefly introduce you to the open source community growing around biosensor devices. As an example I will demonstrate a machine learning system I built with my own biosensors, where I choose Julia to keep everything high performing.

Outline

Description

Biosensors allow you to perform data science on your own bio signals, like brainwaves, heartrates and electrical muscle signals. How cool is that?! In this talk I'll briefly introduce you to the open source community growing around biosensor devices.

I will explain briefly what biosensors are. What kinds are available to consumers and engineers. What sensors do I have myself. How to obtain the data from them.

For the latter part I will introduce the open source BrainFlow library, for which I am a voluntary open source developer. It is a fast performing c++ library that's easy to use, can be deployed anywhere and has many language bindings, including Python and Julia. BrainFlow allows anyone with a biosensor to extract their own data with little hassle and build applications in their favorite programming language.

I will show code examples for how to obtain data from such biosensors, using Julia and BrainFlow. I specifically demonstrate gesture predictions using myo-electric muscle sensors. This topic I investigated for building open source bionic arm control systems. I would like to do a live demo, or at least show videos of the live data streaming and machine learning predictions. You can control real devices with these algorithms, like bionic arms, but I have also used it to play video games.

The live data processing, data streaming and machine learning predictions need to be as fast as possible, so I wrote all my code in Julia to show it is performant enough for this task.