Supriya isn’t new to being a state science fair laureate. Last year, this young fencer won the WSSEF award for measuring her muscles’ reaction time before and after warm-ups to improve her lunge performance.
This time around, she added the brain and heart into the equation, measuring her EEG, EKG and EMG with and without a 15-minute warm-up.
Every fencer will hear it countless times: warm-ups are a MUST. Do them and they’ll bump up your performance. Skip them and you may end up hurting yourself.
But not every fencer will ask why! Supriya Nair, a busy sixth-grader from Redmond, WA, decided to conduct an experiment and find out what the correlation is between exercise and performance in her favorite sport. Where other people see a self-evident truth that doesn’t need any questioning, this scientifically-minded middle-schooler saw a hypothesis that she can poke through to test it, quantify it, and prove it!
And what better way to do that than to:
sport a set of electrodes of a Neuron SpikerBox to capture an EMG signal from her right hand and right leg as she lunges,
measure her muscles’ reaction time from rest to touche in controlled circumstances, with and without 15-minute warm-ups, and compare the findings.
“I’d always hear it from coaches that I needed to do pre-bout exercise. But there was no quantitative data that would support it, just qualitative. And frankly, I was not very disciplined in warm-ups,” Supriya told us in a Zoom interview. That’s how she came up with the idea to eavesdrop on her muscles’ electrical activity using the SpikerBox her dad got her, and measure it to see whether it adds up to the hypothesis. And boom! Pre-bout exercise lasting only 15 minutes can improve a fencer’s performance by a whopping 15%, she discovered.
Call for HS Teachers and Undergraduates in Biology, Engineering and the Arts:
Calling all AI and neuroscience nerds (AND nerd wannabes): We are back!
After taking a hiatus due to a global pandemic, we are proud to announce that we are returning with a very special guest star: TinyML! Tiny Machine Learning (TinyML) is a deep learning toolkit made for tinkers, educators and for those who want to know how machine learning really works… and we are excited about what it could mean to neuroscience educators!
For the first time ever, we are inviting K12 teachers to be a part of our summer program! Learn how to integrate Machine Learning into your project-based lessons and help provide feedback on our teaching tools and project curricula!
This summer, our fellowship program will focus on developing creative, wearable, and fun human-machine interfaces that can react with your brain waves, muscle, heart and eye movements using Deep Learning. You will learn the basics of neuroscience, computational thinking, machine learning, electronics, and will go from start to finish on developing your very own project. You will get support from our in house scientists and experts through every stage of your project.
Our AI Fellowship program will be designed around 2 cohorts. The first are undergraduates with a background in Neuroscience, Art, Electrical, Mechanical or Computer Engineering, where they learn how to develop their own innovations, conduct fun experiments around computational neuroscience. We are also recruiting High School teachers interested in learning about AI and how to teach hands-on AI lesson plans in their classroom. Teachers will participate remotely from around the country (1hr / week), and will help guide our projects for optimal use in the classroom.
This fellowship is focused on developing computational skills. To do so, you will learn how to read and write peer-reviewed papers, discuss and plan around ethical concerns of using AI, learn how to develop a project and collect data, how to analyze and test results, how to make your own scientific poster and present your work to the academic communities, and finally how to speak to the public about your work. This program is unique: instead of working on a small part of the bigger project… all fellow projects are yours alone! We will support and guide you through, but you will experience everything from inception to publication… much like the life of a graduate researcher. No prior research experience is necessary or required!