About seven months ago, Chantilly High School student Gautham Ramachandran came across a man in a wheelchair on the sidewalk.
Ramachandran said he was inspired by the man who was navigating life without his legs. Ramachandran approached him, and they exchanged pleasantries.
In the days that followed, Ramachandran reflected on his desire to help people like the man he spoke to.
鈥淚 was wrestling with a pressing question: How can we leverage technology to provide autonomy and empower individuals like him?鈥� he said.
Ramachandran and his classmate, Sriram Nallani, realized the answer to that question involved artificial intelligence. They used AI to create an algorithm that can be used to classify electroencephalogram (EEG) signals, which can be used to control prosthetics.
鈥淚t’s a key to a new realm of interaction, where your thoughts seamlessly translate into action; where technology is an invisible, intuitive extension of the human experience,鈥� Ramachandran told WTOP.
Ramachandran has been programming since he was in third grade, and used to create video games using HTML and JavaScript. Instead of playing the video games, though, he said he 鈥済ot addicted to creating them,鈥� and spent hours coding.
When he was in middle school, Ramachandran said he released a game on the platform Steam. But none of that compared to his latest efforts.
Ramachandran said he and Nalini considered different types of available technology for analyzing brain signals. In some cases, patients get implants, which Ramachandran said are innovative but 鈥渞equire a level of invasiveness that isn鈥檛 really ideal for everyone.鈥�
A traditional EEG headset is another alternative, but Ramachandran said those are complicated 鈥渄ue to needing so many electrodes, and frankly, not as accurate as we鈥檇 hope, especially when it comes to classifying movements.鈥�
So, the two students took the EEG technology and streamlined it.
鈥淲e basically used this AI algorithm as the embodiment for this vision,鈥� Ramachandran said. 鈥淚t鈥檚 designed to work with just a handful of electrodes.鈥�
The innovation is helping with accuracy, he said. Previously, the maximum accuracy he鈥檚 seen is 98%, 鈥渨hich means that there鈥檚 going to be two mistakes out of every 100 movements.鈥�
With the help of the algorithm, Ramachandran said there鈥檚 鈥渃lassification accuracy that reaches up to the zenith, up to 100% accuracy, which is really not just an improvement, it鈥檚 a revolution.鈥�
The technology, Ramachandran said, 鈥渁llows people to basically control prosthetics or control devices using their brain signals.鈥�
The pair published their findings .
Their work, he said, helps 鈥減rovide a cost-effective solution to prosthetics.鈥�
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