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AI uncovers rapid changes in Parkinson's brain signals by separating rhythms from background activity
A research team led by professor Ji-Woong Choi of the Department of Electrical Engineering and Computer Science at DGIST has developed NONOS, a deep learning–based analysis technology that precisely separates rhythms from the underlying…
AI Summary
A team led by Professor Ji‑Woong Choi at DGIST created NONOS, a deep‑learning tool that separates rhythmic brain activity from background signals with high temporal resolution. The method was developed in collaboration with researchers from Kumoh National Institute of Technology, Korea University, and the Korea Brain Research Institute. NONOS isolates oscillatory components—regularly repeating electrical rhythms—from non‑oscillatory background noise in brain recordings. The results, published in NeuroImage, demonstrate the technique’s ability to extract clear rhythmic signals, analogous to picking out a single voice in a noisy environment.
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