Dear AI, Embedded and real-time backend developers, Currently am working on how we could make a configurable Raspberry-PI on behalf of signal processing and AI-integrated back-end somehow that received signals would be getting stored, processed, and later on make an AI trained by the data for diagnosis of EEG/EMG signals.(brain and body healthcare)
read the project infra.
If you want to become an open-source programmer working on this project, I would be happily add you as collaborator.
by any means after visiting the project I would be happy to share the private repo so that you would know of the process.
YoungAlpaccino
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EEG-EMG-signal-processing-via-Rasberry-PI
NOT A SHOWCASE THIS ONE. THIS ONE IS ONE OF MY FAVORITE WORKFLOWS CAUSE I LOVE SIGNAL PROCESSING IN HEALTH MATTERS
biosignal — EEG/EMG capture, analysis & anomaly detection
Capture biosignals from the human body/brain, clean them, find anomalies, and report a result. Built to run on your PC today (synthetic signals) and on a Raspberry Pi with a real biosignal front-end later — same code, swap the source.
ACQUIRE ──► FILTER ──► FEATURES ──► DETECT ANOMALIES ──► REPORT + PLOT
EEG/EMG band-pass band power robust z-score verdict + PNG
(sensor / + notch RMS, ZCR on windowed RMS
synthetic) (mains hum)
What EEG and EMG are
- EEG (electroencephalography) — tiny electrical voltages from brain activity measured on the scalp. Lives at 0.5–45 Hz, split into bands (delta, theta, alpha, beta, gamma). Microvolt-scale → needs a sensitive amplifier.
- EMG (electromyography) — electrical activity of muscles, measured on the skin over a muscle. Faster (20–450 Hz), larger amplitude than EEG.
Both are weak analog voltages, so they need…
https://github.com/YoungAlpaccino/EEG-EMG-signal-processing-via-Rasberry-PI.git
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