The latest articles on DEV Community by Amir Mohammad Hemmati (@youngalpaccino). https://dev.to/youngalpaccino https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3966207%2F8fe91360-9bd2-422e-9957-5465fefe6e23.jpeg https://dev.to/youngalpaccino en Amir Mohammad Hemmati Wed, 03 Jun 2026 09:47:36 +0000 https://dev.to/youngalpaccino/hey-i-want-collaborators-on-developing-on-raspberry-pi-299l https://dev.to/youngalpaccino/hey-i-want-collaborators-on-developing-on-raspberry-pi-299l <p><strong>Dear</strong> <strong>AI, Embedded and real-time backend developers</strong>, 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)<br> read the project infra.<br> If you want to become an open-source programmer working on this project, I would be happily add you as collaborator.<br> by any means after visiting the project I would be happy to share the private repo so that you would know of the process.</p> <div class="ltag-github-readme-tag"> <div class="readme-overview"> <h2> <img src="https://assets.dev.to/assets/github-logo-5a155e1f9a670af7944dd5e12375bc76ed542ea80224905ecaf878b9157cdefc.svg" alt="GitHub logo"> <a href="https://github.com/YoungAlpaccino" rel="noopener noreferrer"> YoungAlpaccino </a> / <a href="https://github.com/YoungAlpaccino/EEG-EMG-signal-processing-via-Rasberry-PI" rel="noopener noreferrer"> EEG-EMG-signal-processing-via-Rasberry-PI </a> </h2> <h3> NOT A SHOWCASE THIS ONE. THIS ONE IS ONE OF MY FAVORITE WORKFLOWS CAUSE I LOVE SIGNAL PROCESSING IN HEALTH MATTERS </h3> </div> <div class="ltag-github-body"> <div id="readme" class="md"> <div class="markdown-heading"> <h1 class="heading-element">biosignal — EEG/EMG capture, analysis &amp; anomaly detection</h1> </div> <p>Capture biosignals from the human body/brain, clean them, find anomalies, and report a result. Built to run <strong>on your PC today</strong> (synthetic signals) and on a <strong>Raspberry Pi with a real biosignal front-end</strong> later — same code, swap the source.</p> <div class="snippet-clipboard-content notranslate position-relative overflow-auto"><pre class="notranslate"><code>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) </code></pre></div> <div class="markdown-heading"> <h2 class="heading-element">What EEG and EMG are</h2> </div> <ul> <li> <strong>EEG</strong> (electroencephalography) — tiny electrical voltages from <strong>brain</strong> activity measured on the scalp. Lives at <strong>0.5–45 Hz</strong>, split into bands (delta, theta, alpha, beta, gamma). Microvolt-scale → needs a sensitive amplifier.</li> <li> <strong>EMG</strong> (electromyography) — electrical activity of <strong>muscles</strong>, measured on the skin over a muscle. Faster (<strong>20–450 Hz</strong>), larger amplitude than EEG.</li> </ul> <p>Both are weak analog voltages, so they need…</p> </div> </div> <div class="gh-btn-container"><a class="gh-btn" href="https://github.com/YoungAlpaccino/EEG-EMG-signal-processing-via-Rasberry-PI" rel="noopener noreferrer">View on GitHub</a></div> </div> <p><a href="https://github.com/YoungAlpaccino/EEG-EMG-signal-processing-via-Rasberry-PI.git" rel="noopener noreferrer">https://github.com/YoungAlpaccino/EEG-EMG-signal-processing-via-Rasberry-PI.git</a></p> ai python machinelearning datascience