<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Arduino |</title><link>https://deebhan-portfolio-github-io-ut7q.vercel.app/tags/arduino/</link><atom:link href="https://deebhan-portfolio-github-io-ut7q.vercel.app/tags/arduino/index.xml" rel="self" type="application/rss+xml"/><description>Arduino</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sun, 01 Feb 2026 00:00:00 +0000</lastBuildDate><image><url>https://deebhan-portfolio-github-io-ut7q.vercel.app/media/icon_hu_eee4a95885829ab2.png</url><title>Arduino</title><link>https://deebhan-portfolio-github-io-ut7q.vercel.app/tags/arduino/</link></image><item><title>EMG-Based Smart Wheelchair</title><link>https://deebhan-portfolio-github-io-ut7q.vercel.app/projects/smart-wheelchair/</link><pubDate>Sun, 01 Feb 2026 00:00:00 +0000</pubDate><guid>https://deebhan-portfolio-github-io-ut7q.vercel.app/projects/smart-wheelchair/</guid><description>&lt;p&gt;A smart wheelchair prototype that uses EMG sensors, Arduino, and ESP32 to control wheelchair movement through muscle signals, trained using machine learning — aimed at improving mobility for people with physical disabilities.&lt;/p&gt;</description></item></channel></rss>