Predicting Finger Movement with a Bracelet & Open Source Tech

Can you predict finger movement using nothing but a bracelet on your forearm? After three years of late nights, debugging, and prototypes that barely held together, I finally have an answer — and the results are better than I expected. Welcome to the OpenMuscle Project — an open-source, open-hardware initiative to create affordable, modular prosthetic sensors, human interface devices, and experimental wearable tech that anyone can build, test, and improve. In this video, I share the journey behind the FlexGrid pressure-sensing bracelet and the LASK5 labeling device — two core tools that enabled me to train a real-time machine learning model to predict finger flexion and extension from the forearm alone. We’ll cover: Why proprietary prosthetic tech made me start OpenMuscle How I trained a supervised ML model using a homemade labeler Flex PCB design struggles (and wins!) Power, Wi-Fi, and OLED debugging hell A live prediction demo that finally proves the concept Whether you’re into robotics, wearable tech, assistive devices, or open-source innovation — this is just the beginning. 🔧 Build It Yourself 🧠 GitHub (code, schematics, PCB files): https://github.com/Open-Muscle/OpenMu... 🎮 Discord (chat, updates, Q&A):   / discord   ☕ Support future builds & videos: https://patreon.com/turfptax?utm_medi... 💬 Want to help? Like, subscribe, and share this project. Together, we can build a better future — open, accessible, and community-powered. 🏷️ Hashtags: #OpenMuscle #FlexGrid #LASK5 #OpenHardware #ESP32 #Prosthetics #WearableTech #MachineLearning #Biometrics #DIYTech #HumanInterfaceDevice