TinyNML is a growing collection of embedded machine learning projects developed in the Neuromechatronics Lab at Carnegie Mellon University. The repository focuses on deploying ML models on resource-constrained microcontrollers like the Raspberry Pi Pico and other edge devices.
Whether it’s motion recognition, gesture control, biosignal processing, or edge AI inference pipelines, TinyNML provides a collaborative platform for prototyping and deploying models on embedded hardware.
| Project | Description | Language | Hardware |
|---|---|---|---|
| pico_motion_classifier | Real-time circular motion classification using MPU6050 | C++ | Pico W + MPU6050 + SSD1306 |
| pico_emg_gesture_classifier | EMG-based gesture classification | CircuitPython | Pico W + EMG electrodes |
| pico_cnn_mnist_classifier | CNN digit recognition with weight extraction (no TFLite) | CircuitPython | Pico + OV7670 camera |