devnithw/gesture-tinyml
Embedded machine learning for gesture recognition using Arduino Nano 33 BLE Sense. Includes source code for programming the board and notebooks for training the model.
This project helps engineers and hobbyists develop custom gesture recognition systems using an Arduino Nano 33 BLE Sense. You can record specific arm movements like a punch or flex, then use this data to train a tiny machine learning model. The output is a program that allows the Arduino board to classify and predict those gestures in real-time based on its accelerometer data.
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Use this if you need to quickly prototype or implement a simple, low-power gesture recognition feature for an embedded device.
Not ideal if you require advanced gesture analysis, need to classify many complex gestures, or are working with different hardware platforms.
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Language
C
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Last pushed
Apr 25, 2024
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