Getting in your daily exercise is vital to living a healthy life and having proper form when squatting can go a long way towards achieving that goal without causing joint pain from doing them incorrectly. The Squats Counter is a device worn around the thigh that utilizes machine learning and TensorFlow Lite to automatically track the user’s form and count how many squats have been performed. 

Creator Manas Pange started his project by flashing the tf4micro-moition-kit code to a Nano 33 BLE Sense, which features an onboard three-axis accelerometer. From there, he opened the Tiny Motion Trainer Experiment by Google that connects to the Arduino over Bluetooth® and captures many successive samples of motion. After gathering enough proper and improper form samples, Manas trained, tested, and deployed the resulting model to the board.

Every time a proper squat is completed, the counter ticks down by one until it reaches a predefined goal.

For more details about the Squats Counter, which was recently named a winner in the TensorFlow Lite for Microcontroller Challenge, you can view its GitHub repository here. 

Boards:Nano 33 BLE Sense

Categories:ArduinoMachine Learning

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